diff --git a/config.json b/config.json new file mode 100644 index 0000000000000000000000000000000000000000..32e5f508d07378286598a4173c52035f1c5414f8 --- /dev/null +++ b/config.json @@ -0,0 +1,45 @@ +{ + "_name_or_path": "lmsys/vicuna-13b-v1.5", + "architectures": [ + "LlavaLlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 1, + "eos_token_id": 2, + "freeze_mm_mlp_adapter": false, + "hidden_act": "silu", + "hidden_size": 5120, + "image_aspect_ratio": "pad", + "initializer_range": 0.02, + "intermediate_size": 13824, + "max_length": 4096, + "max_position_embeddings": 4096, + "mm_hidden_size": 1024, + "mm_patch_merge_type": "flat", + "mm_projector_lr": null, + "mm_projector_type": "mlp2x_gelu", + "mm_use_im_patch_token": false, + "mm_use_im_start_end": false, + "mm_vision_select_feature": "patch", + "mm_vision_select_layer": -2, + "mm_vision_tower": "openai/clip-vit-large-patch14-336", + "model_type": "llava_llama", + "num_attention_heads": 40, + "num_hidden_layers": 40, + "num_key_value_heads": 40, + "pad_token_id": 0, + "pretraining_tp": 1, + "rms_norm_eps": 1e-05, + "rope_scaling": null, + "rope_theta": 10000.0, + "tie_word_embeddings": false, + "tokenizer_model_max_length": 1560, + "tokenizer_padding_side": "right", + "torch_dtype": "bfloat16", + "transformers_version": "4.36.2", + "tune_mm_mlp_adapter": false, + "use_cache": true, + "use_mm_proj": true, + "vocab_size": 32000 +} diff --git a/headcut_mask_3p67/0.pth b/headcut_mask_3p67/0.pth new file mode 100644 index 0000000000000000000000000000000000000000..8ec9bab63c4bd1fb0839cbf77c052a685f06f0be --- /dev/null +++ b/headcut_mask_3p67/0.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8b9e56ed6127a980308a442909092f02a52cb4d87bfc24532aa6272685fe4247 +size 1086 diff --git a/headcut_mask_3p67/1.pth b/headcut_mask_3p67/1.pth new file mode 100644 index 0000000000000000000000000000000000000000..6ddaa47c57e69098e6def45e3e85d7897289b87f --- /dev/null +++ b/headcut_mask_3p67/1.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:424a0b376990caa5d86f6353e3c0206532903814a51a9846ee87f522aad04bbf +size 1086 diff --git a/headcut_mask_3p67/10.pth b/headcut_mask_3p67/10.pth new file mode 100644 index 0000000000000000000000000000000000000000..375f8df29fd8c340702f8b1f1057fd3fec46a8b6 --- /dev/null +++ b/headcut_mask_3p67/10.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2bb9611827c68bd7cd953db744e33e38512dbec375b173f89772eadc102bbc64 +size 1155 diff --git a/headcut_mask_3p67/11.pth b/headcut_mask_3p67/11.pth new file mode 100644 index 0000000000000000000000000000000000000000..2d60371e64fe928f8cdc3439d1e50031c35aa3fc --- /dev/null +++ b/headcut_mask_3p67/11.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:84f46bf6288508158790660d90d2c542e0f8015788db75d2eb134fc696e5bea3 +size 1155 diff --git a/headcut_mask_3p67/12.pth b/headcut_mask_3p67/12.pth new file mode 100644 index 0000000000000000000000000000000000000000..f1852d01e590a6fb56d1d8c410ee768eb8464ec2 --- /dev/null +++ b/headcut_mask_3p67/12.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8dfcc4b3c6c5cffbd6b811f2a7ab396aa25255c9de4c2e5921c0c07a0ce8c7bd +size 1155 diff --git a/headcut_mask_3p67/13.pth b/headcut_mask_3p67/13.pth new file mode 100644 index 0000000000000000000000000000000000000000..48623021007ea84256dbc384e8f7872973609586 --- /dev/null +++ b/headcut_mask_3p67/13.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:223dd3a8636ca048241f6237545ecbbadcfc74b349ba2f6fdea916a808f29dd0 +size 1155 diff --git a/headcut_mask_3p67/14.pth b/headcut_mask_3p67/14.pth new file mode 100644 index 0000000000000000000000000000000000000000..2f4a4e4010eb6a74e4bcd49183dc460720a7295d --- /dev/null +++ b/headcut_mask_3p67/14.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eab1f1767e6e0bb97df5cd9e7379c169ad514a2b0ea341ab88010ceb3308532e +size 1155 diff --git a/headcut_mask_3p67/15.pth b/headcut_mask_3p67/15.pth new file mode 100644 index 0000000000000000000000000000000000000000..e902837669100b34d51cb2e251610f916f298d56 --- /dev/null +++ b/headcut_mask_3p67/15.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d72e6a062da7986efc37e7ffc3ddac0ecc27cda0d03c448810b0fddb9d19a2e0 +size 1155 diff --git a/headcut_mask_3p67/16.pth b/headcut_mask_3p67/16.pth new file mode 100644 index 0000000000000000000000000000000000000000..c007e245c9c324e4d5f0fc2ccf79ae501806b911 --- /dev/null +++ b/headcut_mask_3p67/16.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6a8d71f6d290269f451a97c055191b6754589fe9c845a8788d08a9c6c3555b97 +size 1155 diff --git a/headcut_mask_3p67/17.pth b/headcut_mask_3p67/17.pth new file mode 100644 index 0000000000000000000000000000000000000000..f82603a82c7ac0d10984320018d7ff90c280d7d3 --- /dev/null +++ b/headcut_mask_3p67/17.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:990c4174d0cc904366efc9ebea2075038131023eacc56ac73b89bec77c68a4a2 +size 1155 diff --git a/headcut_mask_3p67/18.pth b/headcut_mask_3p67/18.pth new file mode 100644 index 0000000000000000000000000000000000000000..9a9020e9d1a2e41128261440444825c63a4c7f5f --- /dev/null +++ b/headcut_mask_3p67/18.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a1aeb9a6f68c255355fce36d6877e9295fcc7372f913b9821fa327fc2d72d82d +size 1155 diff --git a/headcut_mask_3p67/19.pth b/headcut_mask_3p67/19.pth new file mode 100644 index 0000000000000000000000000000000000000000..7a4018cf7373ff8d42442d47b106cd2700a2a50f --- /dev/null +++ b/headcut_mask_3p67/19.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1c60bef878d8883962eecabe6bdc4e464b215156e682fe0319bf48f151410e96 +size 1155 diff --git a/headcut_mask_3p67/2.pth b/headcut_mask_3p67/2.pth new file mode 100644 index 0000000000000000000000000000000000000000..ee94f7553f45acbf97d2a360693bf8833594088e --- /dev/null +++ b/headcut_mask_3p67/2.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d595e7d7c1d7f7e6ab277a82804eaf49ca7ecb3f451f80ca46b987bd48b48e30 +size 1086 diff --git a/headcut_mask_3p67/20.pth b/headcut_mask_3p67/20.pth new file mode 100644 index 0000000000000000000000000000000000000000..a2598e2589f75389e381770e26769978d067d5c6 --- /dev/null +++ b/headcut_mask_3p67/20.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9d816d5f933cedfc2959d51076c0a3ca05b80a462773a322eb1ec9a18c0fa732 +size 1155 diff --git a/headcut_mask_3p67/21.pth b/headcut_mask_3p67/21.pth new file mode 100644 index 0000000000000000000000000000000000000000..f2750f4586bbe05a81b9c9194f2192f95bb5e3ec --- /dev/null +++ b/headcut_mask_3p67/21.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:524f0cd620492ed32560761c16af3e0b545a8be4ae9dfc0d03a99c004e85f1fd +size 1155 diff --git a/headcut_mask_3p67/22.pth b/headcut_mask_3p67/22.pth new file mode 100644 index 0000000000000000000000000000000000000000..6af40b716bc72e109dfc270a84feffc41474101b --- /dev/null +++ b/headcut_mask_3p67/22.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:031fbf160201f90d59dcf7c3b0f47a440718b1fa4f98808cd9e9fde40821713a +size 1155 diff --git a/headcut_mask_3p67/23.pth b/headcut_mask_3p67/23.pth new file mode 100644 index 0000000000000000000000000000000000000000..96193649ac06b7348c252a6cbb778f5160f669f4 --- /dev/null +++ b/headcut_mask_3p67/23.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eaca8a9ddcfde6cb93dc7725ab06523d619426928a6dc8acedb1ebefdf2e0812 +size 1155 diff --git a/headcut_mask_3p67/24.pth b/headcut_mask_3p67/24.pth new file mode 100644 index 0000000000000000000000000000000000000000..6617b363dd73ba871b28f95538e87b2f3fd2a3e6 --- /dev/null +++ b/headcut_mask_3p67/24.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8232aa68127a7a1494120ce7da98dd988c8d057c7509b3f171d79ace114073b3 +size 1155 diff --git a/headcut_mask_3p67/25.pth b/headcut_mask_3p67/25.pth new file mode 100644 index 0000000000000000000000000000000000000000..eb132f6fc93649531fb97d04146420d85636ff5e --- /dev/null +++ b/headcut_mask_3p67/25.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bafe13ed42077a63a15e7e06b8903f5650858e35c7f0702f8807797af90aee77 +size 1155 diff --git a/headcut_mask_3p67/26.pth b/headcut_mask_3p67/26.pth new file mode 100644 index 0000000000000000000000000000000000000000..85986119792c1d6c7beb7a09a200291255e9c676 --- /dev/null +++ b/headcut_mask_3p67/26.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e05a0c7ee4c1d819437faf49a7dec8d802d0a332ece890eaea34512c8b12c91d +size 1155 diff --git a/headcut_mask_3p67/27.pth b/headcut_mask_3p67/27.pth new file mode 100644 index 0000000000000000000000000000000000000000..269c3414efd20a8d9d8f39d749aeba03259f5c6f --- /dev/null +++ b/headcut_mask_3p67/27.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:420c29fc5e1eeb102cb54d60aa9018e57e4eafc3fc0af705d42c298d0c65b801 +size 1155 diff --git a/headcut_mask_3p67/28.pth b/headcut_mask_3p67/28.pth new file mode 100644 index 0000000000000000000000000000000000000000..7b35405ba1d30360efe0a8a41e66c4c550437967 --- /dev/null +++ b/headcut_mask_3p67/28.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b913ebb397e7e9056c9cacd977aab668462cce09b044152a36466c68eaeb0890 +size 1155 diff --git a/headcut_mask_3p67/29.pth b/headcut_mask_3p67/29.pth new file mode 100644 index 0000000000000000000000000000000000000000..3b49ba3f5cdd3302d78558e22b2987e20389ee35 --- /dev/null +++ b/headcut_mask_3p67/29.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:587fb7c05256d2c96db21cfb258f9425e102c132014101091ae54ce81583ae19 +size 1155 diff --git a/headcut_mask_3p67/3.pth b/headcut_mask_3p67/3.pth new file mode 100644 index 0000000000000000000000000000000000000000..126d9a019125fae57d885164b2406ae3cf6ee32d --- /dev/null +++ b/headcut_mask_3p67/3.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4271bcca623f7aa8057d3af35166258e80a19ed4989c25ec9f2da9563922f319 +size 1086 diff --git a/headcut_mask_3p67/30.pth b/headcut_mask_3p67/30.pth new file mode 100644 index 0000000000000000000000000000000000000000..76618a055a26ee3b4065de0ee9f1a25915e01ce1 --- /dev/null +++ b/headcut_mask_3p67/30.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7e2e58ba07180eb45d1dce42707bc0c82d04786f6759f2741f7993b5b4c8a510 +size 1155 diff --git a/headcut_mask_3p67/31.pth b/headcut_mask_3p67/31.pth new file mode 100644 index 0000000000000000000000000000000000000000..e153612129106c3a36abd689e5af6a8590b6d39b --- /dev/null +++ b/headcut_mask_3p67/31.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ecf13c5e773db32dc2988b034f3cc8c811776aad5ee778e230cb7acd3db38426 +size 1155 diff --git a/headcut_mask_3p67/32.pth b/headcut_mask_3p67/32.pth new file mode 100644 index 0000000000000000000000000000000000000000..fd94813d589dfa35756fd555ad7fd2acd415079e --- /dev/null +++ b/headcut_mask_3p67/32.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dcb39d0a7f3d32871cde5848627dcbb2b40f2654e5cd2715af19b6dbb4b36932 +size 1155 diff --git a/headcut_mask_3p67/33.pth b/headcut_mask_3p67/33.pth new file mode 100644 index 0000000000000000000000000000000000000000..11cdd299a9ebf3a78e8cb4033a7b6ed06fceb1c6 --- /dev/null +++ b/headcut_mask_3p67/33.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d6ba2e384a7389ec3b2ba5b738d5ae2b86721aa0c734ed982a70bd97566c5031 +size 1155 diff --git a/headcut_mask_3p67/34.pth b/headcut_mask_3p67/34.pth new file mode 100644 index 0000000000000000000000000000000000000000..3c75d2d74e0207a0a2fe49e2da40272ef7666179 --- /dev/null +++ b/headcut_mask_3p67/34.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:36602961f4780500b4af89602758a816eea7515716b486670e78e265f3228db5 +size 1155 diff --git a/headcut_mask_3p67/35.pth b/headcut_mask_3p67/35.pth new file mode 100644 index 0000000000000000000000000000000000000000..dfef644d87146c4cb3eadd4b8f4a7dfb23856343 --- /dev/null +++ b/headcut_mask_3p67/35.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:aa2d4a17b06969a9338de44a05ff6dc272329b3f3774538f82daa8750f45dc81 +size 1155 diff --git a/headcut_mask_3p67/36.pth b/headcut_mask_3p67/36.pth new file mode 100644 index 0000000000000000000000000000000000000000..938874ed93454c77486be8bbded1f5a72c261835 --- /dev/null +++ b/headcut_mask_3p67/36.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:58c14d3476676fa0f07ee8d9697a08fd9acf64e53df8b9f3c8f8bea98343d88e +size 1155 diff --git a/headcut_mask_3p67/37.pth b/headcut_mask_3p67/37.pth new file mode 100644 index 0000000000000000000000000000000000000000..c454331515839d15eda1fb6b1046d63b0d891ff5 --- /dev/null +++ b/headcut_mask_3p67/37.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6c4f3ba785ed7ec0be36e6cf388e08d98559e1088d000b9689d98aaad5b0f341 +size 1155 diff --git a/headcut_mask_3p67/38.pth b/headcut_mask_3p67/38.pth new file mode 100644 index 0000000000000000000000000000000000000000..f882d6d6ecaee6eb25ac465cf6f902e42f37e830 --- /dev/null +++ b/headcut_mask_3p67/38.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:65230cf1f3d7be3ff6a6f7aad691d9add7d9132a4328002417c0b246f533daa0 +size 1155 diff --git a/headcut_mask_3p67/39.pth b/headcut_mask_3p67/39.pth new file mode 100644 index 0000000000000000000000000000000000000000..8270ff11817acbe946aaa8807aed64c51cdad48c --- /dev/null +++ b/headcut_mask_3p67/39.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b205ba9c0de51ddf420ad5d398bfe27d50dcff5119af47658a4762ccc4160f68 +size 1155 diff --git a/headcut_mask_3p67/4.pth b/headcut_mask_3p67/4.pth new file mode 100644 index 0000000000000000000000000000000000000000..35c826007e27397e4f8fea4c68cc3093a26cad7a --- /dev/null +++ b/headcut_mask_3p67/4.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5d14812e6aa11cb8321f58df2cae98fb83c97bdafd9ffd5d6ddef1a913324e1d +size 1086 diff --git a/headcut_mask_3p67/5.pth b/headcut_mask_3p67/5.pth new file mode 100644 index 0000000000000000000000000000000000000000..7330739efef7f54c1a59c26c05d0825ccfa63f7f --- /dev/null +++ b/headcut_mask_3p67/5.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d613713664cc03ea59215eb9d19cc8ca1fb52410754d9845ec6b79bed4ea3449 +size 1086 diff --git a/headcut_mask_3p67/6.pth b/headcut_mask_3p67/6.pth new file mode 100644 index 0000000000000000000000000000000000000000..09c80a89e59c2b3308fdbbe896e338e51d3ebd01 --- /dev/null +++ b/headcut_mask_3p67/6.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c4ad6a2c9cdafd520ffedd5d90f2f8ec36bfddabf9d6e77d3bb02848b60a6e6e +size 1086 diff --git a/headcut_mask_3p67/7.pth b/headcut_mask_3p67/7.pth new file mode 100644 index 0000000000000000000000000000000000000000..ec9b93259f5bcba3a45d38e61edbe3ceeac2346d --- /dev/null +++ b/headcut_mask_3p67/7.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e117c779be6f6e9d74f644029273e86d575e63a741f7979196d976fc1ca44c62 +size 1086 diff --git a/headcut_mask_3p67/8.pth b/headcut_mask_3p67/8.pth new file mode 100644 index 0000000000000000000000000000000000000000..974f54d1975849537da464a379eb2f605c226786 --- /dev/null +++ b/headcut_mask_3p67/8.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:22e124d901c05bd9d19011e199fcb3abf2730bbcca97e32111fb11bb87e4fffc +size 1086 diff --git a/headcut_mask_3p67/9.pth b/headcut_mask_3p67/9.pth new file mode 100644 index 0000000000000000000000000000000000000000..1aa232342d9702151492da25b94ac18fec501d2b --- /dev/null +++ b/headcut_mask_3p67/9.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9dd8aa2037ac9d45e951d2777ef747f7841c6daf8aeac5ba5bd69ee3f9a360bd +size 1086 diff --git a/model-00001-of-00006.safetensors b/model-00001-of-00006.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..d6cd0ff058755188cdc9666628b00877572e9fbb --- /dev/null +++ b/model-00001-of-00006.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d559fa01c34da0aecb7c273f3a6cf55addc5264bd99d62a4f87ec7de5aec2396 +size 4978265800 diff --git a/model-00002-of-00006.safetensors b/model-00002-of-00006.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..17e2e366cf87adb090f6e785a064c0e2df41a761 --- /dev/null +++ b/model-00002-of-00006.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:98d8c39720cc027c4b4e40592cfabe8d5fe2a4a556483b4aa5dfbdf73e69f10d +size 4970422232 diff --git a/model-00003-of-00006.safetensors b/model-00003-of-00006.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..5a6d656eed81ffbc61e0c8114903a34eab190f2c --- /dev/null +++ b/model-00003-of-00006.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1d9321a1f58401a4165ed04cbe9593d664e6b288fc8d10d895e5cdac4f17dcd0 +size 4970422256 diff --git a/model-00004-of-00006.safetensors b/model-00004-of-00006.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..f7509f9afc4ab0aad3ec8a849259623755e8ef23 --- /dev/null +++ b/model-00004-of-00006.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b2dbecacf52532c933f168748fe35bbcf512bae73e8137002bdf175ed94b7d45 +size 4933701504 diff --git a/model-00005-of-00006.safetensors b/model-00005-of-00006.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..5c1d04dcb035e3880a6567bfeef3d7cdeeb365b8 --- /dev/null +++ b/model-00005-of-00006.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:45fb012f1c7d53f1771f868550908ec18af182aaf822647d4eb94be0edbc5ff7 +size 4933722216 diff --git a/model-00006-of-00006.safetensors b/model-00006-of-00006.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..6bfd252fff0f57bba871af7340bc8841f6474eeb --- /dev/null +++ b/model-00006-of-00006.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3f5a5e9db88af642a1b044b716a65748c1374c193bef5261b8b2b9ca12cbbbaa +size 1915248664 diff --git a/model.safetensors.index.json b/model.safetensors.index.json new file mode 100644 index 0000000000000000000000000000000000000000..0b710ea4003a96fb2d14b8f7775e12bcfcfb7c2a --- /dev/null +++ b/model.safetensors.index.json @@ -0,0 +1,765 @@ +{ + "metadata": { + "total_size": 26701678592 + }, + "weight_map": { + "lm_head.weight": "model-00006-of-00006.safetensors", + "model.embed_tokens.weight": "model-00001-of-00006.safetensors", + "model.layers.0.input_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.0.mlp.down_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.0.mlp.up_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.1.input_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.1.mlp.down_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.1.mlp.up_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.10.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.10.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.10.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.10.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.10.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.10.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.10.self_attn.o_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.10.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.10.self_attn.v_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.11.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.11.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.11.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.11.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.11.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.11.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.11.self_attn.o_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.11.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.11.self_attn.v_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.12.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.12.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.12.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.12.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.12.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.12.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.12.self_attn.o_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.12.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.12.self_attn.v_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.13.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.13.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.13.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.13.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.13.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.13.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.13.self_attn.o_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.13.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.13.self_attn.v_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.14.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.14.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.14.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.14.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.14.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.14.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.14.self_attn.o_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.14.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.14.self_attn.v_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.15.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.15.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.15.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.15.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.15.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.15.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.15.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.15.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.15.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.16.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.16.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.16.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.16.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.16.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.16.self_attn.k_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.16.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.16.self_attn.q_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.16.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.17.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.17.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.17.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.17.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.17.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.17.self_attn.k_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.17.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.17.self_attn.q_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.17.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.18.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.18.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.18.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.18.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.18.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.18.self_attn.k_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.18.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.18.self_attn.q_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.18.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.19.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.19.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.19.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.19.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.19.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.19.self_attn.k_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.19.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.19.self_attn.q_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.19.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.2.input_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.2.mlp.down_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.2.mlp.up_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.20.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.20.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.20.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.20.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.20.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.20.self_attn.k_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.20.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.20.self_attn.q_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.20.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.21.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.21.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.21.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.21.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.21.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.21.self_attn.k_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.21.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.21.self_attn.q_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.21.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.22.input_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.22.mlp.down_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.22.mlp.gate_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.22.mlp.up_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.22.post_attention_layernorm.weight": "model-00003-of-00006.safetensors", + "model.layers.22.self_attn.k_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.22.self_attn.o_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.22.self_attn.q_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.22.self_attn.v_proj.weight": "model-00003-of-00006.safetensors", + "model.layers.23.input_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.23.mlp.down_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.23.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.23.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.23.post_attention_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.23.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.23.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.23.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.23.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.24.input_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.24.mlp.down_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.24.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.24.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.24.post_attention_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.24.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.24.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.24.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.24.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.25.input_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.25.mlp.down_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.25.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.25.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.25.post_attention_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.25.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.25.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.25.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.25.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.26.input_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.26.mlp.down_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.26.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.26.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.26.post_attention_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.26.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.26.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.26.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.26.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.27.input_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.27.mlp.down_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.27.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.27.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.27.post_attention_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.27.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.27.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.27.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.27.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.28.input_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.28.mlp.down_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.28.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.28.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.28.post_attention_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.28.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.28.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.28.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.28.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.29.input_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.29.mlp.down_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.29.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.29.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.29.post_attention_layernorm.weight": "model-00004-of-00006.safetensors", + "model.layers.29.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.29.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.29.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.29.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.3.input_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.3.mlp.down_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.3.mlp.up_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.30.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.30.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.30.mlp.gate_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.30.mlp.up_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.30.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.30.self_attn.k_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.30.self_attn.o_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.30.self_attn.q_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.30.self_attn.v_proj.weight": "model-00004-of-00006.safetensors", + "model.layers.31.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.31.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.31.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.31.mlp.up_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.31.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.31.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.31.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.31.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.31.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.32.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.32.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.32.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.32.mlp.up_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.32.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.32.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.32.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.32.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.32.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.33.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.33.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.33.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.33.mlp.up_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.33.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.33.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.33.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.33.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.33.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.34.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.34.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.34.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.34.mlp.up_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.34.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.34.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.34.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.34.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.34.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.35.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.35.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.35.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.35.mlp.up_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.35.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.35.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.35.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.35.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.35.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.36.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.36.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.36.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.36.mlp.up_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.36.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.36.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.36.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.36.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.36.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.37.input_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.37.mlp.down_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.37.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.37.mlp.up_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.37.post_attention_layernorm.weight": "model-00005-of-00006.safetensors", + "model.layers.37.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.37.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.37.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.37.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.38.input_layernorm.weight": "model-00006-of-00006.safetensors", + "model.layers.38.mlp.down_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.38.mlp.gate_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.38.mlp.up_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.38.post_attention_layernorm.weight": "model-00006-of-00006.safetensors", + "model.layers.38.self_attn.k_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.38.self_attn.o_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.38.self_attn.q_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.38.self_attn.v_proj.weight": "model-00005-of-00006.safetensors", + "model.layers.39.input_layernorm.weight": "model-00006-of-00006.safetensors", + "model.layers.39.mlp.down_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.39.mlp.gate_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.39.mlp.up_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.39.post_attention_layernorm.weight": "model-00006-of-00006.safetensors", + "model.layers.39.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.39.self_attn.o_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.39.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.39.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.layers.4.input_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.4.mlp.down_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.4.mlp.up_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.5.input_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.5.mlp.down_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.5.mlp.up_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.6.input_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.6.mlp.down_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.6.mlp.up_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00006.safetensors", + "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.7.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.7.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.7.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.7.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.7.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00006.safetensors", + "model.layers.8.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.8.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.8.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.8.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.8.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.8.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.8.self_attn.o_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.8.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.8.self_attn.v_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.9.input_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.9.mlp.down_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.9.mlp.gate_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.9.mlp.up_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00006.safetensors", + "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00006.safetensors", + "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00006.safetensors", + "model.mm_projector.0.bias": "model-00006-of-00006.safetensors", + "model.mm_projector.0.weight": "model-00006-of-00006.safetensors", + "model.mm_projector.2.bias": "model-00006-of-00006.safetensors", + "model.mm_projector.2.weight": "model-00006-of-00006.safetensors", + "model.norm.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.embeddings.class_embedding": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.embeddings.patch_embedding.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.embeddings.position_embedding.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.0.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.1.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.11.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.13.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.14.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.15.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.16.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.17.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.18.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.19.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.2.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.21.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.22.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.23.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.4.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.5.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.6.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.layer_norm1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.layer_norm1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.layer_norm2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.layer_norm2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.mlp.fc1.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.mlp.fc1.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.mlp.fc2.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.mlp.fc2.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.k_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.k_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.out_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.out_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.q_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.q_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.post_layernorm.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.post_layernorm.weight": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.pre_layrnorm.bias": "model-00006-of-00006.safetensors", + "model.vision_tower.vision_tower.vision_model.pre_layrnorm.weight": "model-00006-of-00006.safetensors" + } +} diff --git a/modeling_llama.py b/modeling_llama.py new file mode 100644 index 0000000000000000000000000000000000000000..182dbcc62106eb4392fe106011a6b5f955238637 --- /dev/null +++ b/modeling_llama.py @@ -0,0 +1,1483 @@ +# coding=utf-8 +# Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved. +# +# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX +# and OPT implementations in this library. It has been modified from its +# original forms to accommodate minor architectural differences compared +# to GPT-NeoX and OPT used by the Meta AI team that trained the model. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" PyTorch LLaMA model.""" +import math +import warnings +from typing import List, Optional, Tuple, Union + +import torch +import torch.nn.functional as F +import torch.utils.checkpoint +from torch import nn +from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss + +from ...activations import ACT2FN +from ...cache_utils import Cache, DynamicCache +from ...modeling_attn_mask_utils import ( + AttentionMaskConverter, + _prepare_4d_attention_mask, + _prepare_4d_causal_attention_mask, + _prepare_4d_causal_attention_mask_for_sdpa, +) +from ...modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, SequenceClassifierOutputWithPast +from ...modeling_utils import PreTrainedModel +from ...pytorch_utils import ALL_LAYERNORM_LAYERS, is_torch_greater_or_equal_than_1_13 +from ...utils import ( + add_start_docstrings, + add_start_docstrings_to_model_forward, + is_flash_attn_2_available, + is_flash_attn_greater_or_equal_2_10, + logging, + replace_return_docstrings, +) +from ...utils.import_utils import is_torch_fx_available +from .configuration_llama import LlamaConfig + + +if is_flash_attn_2_available(): + from flash_attn import flash_attn_func, flash_attn_varlen_func + from flash_attn.bert_padding import index_first_axis, pad_input, unpad_input # noqa + + +# This makes `_prepare_4d_causal_attention_mask` a leaf function in the FX graph. +# It means that the function will not be traced through and simply appear as a node in the graph. +if is_torch_fx_available(): + if not is_torch_greater_or_equal_than_1_13: + import torch.fx + + _prepare_4d_causal_attention_mask = torch.fx.wrap(_prepare_4d_causal_attention_mask) + + +logger = logging.get_logger(__name__) + +_CONFIG_FOR_DOC = "LlamaConfig" + +count_drop_head = 0 +def _get_unpad_data(attention_mask): + seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32) + indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten() + max_seqlen_in_batch = seqlens_in_batch.max().item() + cu_seqlens = F.pad(torch.cumsum(seqlens_in_batch, dim=0, dtype=torch.torch.int32), (1, 0)) + return ( + indices, + cu_seqlens, + max_seqlen_in_batch, + ) + + +def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None): + warnings.warn( + "Calling `transformers.models.llama.modeling_llama._prepare_4d_attention_mask` is deprecated and will be removed in v4.37. Use `transformers.modeling_attn_mask_utils._prepare_4d_attention_mask" + ) + return _prepare_4d_attention_mask(mask=mask, dtype=dtype, tgt_len=tgt_len) + + +def _make_causal_mask( + input_ids_shape: torch.Size, dtype: torch.dtype, device: torch.device, past_key_values_length: int = 0 +): + warnings.warn( + "Calling `transformers.models.llama.modeling_llama._make_causal_mask` is deprecated and will be removed in v4.37. Use `transformers.models.llama.modeling_llama.AttentionMaskConverter._make_causal_mask" + ) + return AttentionMaskConverter._make_causal_mask( + input_ids_shape=input_ids_shape, dtype=dtype, device=device, past_key_values_length=past_key_values_length + ) + + +class LlamaRMSNorm(nn.Module): + def __init__(self, hidden_size, eps=1e-6): + """ + LlamaRMSNorm is equivalent to T5LayerNorm + """ + super().__init__() + self.weight = nn.Parameter(torch.ones(hidden_size)) + self.variance_epsilon = eps + + def forward(self, hidden_states): + input_dtype = hidden_states.dtype + hidden_states = hidden_states.to(torch.float32) + variance = hidden_states.pow(2).mean(-1, keepdim=True) + hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon) + return self.weight * hidden_states.to(input_dtype) + + +ALL_LAYERNORM_LAYERS.append(LlamaRMSNorm) + + +class LlamaRotaryEmbedding(nn.Module): + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None): + super().__init__() + + self.dim = dim + self.max_position_embeddings = max_position_embeddings + self.base = base + inv_freq = 1.0 / (self.base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim)) + self.register_buffer("inv_freq", inv_freq, persistent=False) + + # Build here to make `torch.jit.trace` work. + self._set_cos_sin_cache( + seq_len=max_position_embeddings, device=self.inv_freq.device, dtype=torch.get_default_dtype() + ) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype) + + freqs = torch.outer(t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False) + self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False) + + def forward(self, x, seq_len=None): + # x: [bs, num_attention_heads, seq_len, head_size] + if seq_len > self.max_seq_len_cached: + self._set_cos_sin_cache(seq_len=seq_len, device=x.device, dtype=x.dtype) + + return ( + self.cos_cached[:seq_len].to(dtype=x.dtype), + self.sin_cached[:seq_len].to(dtype=x.dtype), + ) + + +class LlamaLinearScalingRotaryEmbedding(LlamaRotaryEmbedding): + """LlamaRotaryEmbedding extended with linear scaling. Credits to the Reddit user /u/kaiokendev""" + + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0): + self.scaling_factor = scaling_factor + super().__init__(dim, max_position_embeddings, base, device) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype) + t = t / self.scaling_factor + + freqs = torch.outer(t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False) + self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False) + + +class LlamaDynamicNTKScalingRotaryEmbedding(LlamaRotaryEmbedding): + """LlamaRotaryEmbedding extended with Dynamic NTK scaling. Credits to the Reddit users /u/bloc97 and /u/emozilla""" + + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0): + self.scaling_factor = scaling_factor + super().__init__(dim, max_position_embeddings, base, device) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + + if seq_len > self.max_position_embeddings: + base = self.base * ( + (self.scaling_factor * seq_len / self.max_position_embeddings) - (self.scaling_factor - 1) + ) ** (self.dim / (self.dim - 2)) + inv_freq = 1.0 / (base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim)) + self.register_buffer("inv_freq", inv_freq, persistent=False) + + t = torch.arange(self.max_seq_len_cached, device=device, dtype=self.inv_freq.dtype) + + freqs = torch.outer(t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer("cos_cached", emb.cos().to(dtype), persistent=False) + self.register_buffer("sin_cached", emb.sin().to(dtype), persistent=False) + + +def rotate_half(x): + """Rotates half the hidden dims of the input.""" + x1 = x[..., : x.shape[-1] // 2] + x2 = x[..., x.shape[-1] // 2 :] + return torch.cat((-x2, x1), dim=-1) + + +def apply_rotary_pos_emb(q, k, cos, sin, position_ids, unsqueeze_dim=1): + """Applies Rotary Position Embedding to the query and key tensors. + + Args: + q (`torch.Tensor`): The query tensor. + k (`torch.Tensor`): The key tensor. + cos (`torch.Tensor`): The cosine part of the rotary embedding. + sin (`torch.Tensor`): The sine part of the rotary embedding. + position_ids (`torch.Tensor`): + The position indices of the tokens corresponding to the query and key tensors. For example, this can be + used to pass offsetted position ids when working with a KV-cache. + unsqueeze_dim (`int`, *optional*, defaults to 1): + The 'unsqueeze_dim' argument specifies the dimension along which to unsqueeze cos[position_ids] and + sin[position_ids] so that they can be properly broadcasted to the dimensions of q and k. For example, note + that cos[position_ids] and sin[position_ids] have the shape [batch_size, seq_len, head_dim]. Then, if q and + k have the shape [batch_size, heads, seq_len, head_dim], then setting unsqueeze_dim=1 makes + cos[position_ids] and sin[position_ids] broadcastable to the shapes of q and k. Similarly, if q and k have + the shape [batch_size, seq_len, heads, head_dim], then set unsqueeze_dim=2. + Returns: + `tuple(torch.Tensor)` comprising of the query and key tensors rotated using the Rotary Position Embedding. + """ + cos = cos[position_ids].unsqueeze(unsqueeze_dim) + sin = sin[position_ids].unsqueeze(unsqueeze_dim) + q_embed = (q * cos) + (rotate_half(q) * sin) + k_embed = (k * cos) + (rotate_half(k) * sin) + return q_embed, k_embed + + +class LlamaMLP(nn.Module): + def __init__(self, config): + super().__init__() + self.config = config + self.hidden_size = config.hidden_size + self.intermediate_size = config.intermediate_size + self.gate_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=False) + self.up_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=False) + self.down_proj = nn.Linear(self.intermediate_size, self.hidden_size, bias=False) + self.act_fn = ACT2FN[config.hidden_act] + + def forward(self, x): + if self.config.pretraining_tp > 1: + slice = self.intermediate_size // self.config.pretraining_tp + gate_proj_slices = self.gate_proj.weight.split(slice, dim=0) + up_proj_slices = self.up_proj.weight.split(slice, dim=0) + down_proj_slices = self.down_proj.weight.split(slice, dim=1) + + gate_proj = torch.cat( + [F.linear(x, gate_proj_slices[i]) for i in range(self.config.pretraining_tp)], dim=-1 + ) + up_proj = torch.cat([F.linear(x, up_proj_slices[i]) for i in range(self.config.pretraining_tp)], dim=-1) + + intermediate_states = (self.act_fn(gate_proj) * up_proj).split(slice, dim=2) + down_proj = [ + F.linear(intermediate_states[i], down_proj_slices[i]) for i in range(self.config.pretraining_tp) + ] + down_proj = sum(down_proj) + else: + down_proj = self.down_proj(self.act_fn(self.gate_proj(x)) * self.up_proj(x)) + + return down_proj + + +def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor: + """ + This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch, + num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim) + """ + batch, num_key_value_heads, slen, head_dim = hidden_states.shape + if n_rep == 1: + return hidden_states + hidden_states = hidden_states[:, :, None, :, :].expand(batch, num_key_value_heads, n_rep, slen, head_dim) + return hidden_states.reshape(batch, num_key_value_heads * n_rep, slen, head_dim) + + +class LlamaAttention(nn.Module): + """Multi-headed attention from 'Attention Is All You Need' paper""" + + def __init__(self, config: LlamaConfig, layer_idx: Optional[int] = None): + super().__init__() + self.config = config + self.layer_idx = layer_idx + if layer_idx is None: + logger.warning_once( + f"Instantiating {self.__class__.__name__} without passing `layer_idx` is not recommended and will " + "to errors during the forward call, if caching is used. Please make sure to provide a `layer_idx` " + "when creating this class." + ) + + self.attention_dropout = config.attention_dropout + self.hidden_size = config.hidden_size + self.num_heads = config.num_attention_heads + self.head_dim = self.hidden_size // self.num_heads + self.num_key_value_heads = config.num_key_value_heads + self.num_key_value_groups = self.num_heads // self.num_key_value_heads + self.max_position_embeddings = config.max_position_embeddings + self.rope_theta = config.rope_theta + self.is_causal = True + + if (self.head_dim * self.num_heads) != self.hidden_size: + raise ValueError( + f"hidden_size must be divisible by num_heads (got `hidden_size`: {self.hidden_size}" + f" and `num_heads`: {self.num_heads})." + ) + + self.q_proj = nn.Linear(self.hidden_size, self.num_heads * self.head_dim, bias=config.attention_bias) + self.k_proj = nn.Linear(self.hidden_size, self.num_key_value_heads * self.head_dim, bias=config.attention_bias) + self.v_proj = nn.Linear(self.hidden_size, self.num_key_value_heads * self.head_dim, bias=config.attention_bias) + self.o_proj = nn.Linear(self.num_heads * self.head_dim, self.hidden_size, bias=config.attention_bias) + self._init_rope() + self.mask = torch.load('headcut_mask_3p67/'+str(self.layer_idx)+'.pth') + def _init_rope(self): + if self.config.rope_scaling is None: + self.rotary_emb = LlamaRotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + base=self.rope_theta, + ) + else: + scaling_type = self.config.rope_scaling["type"] + scaling_factor = self.config.rope_scaling["factor"] + if scaling_type == "linear": + self.rotary_emb = LlamaLinearScalingRotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + scaling_factor=scaling_factor, + base=self.rope_theta, + ) + elif scaling_type == "dynamic": + self.rotary_emb = LlamaDynamicNTKScalingRotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + scaling_factor=scaling_factor, + base=self.rope_theta, + ) + else: + raise ValueError(f"Unknown RoPE scaling type {scaling_type}") + + def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int): + return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous() + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Cache] = None, + output_attentions: bool = False, + use_cache: bool = False, + **kwargs, + ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]: + if "padding_mask" in kwargs: + warnings.warn( + "Passing `padding_mask` is deprecated and will be removed in v4.37. Please make sure use `attention_mask` instead.`" + ) + + bsz, q_len, _ = hidden_states.size() + + if self.config.pretraining_tp > 1: + key_value_slicing = (self.num_key_value_heads * self.head_dim) // self.config.pretraining_tp + query_slices = self.q_proj.weight.split( + (self.num_heads * self.head_dim) // self.config.pretraining_tp, dim=0 + ) + key_slices = self.k_proj.weight.split(key_value_slicing, dim=0) + value_slices = self.v_proj.weight.split(key_value_slicing, dim=0) + + query_states = [F.linear(hidden_states, query_slices[i]) for i in range(self.config.pretraining_tp)] + query_states = torch.cat(query_states, dim=-1) + + key_states = [F.linear(hidden_states, key_slices[i]) for i in range(self.config.pretraining_tp)] + key_states = torch.cat(key_states, dim=-1) + + value_states = [F.linear(hidden_states, value_slices[i]) for i in range(self.config.pretraining_tp)] + value_states = torch.cat(value_states, dim=-1) + + else: + query_states = self.q_proj(hidden_states) + key_states = self.k_proj(hidden_states) + value_states = self.v_proj(hidden_states) + + query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2) + key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + + kv_seq_len = key_states.shape[-2] + if past_key_value is not None: + if self.layer_idx is None: + raise ValueError( + f"The cache structure has changed since version v4.36. If you are using {self.__class__.__name__} " + "for auto-regressive decoding with k/v caching, please make sure to initialize the attention class " + "with a layer index." + ) + kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx) + cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len) + query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids) + + if past_key_value is not None: + cache_kwargs = {"sin": sin, "cos": cos} # Specific to RoPE models + key_states, value_states = past_key_value.update(key_states, value_states, self.layer_idx, cache_kwargs) + + key_states = repeat_kv(key_states, self.num_key_value_groups) + value_states = repeat_kv(value_states, self.num_key_value_groups) + #attn = "local" + attn = "original" + # print("layer_index",self.layer_idx) + ''' + offset=35 + if self.layer_idx<=10 or self.layer_idx>=20: # > 37 + attention_mask = attention_mask.clone() + attention_mask[:,:,offset+576:,offset:offset+576]=float('-inf') + if attention_mask.shape[2]==1: + attention_mask[:,:,:,offset:offset+576]=float('-inf') + attention_mask = attention_mask.clone() + #print(attention_mask) + # print(value_states.shape) + ''' + if attn == "original": + import time + start = time.time() + attn_weights = torch.matmul(query_states, key_states.transpose(2, 3)) / math.sqrt(self.head_dim) #torch.Size([16, 40, 1752, 1752]) + if attn_weights.size() != (bsz, self.num_heads, q_len, kv_seq_len): + raise ValueError( + f"Attention weights should be of size {(bsz, self.num_heads, q_len, kv_seq_len)}, but is" + f" {attn_weights.size()}" + ) + + if attention_mask is not None: + if attention_mask.size() != (bsz, 1, q_len, kv_seq_len): + raise ValueError( + f"Attention mask should be of size {(bsz, 1, q_len, kv_seq_len)}, but is {attention_mask.size()}" + ) + attn_weights = attn_weights + attention_mask + + # upcast attention to fp32 + attn_weights = nn.functional.softmax(attn_weights, dim=-1, dtype=torch.float32).to(query_states.dtype) + attn_weights = nn.functional.dropout(attn_weights, p=self.attention_dropout, training=self.training) + #import pdb; pdb.set_trace() + #if self.layer_idx ==20: + # import pdb; pdb.set_trace() + # mask = torch.load('temp/'+str(self.layer_idx)+'.pth') + + + #import pdb; pdb.set_trace() + if attn_weights.shape[2]>1: + ''' + res_v = torch.sum( attn_weights[0,:,35+576:,35:35+576],dim=[1,2]) + res_t = torch.sum( attn_weights[0,:,35+576:,35+576:],dim=[1,2]) + res = res_v/res_t + print(self.layer_idx,len(res[res<0.3])) + ''' + # mask = torch.load('temp/'+str(self.layer_idx)+'.pth') + mask = self.mask.unsqueeze(1).unsqueeze(1).unsqueeze(0) + + attn_weights[:,:,:,35:35+576] = attn_weights[:,:,:,35:35+576]*mask.cuda() + else: + ''' + res_v = torch.sum( attn_weights[0,:,:,35:35+576],dim=[1,2]) + res_t = torch.sum( attn_weights[0,:,:,35+576:],dim=[1,2]) + res_s = torch.sum( attn_weights[0,:,:,:35],dim=[1,2]) + res = res_v/(res_t+res_s) + #import pdb; pdb.set_trace() + + mask = res>0.1 + mask = torch.unsqueeze(mask,dim=1) + mask =mask.repeat(1,620-35) + # torch.save(mask, 'temp/'+str(self.layer_idx)+'.pth') + ''' + # mask = torch.load('temp/'+str(self.layer_idx)+'.pth') + mask = self.mask.unsqueeze(1).unsqueeze(1) + attn_weights[0,:,:1,35:35+576] = attn_weights[0,:,:1,35:35+576]*mask.cuda() + global count_drop_head + count_drop_head+= int(len(mask[mask>0])/mask.shape[1]) + if self.layer_idx==39: + # print(count_drop_head/40) + count_drop_head=0 + #print(self.layer_idx, res) + # sorted_tensor, indices = torch.sort(res) + # print(self.layer_idx, "sorted", sorted_tensor) + # print(attn_weights[:,:,35:35+576,35:35+576].sum()) + attn_output = torch.matmul(attn_weights, value_states) + end = time.time() + #print(end-start) + + if attn_output.size() != (bsz, self.num_heads, q_len, self.head_dim): + raise ValueError( + f"`attn_output` should be of size {(bsz, self.num_heads, q_len, self.head_dim)}, but is" + f" {attn_output.size()}" + ) + + attn_output = attn_output.transpose(1, 2).contiguous() + + attn_output = attn_output.reshape(bsz, q_len, self.hidden_size) + + if self.config.pretraining_tp > 1: + attn_output = attn_output.split(self.hidden_size // self.config.pretraining_tp, dim=2) + o_proj_slices = self.o_proj.weight.split(self.hidden_size // self.config.pretraining_tp, dim=1) + attn_output = sum([F.linear(attn_output[i], o_proj_slices[i]) for i in range(self.config.pretraining_tp)]) + else: + attn_output = self.o_proj(attn_output) + + if not output_attentions: + attn_weights = None + + return attn_output, attn_weights, past_key_value + + +class LlamaFlashAttention2(LlamaAttention): + """ + Llama flash attention module. This module inherits from `LlamaAttention` as the weights of the module stays + untouched. The only required change would be on the forward pass where it needs to correctly call the public API of + flash attention and deal with padding tokens in case the input contains any of them. + """ + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + # TODO: Should be removed once Flash Attention for RoCm is bumped to 2.1. + # flash_attn<2.1 generates top-left aligned causal mask, while what is needed here is bottom-right alignement, that was made default for flash_attn>=2.1. This attribute is used to handle this difference. Reference: https://github.com/Dao-AILab/flash-attention/releases/tag/v2.1.0. + # Beware that with flash_attn<2.1, using q_seqlen != k_seqlen (except for the case q_seqlen == 1) produces a wrong mask (top-left). + self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal_2_10() + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.LongTensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Cache] = None, + output_attentions: bool = False, + use_cache: bool = False, + **kwargs, + ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]: + # LlamaFlashAttention2 attention does not support output_attentions + if "padding_mask" in kwargs: + warnings.warn( + "Passing `padding_mask` is deprecated and will be removed in v4.37. Please make sure use `attention_mask` instead.`" + ) + + # overwrite attention_mask with padding_mask + attention_mask = kwargs.pop("padding_mask") + + output_attentions = False + + bsz, q_len, _ = hidden_states.size() + + query_states = self.q_proj(hidden_states) + key_states = self.k_proj(hidden_states) + value_states = self.v_proj(hidden_states) + + # Flash attention requires the input to have the shape + # batch_size x seq_length x head_dim x hidden_dim + # therefore we just need to keep the original shape + query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2) + key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + + kv_seq_len = key_states.shape[-2] + if past_key_value is not None: + kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx) + cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len) + query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids) + + if past_key_value is not None: + cache_kwargs = {"sin": sin, "cos": cos} # Specific to RoPE models + key_states, value_states = past_key_value.update(key_states, value_states, self.layer_idx, cache_kwargs) + + # TODO: These transpose are quite inefficient but Flash Attention requires the layout [batch_size, sequence_length, num_heads, head_dim]. We would need to refactor the KV cache + # to be able to avoid many of these transpose/reshape/view. + query_states = query_states.transpose(1, 2) + key_states = key_states.transpose(1, 2) + value_states = value_states.transpose(1, 2) + + dropout_rate = self.attention_dropout if self.training else 0.0 + + # In PEFT, usually we cast the layer norms in float32 for training stability reasons + # therefore the input hidden states gets silently casted in float32. Hence, we need + # cast them back in the correct dtype just to be sure everything works as expected. + # This might slowdown training & inference so it is recommended to not cast the LayerNorms + # in fp32. (LlamaRMSNorm handles it correctly) + + input_dtype = query_states.dtype + if input_dtype == torch.float32: + # Handle the case where the model is quantized + if hasattr(self.config, "_pre_quantization_dtype"): + target_dtype = self.config._pre_quantization_dtype + else: + target_dtype = self.q_proj.weight.dtype + + logger.warning_once( + f"The input hidden states seems to be silently casted in float32, this might be related to" + f" the fact you have upcasted embedding or layer norm layers in float32. We will cast back the input in" + f" {target_dtype}." + ) + + query_states = query_states.to(target_dtype) + key_states = key_states.to(target_dtype) + value_states = value_states.to(target_dtype) + + attn_output = self._flash_attention_forward( + query_states, key_states, value_states, attention_mask, q_len, dropout=dropout_rate + ) + + attn_output = attn_output.reshape(bsz, q_len, self.hidden_size).contiguous() + attn_output = self.o_proj(attn_output) + + if not output_attentions: + attn_weights = None + + return attn_output, attn_weights, past_key_value + + def _flash_attention_forward( + self, query_states, key_states, value_states, attention_mask, query_length, dropout=0.0, softmax_scale=None + ): + """ + Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token + first unpad the input, then computes the attention scores and pad the final attention scores. + + Args: + query_states (`torch.Tensor`): + Input query states to be passed to Flash Attention API + key_states (`torch.Tensor`): + Input key states to be passed to Flash Attention API + value_states (`torch.Tensor`): + Input value states to be passed to Flash Attention API + attention_mask (`torch.Tensor`): + The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the + position of padding tokens and 1 for the position of non-padding tokens. + dropout (`int`, *optional*): + Attention dropout + softmax_scale (`float`, *optional*): + The scaling of QK^T before applying softmax. Default to 1 / sqrt(head_dim) + """ + if not self._flash_attn_uses_top_left_mask: + causal = self.is_causal + else: + # TODO: Remove the `query_length != 1` check once Flash Attention for RoCm is bumped to 2.1. For details, please see the comment in LlamaFlashAttention2 __init__. + causal = self.is_causal and query_length != 1 + + # Contains at least one padding token in the sequence + if attention_mask is not None: + batch_size = query_states.shape[0] + query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = self._upad_input( + query_states, key_states, value_states, attention_mask, query_length + ) + + cu_seqlens_q, cu_seqlens_k = cu_seq_lens + max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens + + attn_output_unpad = flash_attn_varlen_func( + query_states, + key_states, + value_states, + cu_seqlens_q=cu_seqlens_q, + cu_seqlens_k=cu_seqlens_k, + max_seqlen_q=max_seqlen_in_batch_q, + max_seqlen_k=max_seqlen_in_batch_k, + dropout_p=dropout, + softmax_scale=softmax_scale, + causal=causal, + ) + + attn_output = pad_input(attn_output_unpad, indices_q, batch_size, query_length) + else: + attn_output = flash_attn_func( + query_states, key_states, value_states, dropout, softmax_scale=softmax_scale, causal=causal + ) + + return attn_output + + def _upad_input(self, query_layer, key_layer, value_layer, attention_mask, query_length): + indices_k, cu_seqlens_k, max_seqlen_in_batch_k = _get_unpad_data(attention_mask) + batch_size, kv_seq_len, num_key_value_heads, head_dim = key_layer.shape + + key_layer = index_first_axis( + key_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k + ) + value_layer = index_first_axis( + value_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k + ) + if query_length == kv_seq_len: + query_layer = index_first_axis( + query_layer.reshape(batch_size * kv_seq_len, self.num_heads, head_dim), indices_k + ) + cu_seqlens_q = cu_seqlens_k + max_seqlen_in_batch_q = max_seqlen_in_batch_k + indices_q = indices_k + elif query_length == 1: + max_seqlen_in_batch_q = 1 + cu_seqlens_q = torch.arange( + batch_size + 1, dtype=torch.int32, device=query_layer.device + ) # There is a memcpy here, that is very bad. + indices_q = cu_seqlens_q[:-1] + query_layer = query_layer.squeeze(1) + else: + # The -q_len: slice assumes left padding. + attention_mask = attention_mask[:, -query_length:] + query_layer, indices_q, cu_seqlens_q, max_seqlen_in_batch_q = unpad_input(query_layer, attention_mask) + + return ( + query_layer, + key_layer, + value_layer, + indices_q, + (cu_seqlens_q, cu_seqlens_k), + (max_seqlen_in_batch_q, max_seqlen_in_batch_k), + ) + + +class LlamaSdpaAttention(LlamaAttention): + """ + Llama attention module using torch.nn.functional.scaled_dot_product_attention. This module inherits from + `LlamaAttention` as the weights of the module stays untouched. The only changes are on the forward pass to adapt to + SDPA API. + """ + + # Adapted from LlamaAttention.forward + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Cache] = None, + output_attentions: bool = False, + use_cache: bool = False, + ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]: + if output_attentions: + # TODO: Improve this warning with e.g. `model.config.attn_implementation = "manual"` once this is implemented. + logger.warning_once( + "LlamaModel is using LlamaSdpaAttention, but `torch.nn.functional.scaled_dot_product_attention` does not support `output_attentions=True`. Falling back to the manual attention implementation, " + 'but specifying the manual implementation will be required from Transformers version v5.0.0 onwards. This warning can be removed using the argument `attn_implementation="eager"` when loading the model.' + ) + return super().forward( + hidden_states=hidden_states, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_value=past_key_value, + output_attentions=output_attentions, + use_cache=use_cache, + ) + + bsz, q_len, _ = hidden_states.size() + + query_states = self.q_proj(hidden_states) + key_states = self.k_proj(hidden_states) + value_states = self.v_proj(hidden_states) + + query_states = query_states.view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2) + key_states = key_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + value_states = value_states.view(bsz, q_len, self.num_key_value_heads, self.head_dim).transpose(1, 2) + + kv_seq_len = key_states.shape[-2] + if past_key_value is not None: + kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx) + cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len) + + query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids) + + if past_key_value is not None: + cache_kwargs = {"sin": sin, "cos": cos} # Specific to RoPE models + key_states, value_states = past_key_value.update(key_states, value_states, self.layer_idx, cache_kwargs) + + key_states = repeat_kv(key_states, self.num_key_value_groups) + value_states = repeat_kv(value_states, self.num_key_value_groups) + + if attention_mask is not None: + if attention_mask.size() != (bsz, 1, q_len, kv_seq_len): + raise ValueError( + f"Attention mask should be of size {(bsz, 1, q_len, kv_seq_len)}, but is {attention_mask.size()}" + ) + + # SDPA with memory-efficient backend is currently (torch==2.1.2) bugged with non-contiguous inputs with custom attn_mask, + # Reference: https://github.com/pytorch/pytorch/issues/112577. + if query_states.device.type == "cuda" and attention_mask is not None: + query_states = query_states.contiguous() + key_states = key_states.contiguous() + value_states = value_states.contiguous() + + attn_output = torch.nn.functional.scaled_dot_product_attention( + query_states, + key_states, + value_states, + attn_mask=attention_mask, + dropout_p=self.attention_dropout if self.training else 0.0, + # The q_len > 1 is necessary to match with AttentionMaskConverter.to_causal_4d that does not create a causal mask in case q_len == 1. + is_causal=self.is_causal and attention_mask is None and q_len > 1, + ) + + attn_output = attn_output.transpose(1, 2).contiguous() + attn_output = attn_output.reshape(bsz, q_len, self.hidden_size) + + attn_output = self.o_proj(attn_output) + + return attn_output, None, past_key_value + + +LLAMA_ATTENTION_CLASSES = { + "eager": LlamaAttention, + "flash_attention_2": LlamaFlashAttention2, + "sdpa": LlamaSdpaAttention, +} + + +class LlamaDecoderLayer(nn.Module): + def __init__(self, config: LlamaConfig, layer_idx: int): + super().__init__() + self.hidden_size = config.hidden_size + config._attn_implementation="eager" + self.self_attn = LLAMA_ATTENTION_CLASSES[config._attn_implementation](config=config, layer_idx=layer_idx) + + self.mlp = LlamaMLP(config) + self.input_layernorm = LlamaRMSNorm(config.hidden_size, eps=config.rms_norm_eps) + self.post_attention_layernorm = LlamaRMSNorm(config.hidden_size, eps=config.rms_norm_eps) + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Tuple[torch.Tensor]] = None, + output_attentions: Optional[bool] = False, + use_cache: Optional[bool] = False, + **kwargs, + ) -> Tuple[torch.FloatTensor, Optional[Tuple[torch.FloatTensor, torch.FloatTensor]]]: + """ + Args: + hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)` + attention_mask (`torch.FloatTensor`, *optional*): + attention mask of size `(batch_size, sequence_length)` if flash attention is used or `(batch_size, 1, + query_sequence_length, key_sequence_length)` if default attention is used. + output_attentions (`bool`, *optional*): + Whether or not to return the attentions tensors of all attention layers. See `attentions` under + returned tensors for more detail. + use_cache (`bool`, *optional*): + If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding + (see `past_key_values`). + past_key_value (`Tuple(torch.FloatTensor)`, *optional*): cached past key and value projection states + """ + if "padding_mask" in kwargs: + warnings.warn( + "Passing `padding_mask` is deprecated and will be removed in v4.37. Please make sure use `attention_mask` instead.`" + ) + residual = hidden_states + + hidden_states = self.input_layernorm(hidden_states) + ''' + attention_mask = attention_mask.clone() + if attention_mask.shape[2]!=1: + attention_mask[:,:,:576,:576]= -65504.0 # -1000000000000.0 -65504.0 + + for i in range(576): + if attention_mask.shape[2]!=1: + attention_mask[:,:,i,i]=0.0 + + # import pdb; pdb.set_trace() + attention_mask=attention_mask.clone() + ''' + # Self Attention + hidden_states, self_attn_weights, present_key_value = self.self_attn( + hidden_states=hidden_states, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_value=past_key_value, + output_attentions=output_attentions, + use_cache=use_cache, + **kwargs, + ) + hidden_states = residual + hidden_states + + # Fully Connected + residual = hidden_states + hidden_states = self.post_attention_layernorm(hidden_states) + hidden_states = self.mlp(hidden_states) + hidden_states = residual + hidden_states + + outputs = (hidden_states,) + + if output_attentions: + outputs += (self_attn_weights,) + + if use_cache: + outputs += (present_key_value,) + + return outputs + + +LLAMA_START_DOCSTRING = r""" + This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the + library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads + etc.) + + This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass. + Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage + and behavior. + + Parameters: + config ([`LlamaConfig`]): + Model configuration class with all the parameters of the model. Initializing with a config file does not + load the weights associated with the model, only the configuration. Check out the + [`~PreTrainedModel.from_pretrained`] method to load the model weights. +""" + + +@add_start_docstrings( + "The bare LLaMA Model outputting raw hidden-states without any specific head on top.", + LLAMA_START_DOCSTRING, +) +class LlamaPreTrainedModel(PreTrainedModel): + config_class = LlamaConfig + base_model_prefix = "model" + supports_gradient_checkpointing = True + _no_split_modules = ["LlamaDecoderLayer"] + _skip_keys_device_placement = "past_key_values" + _supports_flash_attn_2 = True + _supports_sdpa = True + _supports_cache_class = True + + def _init_weights(self, module): + std = self.config.initializer_range + if isinstance(module, nn.Linear): + module.weight.data.normal_(mean=0.0, std=std) + if module.bias is not None: + module.bias.data.zero_() + elif isinstance(module, nn.Embedding): + module.weight.data.normal_(mean=0.0, std=std) + if module.padding_idx is not None: + module.weight.data[module.padding_idx].zero_() + + +LLAMA_INPUTS_DOCSTRING = r""" + Args: + input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`): + Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide + it. + + Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and + [`PreTrainedTokenizer.__call__`] for details. + + [What are input IDs?](../glossary#input-ids) + attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*): + Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`: + + - 1 for tokens that are **not masked**, + - 0 for tokens that are **masked**. + + [What are attention masks?](../glossary#attention-mask) + + Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and + [`PreTrainedTokenizer.__call__`] for details. + + If `past_key_values` is used, optionally only the last `input_ids` have to be input (see + `past_key_values`). + + If you want to change padding behavior, you should read [`modeling_opt._prepare_decoder_attention_mask`] + and modify to your needs. See diagram 1 in [the paper](https://arxiv.org/abs/1910.13461) for more + information on the default strategy. + + - 1 indicates the head is **not masked**, + - 0 indicates the head is **masked**. + position_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): + Indices of positions of each input sequence tokens in the position embeddings. Selected in the range `[0, + config.n_positions - 1]`. + + [What are position IDs?](../glossary#position-ids) + past_key_values (`Cache` or `tuple(tuple(torch.FloatTensor))`, *optional*): + Pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention + blocks) that can be used to speed up sequential decoding. This typically consists in the `past_key_values` + returned by the model at a previous stage of decoding, when `use_cache=True` or `config.use_cache=True`. + + Two formats are allowed: + - a [`~cache_utils.Cache`] instance; + - Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of + shape `(batch_size, num_heads, sequence_length, embed_size_per_head)`). This is also known as the legacy + cache format. + + The model will output the same cache format that is fed as input. If no `past_key_values` are passed, the + legacy cache format will be returned. + + If `past_key_values` are used, the user can optionally input only the last `input_ids` (those that don't + have their past key value states given to this model) of shape `(batch_size, 1)` instead of all `input_ids` + of shape `(batch_size, sequence_length)`. + inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*): + Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This + is useful if you want more control over how to convert `input_ids` indices into associated vectors than the + model's internal embedding lookup matrix. + use_cache (`bool`, *optional*): + If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see + `past_key_values`). + output_attentions (`bool`, *optional*): + Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned + tensors for more detail. + output_hidden_states (`bool`, *optional*): + Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for + more detail. + return_dict (`bool`, *optional*): + Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple. +""" + + +@add_start_docstrings( + "The bare LLaMA Model outputting raw hidden-states without any specific head on top.", + LLAMA_START_DOCSTRING, +) +class LlamaModel(LlamaPreTrainedModel): + """ + Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`LlamaDecoderLayer`] + + Args: + config: LlamaConfig + """ + + def __init__(self, config: LlamaConfig): + super().__init__(config) + self.padding_idx = config.pad_token_id + self.vocab_size = config.vocab_size + + self.embed_tokens = nn.Embedding(config.vocab_size, config.hidden_size, self.padding_idx) + self.layers = nn.ModuleList( + [LlamaDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)] + ) + self._use_sdpa = config._attn_implementation == "sdpa" + self._use_flash_attention_2 = config._attn_implementation == "flash_attention_2" + self.norm = LlamaRMSNorm(config.hidden_size, eps=config.rms_norm_eps) + + self.gradient_checkpointing = False + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.embed_tokens + + def set_input_embeddings(self, value): + self.embed_tokens = value + + @add_start_docstrings_to_model_forward(LLAMA_INPUTS_DOCSTRING) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, BaseModelOutputWithPast]: + output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + use_cache = use_cache if use_cache is not None else self.config.use_cache + + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + # retrieve input_ids and inputs_embeds + if input_ids is not None and inputs_embeds is not None: + raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time") + elif input_ids is not None: + batch_size, seq_length = input_ids.shape[:2] + elif inputs_embeds is not None: + batch_size, seq_length = inputs_embeds.shape[:2] + else: + raise ValueError("You have to specify either input_ids or inputs_embeds") + + if self.gradient_checkpointing and self.training: + if use_cache: + logger.warning_once( + "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..." + ) + use_cache = False + + past_key_values_length = 0 + if use_cache: + use_legacy_cache = not isinstance(past_key_values, Cache) + if use_legacy_cache: + past_key_values = DynamicCache.from_legacy_cache(past_key_values) + past_key_values_length = past_key_values.get_usable_length(seq_length) + + if position_ids is None: + device = input_ids.device if input_ids is not None else inputs_embeds.device + position_ids = torch.arange( + past_key_values_length, seq_length + past_key_values_length, dtype=torch.long, device=device + ) + position_ids = position_ids.unsqueeze(0) + + if inputs_embeds is None: + inputs_embeds = self.embed_tokens(input_ids) + + if self._use_flash_attention_2: + # 2d mask is passed through the layers + attention_mask = attention_mask if (attention_mask is not None and 0 in attention_mask) else None + elif self._use_sdpa and not output_attentions: + # output_attentions=True can not be supported when using SDPA, and we fall back on + # the manual implementation that requires a 4D causal mask in all cases. + attention_mask = _prepare_4d_causal_attention_mask_for_sdpa( + attention_mask, + (batch_size, seq_length), + inputs_embeds, + past_key_values_length, + ) + else: + # 4d mask is passed through the layers + attention_mask = _prepare_4d_causal_attention_mask( + attention_mask, (batch_size, seq_length), inputs_embeds, past_key_values_length + ) + + # embed positions + hidden_states = inputs_embeds + + # decoder layers + all_hidden_states = () if output_hidden_states else None + all_self_attns = () if output_attentions else None + next_decoder_cache = None + import time + start = time.time() + for i, decoder_layer in enumerate(self.layers): + if output_hidden_states: + all_hidden_states += (hidden_states,) + #import pdb; pdb.set_trace() + if self.gradient_checkpointing and self.training: + layer_outputs = self._gradient_checkpointing_func( + decoder_layer.__call__, + hidden_states, + attention_mask, + position_ids, + past_key_values, + output_attentions, + use_cache, + ) + else: + layer_outputs = decoder_layer( + hidden_states, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_value=past_key_values, + output_attentions=output_attentions, + use_cache=use_cache, + ) + + hidden_states = layer_outputs[0] + + if use_cache: + next_decoder_cache = layer_outputs[2 if output_attentions else 1] + + if output_attentions: + all_self_attns += (layer_outputs[1],) + end = time.time() + # print(end-start, len(self.layers)) + hidden_states = self.norm(hidden_states) + + # add hidden states from the last decoder layer + if output_hidden_states: + all_hidden_states += (hidden_states,) + + next_cache = None + if use_cache: + next_cache = next_decoder_cache.to_legacy_cache() if use_legacy_cache else next_decoder_cache + if not return_dict: + return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns] if v is not None) + return BaseModelOutputWithPast( + last_hidden_state=hidden_states, + past_key_values=next_cache, + hidden_states=all_hidden_states, + attentions=all_self_attns, + ) + + +class LlamaForCausalLM(LlamaPreTrainedModel): + _tied_weights_keys = ["lm_head.weight"] + + def __init__(self, config): + super().__init__(config) + self.model = LlamaModel(config) + self.vocab_size = config.vocab_size + self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False) + + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.model.embed_tokens + + def set_input_embeddings(self, value): + self.model.embed_tokens = value + + def get_output_embeddings(self): + return self.lm_head + + def set_output_embeddings(self, new_embeddings): + self.lm_head = new_embeddings + + def set_decoder(self, decoder): + self.model = decoder + + def get_decoder(self): + return self.model + + @add_start_docstrings_to_model_forward(LLAMA_INPUTS_DOCSTRING) + @replace_return_docstrings(output_type=CausalLMOutputWithPast, config_class=_CONFIG_FOR_DOC) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, CausalLMOutputWithPast]: + r""" + Args: + labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): + Labels for computing the masked language modeling loss. Indices should either be in `[0, ..., + config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored + (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`. + + Returns: + + Example: + + ```python + >>> from transformers import AutoTokenizer, LlamaForCausalLM + + >>> model = LlamaForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS) + >>> tokenizer = AutoTokenizer.from_pretrained(PATH_TO_CONVERTED_TOKENIZER) + + >>> prompt = "Hey, are you conscious? Can you talk to me?" + >>> inputs = tokenizer(prompt, return_tensors="pt") + + >>> # Generate + >>> generate_ids = model.generate(inputs.input_ids, max_length=30) + >>> tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] + "Hey, are you conscious? Can you talk to me?\nI'm not conscious, but I can talk to you." + ```""" + output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn) + outputs = self.model( + input_ids=input_ids, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + inputs_embeds=inputs_embeds, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + + hidden_states = outputs[0] + if self.config.pretraining_tp > 1: + lm_head_slices = self.lm_head.weight.split(self.vocab_size // self.config.pretraining_tp, dim=0) + logits = [F.linear(hidden_states, lm_head_slices[i]) for i in range(self.config.pretraining_tp)] + logits = torch.cat(logits, dim=-1) + else: + logits = self.lm_head(hidden_states) + logits = logits.float() + + loss = None + if labels is not None: + # Shift so that tokens < n predict n + shift_logits = logits[..., :-1, :].contiguous() + shift_labels = labels[..., 1:].contiguous() + # Flatten the tokens + loss_fct = CrossEntropyLoss() + shift_logits = shift_logits.view(-1, self.config.vocab_size) + shift_labels = shift_labels.view(-1) + # Enable model parallelism + shift_labels = shift_labels.to(shift_logits.device) + loss = loss_fct(shift_logits, shift_labels) + + if not return_dict: + output = (logits,) + outputs[1:] + return (loss,) + output if loss is not None else output + + return CausalLMOutputWithPast( + loss=loss, + logits=logits, + past_key_values=outputs.past_key_values, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + + def prepare_inputs_for_generation( + self, input_ids, past_key_values=None, attention_mask=None, inputs_embeds=None, **kwargs + ): + if past_key_values is not None: + if isinstance(past_key_values, Cache): + cache_length = past_key_values.get_seq_length() + past_length = past_key_values.seen_tokens + max_cache_length = past_key_values.get_max_length() + else: + cache_length = past_length = past_key_values[0][0].shape[2] + max_cache_length = None + + # Keep only the unprocessed tokens: + # 1 - If the length of the attention_mask exceeds the length of input_ids, then we are in a setting where + # some of the inputs are exclusivelly passed as part of the cache (e.g. when passing input_embeds as + # input) + if attention_mask is not None and attention_mask.shape[1] > input_ids.shape[1]: + input_ids = input_ids[:, -(attention_mask.shape[1] - past_length) :] + # 2 - If the past_length is smaller than input_ids', then input_ids holds all input tokens. We can discard + # input_ids based on the past_length. + elif past_length < input_ids.shape[1]: + input_ids = input_ids[:, past_length:] + # 3 - Otherwise (past_length >= input_ids.shape[1]), let's assume input_ids only has unprocessed tokens. + + # If we are about to go beyond the maximum cache length, we need to crop the input attention mask. + if ( + max_cache_length is not None + and attention_mask is not None + and cache_length + input_ids.shape[1] > max_cache_length + ): + attention_mask = attention_mask[:, -max_cache_length:] + + position_ids = kwargs.get("position_ids", None) + if attention_mask is not None and position_ids is None: + # create position_ids on the fly for batch generation + position_ids = attention_mask.long().cumsum(-1) - 1 + position_ids.masked_fill_(attention_mask == 0, 1) + if past_key_values: + position_ids = position_ids[:, -input_ids.shape[1] :] + + # if `inputs_embeds` are passed, we only want to use them in the 1st generation step + if inputs_embeds is not None and past_key_values is None: + model_inputs = {"inputs_embeds": inputs_embeds} + else: + model_inputs = {"input_ids": input_ids} + + model_inputs.update( + { + "position_ids": position_ids, + "past_key_values": past_key_values, + "use_cache": kwargs.get("use_cache"), + "attention_mask": attention_mask, + } + ) + return model_inputs + + @staticmethod + def _reorder_cache(past_key_values, beam_idx): + reordered_past = () + for layer_past in past_key_values: + reordered_past += ( + tuple(past_state.index_select(0, beam_idx.to(past_state.device)) for past_state in layer_past), + ) + return reordered_past + + +@add_start_docstrings( + """ + The LLaMa Model transformer with a sequence classification head on top (linear layer). + + [`LlamaForSequenceClassification`] uses the last token in order to do the classification, as other causal models + (e.g. GPT-2) do. + + Since it does classification on the last token, it requires to know the position of the last token. If a + `pad_token_id` is defined in the configuration, it finds the last token that is not a padding token in each row. If + no `pad_token_id` is defined, it simply takes the last value in each row of the batch. Since it cannot guess the + padding tokens when `inputs_embeds` are passed instead of `input_ids`, it does the same (take the last value in + each row of the batch). + """, + LLAMA_START_DOCSTRING, +) +class LlamaForSequenceClassification(LlamaPreTrainedModel): + def __init__(self, config): + super().__init__(config) + self.num_labels = config.num_labels + self.model = LlamaModel(config) + self.score = nn.Linear(config.hidden_size, self.num_labels, bias=False) + + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.model.embed_tokens + + def set_input_embeddings(self, value): + self.model.embed_tokens = value + + @add_start_docstrings_to_model_forward(LLAMA_INPUTS_DOCSTRING) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, SequenceClassifierOutputWithPast]: + r""" + labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): + Labels for computing the sequence classification/regression loss. Indices should be in `[0, ..., + config.num_labels - 1]`. If `config.num_labels == 1` a regression loss is computed (Mean-Square loss), If + `config.num_labels > 1` a classification loss is computed (Cross-Entropy). + """ + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + transformer_outputs = self.model( + input_ids, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + inputs_embeds=inputs_embeds, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + hidden_states = transformer_outputs[0] + logits = self.score(hidden_states) + + if input_ids is not None: + batch_size = input_ids.shape[0] + else: + batch_size = inputs_embeds.shape[0] + + if self.config.pad_token_id is None and batch_size != 1: + raise ValueError("Cannot handle batch sizes > 1 if no padding token is defined.") + if self.config.pad_token_id is None: + sequence_lengths = -1 + else: + if input_ids is not None: + sequence_lengths = (torch.eq(input_ids, self.config.pad_token_id).int().argmax(-1) - 1).to( + logits.device + ) + else: + sequence_lengths = -1 + + pooled_logits = logits[torch.arange(batch_size, device=logits.device), sequence_lengths] + + loss = None + if labels is not None: + labels = labels.to(logits.device) + if self.config.problem_type is None: + if self.num_labels == 1: + self.config.problem_type = "regression" + elif self.num_labels > 1 and (labels.dtype == torch.long or labels.dtype == torch.int): + self.config.problem_type = "single_label_classification" + else: + self.config.problem_type = "multi_label_classification" + + if self.config.problem_type == "regression": + loss_fct = MSELoss() + if self.num_labels == 1: + loss = loss_fct(pooled_logits.squeeze(), labels.squeeze()) + else: + loss = loss_fct(pooled_logits, labels) + elif self.config.problem_type == "single_label_classification": + loss_fct = CrossEntropyLoss() + loss = loss_fct(pooled_logits.view(-1, self.num_labels), labels.view(-1)) + elif self.config.problem_type == "multi_label_classification": + loss_fct = BCEWithLogitsLoss() + loss = loss_fct(pooled_logits, labels) + if not return_dict: + output = (pooled_logits,) + transformer_outputs[1:] + return ((loss,) + output) if loss is not None else output + + return SequenceClassifierOutputWithPast( + loss=loss, + logits=pooled_logits, + past_key_values=transformer_outputs.past_key_values, + hidden_states=transformer_outputs.hidden_states, + attentions=transformer_outputs.attentions, + ) diff --git a/special_tokens_map.json b/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..14761dcf1466dc232bd41de9c21d4c617b15755e --- /dev/null +++ b/special_tokens_map.json @@ -0,0 +1,24 @@ +{ + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": "", + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/tokenizer.model b/tokenizer.model new file mode 100644 index 0000000000000000000000000000000000000000..6c00c742ce03c627d6cd5b795984876fa49fa899 --- /dev/null +++ b/tokenizer.model @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347 +size 499723 diff --git a/tokenizer_config.json b/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..1ede259689f08e4dad55a405cb964626437a7591 --- /dev/null +++ b/tokenizer_config.json @@ -0,0 +1,42 @@ +{ + "add_bos_token": true, + "add_eos_token": false, + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "legacy": false, + "model_max_length": 1560, + "pad_token": "", + "padding_side": "right", + "sp_model_kwargs": {}, + "spaces_between_special_tokens": false, + "tokenizer_class": "LlamaTokenizer", + "unk_token": "", + "use_default_system_prompt": false +} diff --git a/trainer_state.json b/trainer_state.json new file mode 100644 index 0000000000000000000000000000000000000000..47e7db60750135734b745ff592970f7eaa785eea --- /dev/null +++ b/trainer_state.json @@ -0,0 +1,31200 @@ +{ + "best_metric": null, + "best_model_checkpoint": null, + "epoch": 1.0, + "eval_steps": 500, + "global_step": 5195, + "is_hyper_param_search": false, + "is_local_process_zero": true, + "is_world_process_zero": true, + "log_history": [ + { + "epoch": 0.0, + "learning_rate": 1.282051282051282e-07, + "loss": 1.4715, + "step": 1 + }, + { + "epoch": 0.0, + "learning_rate": 2.564102564102564e-07, + "loss": 1.491, + "step": 2 + }, + { + "epoch": 0.0, + "learning_rate": 3.846153846153847e-07, + "loss": 1.3857, + "step": 3 + }, + { + "epoch": 0.0, + "learning_rate": 5.128205128205128e-07, + "loss": 1.4981, + "step": 4 + }, + { + "epoch": 0.0, + "learning_rate": 6.41025641025641e-07, + "loss": 1.451, + "step": 5 + }, + { + "epoch": 0.0, + "learning_rate": 7.692307692307694e-07, + "loss": 1.4382, + "step": 6 + }, + { + "epoch": 0.0, + "learning_rate": 8.974358974358975e-07, + "loss": 1.4591, + "step": 7 + }, + { + "epoch": 0.0, + "learning_rate": 1.0256410256410257e-06, + "loss": 1.4096, + "step": 8 + }, + { + "epoch": 0.0, + "learning_rate": 1.153846153846154e-06, + "loss": 1.401, + "step": 9 + }, + { + "epoch": 0.0, + "learning_rate": 1.282051282051282e-06, + "loss": 1.3837, + "step": 10 + }, + { + "epoch": 0.0, + "learning_rate": 1.4102564102564104e-06, + "loss": 1.359, + "step": 11 + }, + { + "epoch": 0.0, + "learning_rate": 1.5384615384615387e-06, + "loss": 1.3611, + "step": 12 + }, + { + "epoch": 0.0, + "learning_rate": 1.6666666666666667e-06, + "loss": 1.3102, + "step": 13 + }, + { + "epoch": 0.0, + "learning_rate": 1.794871794871795e-06, + "loss": 1.2844, + "step": 14 + }, + { + "epoch": 0.0, + "learning_rate": 1.9230769230769234e-06, + "loss": 1.2287, + "step": 15 + }, + { + "epoch": 0.0, + "learning_rate": 2.0512820512820513e-06, + "loss": 1.2925, + "step": 16 + }, + { + "epoch": 0.0, + "learning_rate": 2.1794871794871797e-06, + "loss": 1.2597, + "step": 17 + }, + { + "epoch": 0.0, + "learning_rate": 2.307692307692308e-06, + "loss": 1.1856, + "step": 18 + }, + { + "epoch": 0.0, + "learning_rate": 2.435897435897436e-06, + "loss": 1.1592, + "step": 19 + }, + { + "epoch": 0.0, + "learning_rate": 2.564102564102564e-06, + "loss": 1.1085, + "step": 20 + }, + { + "epoch": 0.0, + "learning_rate": 2.6923076923076923e-06, + "loss": 1.1725, + "step": 21 + }, + { + "epoch": 0.0, + "learning_rate": 2.8205128205128207e-06, + "loss": 1.2145, + "step": 22 + }, + { + "epoch": 0.0, + "learning_rate": 2.948717948717949e-06, + "loss": 1.2148, + "step": 23 + }, + { + "epoch": 0.0, + "learning_rate": 3.0769230769230774e-06, + "loss": 1.1553, + "step": 24 + }, + { + "epoch": 0.0, + "learning_rate": 3.205128205128206e-06, + "loss": 1.1441, + "step": 25 + }, + { + "epoch": 0.01, + "learning_rate": 3.3333333333333333e-06, + "loss": 1.2483, + "step": 26 + }, + { + "epoch": 0.01, + "learning_rate": 3.4615384615384617e-06, + "loss": 1.1238, + "step": 27 + }, + { + "epoch": 0.01, + "learning_rate": 3.58974358974359e-06, + "loss": 1.1185, + "step": 28 + }, + { + "epoch": 0.01, + "learning_rate": 3.7179487179487184e-06, + "loss": 1.0634, + "step": 29 + }, + { + "epoch": 0.01, + "learning_rate": 3.846153846153847e-06, + "loss": 1.084, + "step": 30 + }, + { + "epoch": 0.01, + "learning_rate": 3.974358974358974e-06, + "loss": 1.0823, + "step": 31 + }, + { + "epoch": 0.01, + "learning_rate": 4.102564102564103e-06, + "loss": 1.0636, + "step": 32 + }, + { + "epoch": 0.01, + "learning_rate": 4.230769230769231e-06, + "loss": 1.0135, + "step": 33 + }, + { + "epoch": 0.01, + "learning_rate": 4.358974358974359e-06, + "loss": 1.0225, + "step": 34 + }, + { + "epoch": 0.01, + "learning_rate": 4.487179487179488e-06, + "loss": 1.0208, + "step": 35 + }, + { + "epoch": 0.01, + "learning_rate": 4.615384615384616e-06, + "loss": 4.3336, + "step": 36 + }, + { + "epoch": 0.01, + "learning_rate": 4.743589743589744e-06, + "loss": 1.08, + "step": 37 + }, + { + "epoch": 0.01, + "learning_rate": 4.871794871794872e-06, + "loss": 1.0742, + "step": 38 + }, + { + "epoch": 0.01, + "learning_rate": 5e-06, + "loss": 1.0457, + "step": 39 + }, + { + "epoch": 0.01, + "learning_rate": 5.128205128205128e-06, + "loss": 1.0427, + "step": 40 + }, + { + "epoch": 0.01, + "learning_rate": 5.256410256410257e-06, + "loss": 1.0599, + "step": 41 + }, + { + "epoch": 0.01, + "learning_rate": 5.384615384615385e-06, + "loss": 1.0781, + "step": 42 + }, + { + "epoch": 0.01, + "learning_rate": 5.512820512820514e-06, + "loss": 1.0193, + "step": 43 + }, + { + "epoch": 0.01, + "learning_rate": 5.641025641025641e-06, + "loss": 0.9767, + "step": 44 + }, + { + "epoch": 0.01, + "learning_rate": 5.769230769230769e-06, + "loss": 1.0332, + "step": 45 + }, + { + "epoch": 0.01, + "learning_rate": 5.897435897435898e-06, + "loss": 0.9968, + "step": 46 + }, + { + "epoch": 0.01, + "learning_rate": 6.025641025641026e-06, + "loss": 0.9327, + "step": 47 + }, + { + "epoch": 0.01, + "learning_rate": 6.153846153846155e-06, + "loss": 1.0183, + "step": 48 + }, + { + "epoch": 0.01, + "learning_rate": 6.282051282051282e-06, + "loss": 1.0013, + "step": 49 + }, + { + "epoch": 0.01, + "learning_rate": 6.410256410256412e-06, + "loss": 3.5057, + "step": 50 + }, + { + "epoch": 0.01, + "learning_rate": 6.538461538461539e-06, + "loss": 0.9982, + "step": 51 + }, + { + "epoch": 0.01, + "learning_rate": 6.666666666666667e-06, + "loss": 0.9786, + "step": 52 + }, + { + "epoch": 0.01, + "learning_rate": 6.794871794871796e-06, + "loss": 1.0033, + "step": 53 + }, + { + "epoch": 0.01, + "learning_rate": 6.923076923076923e-06, + "loss": 0.9968, + "step": 54 + }, + { + "epoch": 0.01, + "learning_rate": 7.051282051282053e-06, + "loss": 1.0369, + "step": 55 + }, + { + "epoch": 0.01, + "learning_rate": 7.17948717948718e-06, + "loss": 0.894, + "step": 56 + }, + { + "epoch": 0.01, + "learning_rate": 7.307692307692308e-06, + "loss": 0.9616, + "step": 57 + }, + { + "epoch": 0.01, + "learning_rate": 7.435897435897437e-06, + "loss": 0.9738, + "step": 58 + }, + { + "epoch": 0.01, + "learning_rate": 7.564102564102564e-06, + "loss": 0.9695, + "step": 59 + }, + { + "epoch": 0.01, + "learning_rate": 7.692307692307694e-06, + "loss": 0.9637, + "step": 60 + }, + { + "epoch": 0.01, + "learning_rate": 7.820512820512822e-06, + "loss": 0.9757, + "step": 61 + }, + { + "epoch": 0.01, + "learning_rate": 7.948717948717949e-06, + "loss": 0.9546, + "step": 62 + }, + { + "epoch": 0.01, + "learning_rate": 8.076923076923077e-06, + "loss": 0.9701, + "step": 63 + }, + { + "epoch": 0.01, + "learning_rate": 8.205128205128205e-06, + "loss": 0.9771, + "step": 64 + }, + { + "epoch": 0.01, + "learning_rate": 8.333333333333334e-06, + "loss": 1.007, + "step": 65 + }, + { + "epoch": 0.01, + "learning_rate": 8.461538461538462e-06, + "loss": 1.0072, + "step": 66 + }, + { + "epoch": 0.01, + "learning_rate": 8.58974358974359e-06, + "loss": 0.9828, + "step": 67 + }, + { + "epoch": 0.01, + "learning_rate": 8.717948717948719e-06, + "loss": 1.0001, + "step": 68 + }, + { + "epoch": 0.01, + "learning_rate": 8.846153846153847e-06, + "loss": 0.9775, + "step": 69 + }, + { + "epoch": 0.01, + "learning_rate": 8.974358974358976e-06, + "loss": 1.0071, + "step": 70 + }, + { + "epoch": 0.01, + "learning_rate": 9.102564102564104e-06, + "loss": 0.9132, + "step": 71 + }, + { + "epoch": 0.01, + "learning_rate": 9.230769230769232e-06, + "loss": 0.9507, + "step": 72 + }, + { + "epoch": 0.01, + "learning_rate": 9.358974358974359e-06, + "loss": 0.9136, + "step": 73 + }, + { + "epoch": 0.01, + "learning_rate": 9.487179487179487e-06, + "loss": 0.9109, + "step": 74 + }, + { + "epoch": 0.01, + "learning_rate": 9.615384615384616e-06, + "loss": 0.9334, + "step": 75 + }, + { + "epoch": 0.01, + "learning_rate": 9.743589743589744e-06, + "loss": 0.9329, + "step": 76 + }, + { + "epoch": 0.01, + "learning_rate": 9.871794871794872e-06, + "loss": 1.0024, + "step": 77 + }, + { + "epoch": 0.02, + "learning_rate": 1e-05, + "loss": 0.9483, + "step": 78 + }, + { + "epoch": 0.02, + "learning_rate": 1.012820512820513e-05, + "loss": 0.969, + "step": 79 + }, + { + "epoch": 0.02, + "learning_rate": 1.0256410256410256e-05, + "loss": 0.9532, + "step": 80 + }, + { + "epoch": 0.02, + "learning_rate": 1.0384615384615386e-05, + "loss": 0.9433, + "step": 81 + }, + { + "epoch": 0.02, + "learning_rate": 1.0512820512820514e-05, + "loss": 0.9562, + "step": 82 + }, + { + "epoch": 0.02, + "learning_rate": 1.0641025641025643e-05, + "loss": 0.8785, + "step": 83 + }, + { + "epoch": 0.02, + "learning_rate": 1.076923076923077e-05, + "loss": 3.2122, + "step": 84 + }, + { + "epoch": 0.02, + "learning_rate": 1.0897435897435898e-05, + "loss": 0.9635, + "step": 85 + }, + { + "epoch": 0.02, + "learning_rate": 1.1025641025641028e-05, + "loss": 0.8607, + "step": 86 + }, + { + "epoch": 0.02, + "learning_rate": 1.1153846153846154e-05, + "loss": 0.9525, + "step": 87 + }, + { + "epoch": 0.02, + "learning_rate": 1.1282051282051283e-05, + "loss": 0.9491, + "step": 88 + }, + { + "epoch": 0.02, + "learning_rate": 1.1410256410256411e-05, + "loss": 0.9165, + "step": 89 + }, + { + "epoch": 0.02, + "learning_rate": 1.1538461538461538e-05, + "loss": 0.9879, + "step": 90 + }, + { + "epoch": 0.02, + "learning_rate": 1.1666666666666668e-05, + "loss": 0.974, + "step": 91 + }, + { + "epoch": 0.02, + "learning_rate": 1.1794871794871796e-05, + "loss": 0.9685, + "step": 92 + }, + { + "epoch": 0.02, + "learning_rate": 1.1923076923076925e-05, + "loss": 0.9597, + "step": 93 + }, + { + "epoch": 0.02, + "learning_rate": 1.2051282051282051e-05, + "loss": 0.9608, + "step": 94 + }, + { + "epoch": 0.02, + "learning_rate": 1.217948717948718e-05, + "loss": 0.9395, + "step": 95 + }, + { + "epoch": 0.02, + "learning_rate": 1.230769230769231e-05, + "loss": 0.8969, + "step": 96 + }, + { + "epoch": 0.02, + "learning_rate": 1.2435897435897436e-05, + "loss": 0.8574, + "step": 97 + }, + { + "epoch": 0.02, + "learning_rate": 1.2564102564102565e-05, + "loss": 3.2338, + "step": 98 + }, + { + "epoch": 0.02, + "learning_rate": 1.2692307692307693e-05, + "loss": 0.9971, + "step": 99 + }, + { + "epoch": 0.02, + "learning_rate": 1.2820512820512823e-05, + "loss": 0.9778, + "step": 100 + }, + { + "epoch": 0.02, + "learning_rate": 1.294871794871795e-05, + "loss": 0.8861, + "step": 101 + }, + { + "epoch": 0.02, + "learning_rate": 1.3076923076923078e-05, + "loss": 1.0107, + "step": 102 + }, + { + "epoch": 0.02, + "learning_rate": 1.3205128205128207e-05, + "loss": 3.1329, + "step": 103 + }, + { + "epoch": 0.02, + "learning_rate": 1.3333333333333333e-05, + "loss": 0.9429, + "step": 104 + }, + { + "epoch": 0.02, + "learning_rate": 1.3461538461538463e-05, + "loss": 0.9252, + "step": 105 + }, + { + "epoch": 0.02, + "learning_rate": 1.3589743589743592e-05, + "loss": 0.9298, + "step": 106 + }, + { + "epoch": 0.02, + "learning_rate": 1.3717948717948718e-05, + "loss": 0.9961, + "step": 107 + }, + { + "epoch": 0.02, + "learning_rate": 1.3846153846153847e-05, + "loss": 2.8413, + "step": 108 + }, + { + "epoch": 0.02, + "learning_rate": 1.3974358974358975e-05, + "loss": 0.9349, + "step": 109 + }, + { + "epoch": 0.02, + "learning_rate": 1.4102564102564105e-05, + "loss": 0.9491, + "step": 110 + }, + { + "epoch": 0.02, + "learning_rate": 1.4230769230769232e-05, + "loss": 0.9278, + "step": 111 + }, + { + "epoch": 0.02, + "learning_rate": 1.435897435897436e-05, + "loss": 0.9079, + "step": 112 + }, + { + "epoch": 0.02, + "learning_rate": 1.4487179487179489e-05, + "loss": 0.914, + "step": 113 + }, + { + "epoch": 0.02, + "learning_rate": 1.4615384615384615e-05, + "loss": 0.8572, + "step": 114 + }, + { + "epoch": 0.02, + "learning_rate": 1.4743589743589745e-05, + "loss": 0.8608, + "step": 115 + }, + { + "epoch": 0.02, + "learning_rate": 1.4871794871794874e-05, + "loss": 2.8901, + "step": 116 + }, + { + "epoch": 0.02, + "learning_rate": 1.5000000000000002e-05, + "loss": 0.9161, + "step": 117 + }, + { + "epoch": 0.02, + "learning_rate": 1.5128205128205129e-05, + "loss": 0.9586, + "step": 118 + }, + { + "epoch": 0.02, + "learning_rate": 1.5256410256410257e-05, + "loss": 0.8921, + "step": 119 + }, + { + "epoch": 0.02, + "learning_rate": 1.5384615384615387e-05, + "loss": 0.9607, + "step": 120 + }, + { + "epoch": 0.02, + "learning_rate": 1.5512820512820516e-05, + "loss": 0.866, + "step": 121 + }, + { + "epoch": 0.02, + "learning_rate": 1.5641025641025644e-05, + "loss": 0.967, + "step": 122 + }, + { + "epoch": 0.02, + "learning_rate": 1.576923076923077e-05, + "loss": 0.9094, + "step": 123 + }, + { + "epoch": 0.02, + "learning_rate": 1.5897435897435897e-05, + "loss": 0.8653, + "step": 124 + }, + { + "epoch": 0.02, + "learning_rate": 1.602564102564103e-05, + "loss": 0.9287, + "step": 125 + }, + { + "epoch": 0.02, + "learning_rate": 1.6153846153846154e-05, + "loss": 0.8918, + "step": 126 + }, + { + "epoch": 0.02, + "learning_rate": 1.6282051282051282e-05, + "loss": 0.83, + "step": 127 + }, + { + "epoch": 0.02, + "learning_rate": 1.641025641025641e-05, + "loss": 0.9351, + "step": 128 + }, + { + "epoch": 0.02, + "learning_rate": 1.653846153846154e-05, + "loss": 0.9001, + "step": 129 + }, + { + "epoch": 0.03, + "learning_rate": 1.6666666666666667e-05, + "loss": 0.9137, + "step": 130 + }, + { + "epoch": 0.03, + "learning_rate": 1.6794871794871796e-05, + "loss": 0.8886, + "step": 131 + }, + { + "epoch": 0.03, + "learning_rate": 1.6923076923076924e-05, + "loss": 0.9526, + "step": 132 + }, + { + "epoch": 0.03, + "learning_rate": 1.7051282051282053e-05, + "loss": 0.9424, + "step": 133 + }, + { + "epoch": 0.03, + "learning_rate": 1.717948717948718e-05, + "loss": 0.9128, + "step": 134 + }, + { + "epoch": 0.03, + "learning_rate": 1.730769230769231e-05, + "loss": 0.8978, + "step": 135 + }, + { + "epoch": 0.03, + "learning_rate": 1.7435897435897438e-05, + "loss": 0.9465, + "step": 136 + }, + { + "epoch": 0.03, + "learning_rate": 1.7564102564102566e-05, + "loss": 0.9033, + "step": 137 + }, + { + "epoch": 0.03, + "learning_rate": 1.7692307692307694e-05, + "loss": 0.9853, + "step": 138 + }, + { + "epoch": 0.03, + "learning_rate": 1.7820512820512823e-05, + "loss": 0.9438, + "step": 139 + }, + { + "epoch": 0.03, + "learning_rate": 1.794871794871795e-05, + "loss": 0.9394, + "step": 140 + }, + { + "epoch": 0.03, + "learning_rate": 1.807692307692308e-05, + "loss": 0.9071, + "step": 141 + }, + { + "epoch": 0.03, + "learning_rate": 1.8205128205128208e-05, + "loss": 0.9308, + "step": 142 + }, + { + "epoch": 0.03, + "learning_rate": 1.8333333333333333e-05, + "loss": 0.935, + "step": 143 + }, + { + "epoch": 0.03, + "learning_rate": 1.8461538461538465e-05, + "loss": 0.8907, + "step": 144 + }, + { + "epoch": 0.03, + "learning_rate": 1.8589743589743593e-05, + "loss": 0.9061, + "step": 145 + }, + { + "epoch": 0.03, + "learning_rate": 1.8717948717948718e-05, + "loss": 0.9679, + "step": 146 + }, + { + "epoch": 0.03, + "learning_rate": 1.8846153846153846e-05, + "loss": 0.931, + "step": 147 + }, + { + "epoch": 0.03, + "learning_rate": 1.8974358974358975e-05, + "loss": 0.8938, + "step": 148 + }, + { + "epoch": 0.03, + "learning_rate": 1.9102564102564106e-05, + "loss": 0.9108, + "step": 149 + }, + { + "epoch": 0.03, + "learning_rate": 1.923076923076923e-05, + "loss": 2.6512, + "step": 150 + }, + { + "epoch": 0.03, + "learning_rate": 1.935897435897436e-05, + "loss": 0.9489, + "step": 151 + }, + { + "epoch": 0.03, + "learning_rate": 1.9487179487179488e-05, + "loss": 0.9132, + "step": 152 + }, + { + "epoch": 0.03, + "learning_rate": 1.9615384615384617e-05, + "loss": 0.8711, + "step": 153 + }, + { + "epoch": 0.03, + "learning_rate": 1.9743589743589745e-05, + "loss": 2.5829, + "step": 154 + }, + { + "epoch": 0.03, + "learning_rate": 1.9871794871794873e-05, + "loss": 0.9284, + "step": 155 + }, + { + "epoch": 0.03, + "learning_rate": 2e-05, + "loss": 0.9421, + "step": 156 + }, + { + "epoch": 0.03, + "learning_rate": 1.999999805651578e-05, + "loss": 0.8888, + "step": 157 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999992226063874e-05, + "loss": 0.8539, + "step": 158 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999982508646547e-05, + "loss": 0.8966, + "step": 159 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999968904267578e-05, + "loss": 0.9534, + "step": 160 + }, + { + "epoch": 0.03, + "learning_rate": 1.999995141293225e-05, + "loss": 0.9165, + "step": 161 + }, + { + "epoch": 0.03, + "learning_rate": 1.999993003464737e-05, + "loss": 2.667, + "step": 162 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999904769421242e-05, + "loss": 0.9234, + "step": 163 + }, + { + "epoch": 0.03, + "learning_rate": 1.999987561726369e-05, + "loss": 0.917, + "step": 164 + }, + { + "epoch": 0.03, + "learning_rate": 1.999984257818604e-05, + "loss": 0.9647, + "step": 165 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999805652201144e-05, + "loss": 2.4527, + "step": 166 + }, + { + "epoch": 0.03, + "learning_rate": 1.999976483932334e-05, + "loss": 0.9487, + "step": 167 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999720139568508e-05, + "loss": 0.925, + "step": 168 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999671552954013e-05, + "loss": 0.9104, + "step": 169 + }, + { + "epoch": 0.03, + "learning_rate": 1.999961907949874e-05, + "loss": 0.9418, + "step": 170 + }, + { + "epoch": 0.03, + "learning_rate": 1.999956271922309e-05, + "loss": 0.9397, + "step": 171 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999502472148968e-05, + "loss": 0.833, + "step": 172 + }, + { + "epoch": 0.03, + "learning_rate": 1.999943833829979e-05, + "loss": 0.9171, + "step": 173 + }, + { + "epoch": 0.03, + "learning_rate": 1.999937031770049e-05, + "loss": 0.9068, + "step": 174 + }, + { + "epoch": 0.03, + "learning_rate": 1.99992984103775e-05, + "loss": 0.9174, + "step": 175 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999222616358778e-05, + "loss": 0.9062, + "step": 176 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999142935673778e-05, + "loss": 0.9674, + "step": 177 + }, + { + "epoch": 0.03, + "learning_rate": 1.9999059368353474e-05, + "loss": 0.9047, + "step": 178 + }, + { + "epoch": 0.03, + "learning_rate": 1.999897191443035e-05, + "loss": 0.9285, + "step": 179 + }, + { + "epoch": 0.03, + "learning_rate": 1.9998880573938396e-05, + "loss": 0.949, + "step": 180 + }, + { + "epoch": 0.03, + "learning_rate": 1.9998785346913123e-05, + "loss": 0.928, + "step": 181 + }, + { + "epoch": 0.04, + "learning_rate": 1.9998686233391537e-05, + "loss": 0.9573, + "step": 182 + }, + { + "epoch": 0.04, + "learning_rate": 1.9998583233412162e-05, + "loss": 0.9193, + "step": 183 + }, + { + "epoch": 0.04, + "learning_rate": 1.9998476347015042e-05, + "loss": 0.9167, + "step": 184 + }, + { + "epoch": 0.04, + "learning_rate": 1.999836557424172e-05, + "loss": 0.9052, + "step": 185 + }, + { + "epoch": 0.04, + "learning_rate": 1.9998250915135255e-05, + "loss": 0.9266, + "step": 186 + }, + { + "epoch": 0.04, + "learning_rate": 1.9998132369740207e-05, + "loss": 0.9519, + "step": 187 + }, + { + "epoch": 0.04, + "learning_rate": 1.999800993810266e-05, + "loss": 0.9358, + "step": 188 + }, + { + "epoch": 0.04, + "learning_rate": 1.9997883620270203e-05, + "loss": 0.9314, + "step": 189 + }, + { + "epoch": 0.04, + "learning_rate": 1.9997753416291935e-05, + "loss": 0.9292, + "step": 190 + }, + { + "epoch": 0.04, + "learning_rate": 1.9997619326218465e-05, + "loss": 0.8789, + "step": 191 + }, + { + "epoch": 0.04, + "learning_rate": 1.999748135010191e-05, + "loss": 0.8901, + "step": 192 + }, + { + "epoch": 0.04, + "learning_rate": 1.999733948799591e-05, + "loss": 0.9568, + "step": 193 + }, + { + "epoch": 0.04, + "learning_rate": 1.99971937399556e-05, + "loss": 0.9219, + "step": 194 + }, + { + "epoch": 0.04, + "learning_rate": 1.999704410603763e-05, + "loss": 0.9421, + "step": 195 + }, + { + "epoch": 0.04, + "learning_rate": 1.9996890586300168e-05, + "loss": 0.852, + "step": 196 + }, + { + "epoch": 0.04, + "learning_rate": 1.999673318080288e-05, + "loss": 0.9013, + "step": 197 + }, + { + "epoch": 0.04, + "learning_rate": 1.9996571889606956e-05, + "loss": 0.9765, + "step": 198 + }, + { + "epoch": 0.04, + "learning_rate": 1.999640671277508e-05, + "loss": 0.8804, + "step": 199 + }, + { + "epoch": 0.04, + "learning_rate": 1.999623765037147e-05, + "loss": 0.8883, + "step": 200 + }, + { + "epoch": 0.04, + "learning_rate": 1.999606470246183e-05, + "loss": 2.4217, + "step": 201 + }, + { + "epoch": 0.04, + "learning_rate": 1.9995887869113382e-05, + "loss": 0.9569, + "step": 202 + }, + { + "epoch": 0.04, + "learning_rate": 1.999570715039487e-05, + "loss": 0.9408, + "step": 203 + }, + { + "epoch": 0.04, + "learning_rate": 1.9995522546376528e-05, + "loss": 0.9467, + "step": 204 + }, + { + "epoch": 0.04, + "learning_rate": 1.9995334057130117e-05, + "loss": 0.8541, + "step": 205 + }, + { + "epoch": 0.04, + "learning_rate": 1.9995141682728904e-05, + "loss": 0.938, + "step": 206 + }, + { + "epoch": 0.04, + "learning_rate": 1.999494542324766e-05, + "loss": 0.9554, + "step": 207 + }, + { + "epoch": 0.04, + "learning_rate": 1.9994745278762676e-05, + "loss": 0.9275, + "step": 208 + }, + { + "epoch": 0.04, + "learning_rate": 1.999454124935174e-05, + "loss": 0.8765, + "step": 209 + }, + { + "epoch": 0.04, + "learning_rate": 1.9994333335094162e-05, + "loss": 0.9015, + "step": 210 + }, + { + "epoch": 0.04, + "learning_rate": 1.9994121536070757e-05, + "loss": 0.9289, + "step": 211 + }, + { + "epoch": 0.04, + "learning_rate": 1.999390585236385e-05, + "loss": 0.8851, + "step": 212 + }, + { + "epoch": 0.04, + "learning_rate": 1.9993686284057283e-05, + "loss": 0.9212, + "step": 213 + }, + { + "epoch": 0.04, + "learning_rate": 1.9993462831236386e-05, + "loss": 0.9385, + "step": 214 + }, + { + "epoch": 0.04, + "learning_rate": 1.999323549398803e-05, + "loss": 0.9351, + "step": 215 + }, + { + "epoch": 0.04, + "learning_rate": 1.9993004272400576e-05, + "loss": 0.8561, + "step": 216 + }, + { + "epoch": 0.04, + "learning_rate": 1.9992769166563894e-05, + "loss": 0.9246, + "step": 217 + }, + { + "epoch": 0.04, + "learning_rate": 1.9992530176569372e-05, + "loss": 0.926, + "step": 218 + }, + { + "epoch": 0.04, + "learning_rate": 1.999228730250991e-05, + "loss": 0.9129, + "step": 219 + }, + { + "epoch": 0.04, + "learning_rate": 1.9992040544479904e-05, + "loss": 2.8827, + "step": 220 + }, + { + "epoch": 0.04, + "learning_rate": 1.9991789902575273e-05, + "loss": 0.8951, + "step": 221 + }, + { + "epoch": 0.04, + "learning_rate": 1.9991535376893435e-05, + "loss": 2.6192, + "step": 222 + }, + { + "epoch": 0.04, + "learning_rate": 1.9991276967533332e-05, + "loss": 0.9647, + "step": 223 + }, + { + "epoch": 0.04, + "learning_rate": 1.99910146745954e-05, + "loss": 0.8961, + "step": 224 + }, + { + "epoch": 0.04, + "learning_rate": 1.9990748498181597e-05, + "loss": 2.2728, + "step": 225 + }, + { + "epoch": 0.04, + "learning_rate": 1.999047843839538e-05, + "loss": 0.9361, + "step": 226 + }, + { + "epoch": 0.04, + "learning_rate": 1.999020449534172e-05, + "loss": 0.8825, + "step": 227 + }, + { + "epoch": 0.04, + "learning_rate": 1.9989926669127105e-05, + "loss": 0.8717, + "step": 228 + }, + { + "epoch": 0.04, + "learning_rate": 1.9989644959859514e-05, + "loss": 0.9278, + "step": 229 + }, + { + "epoch": 0.04, + "learning_rate": 1.9989359367648457e-05, + "loss": 0.9299, + "step": 230 + }, + { + "epoch": 0.04, + "learning_rate": 1.998906989260494e-05, + "loss": 0.9534, + "step": 231 + }, + { + "epoch": 0.04, + "learning_rate": 1.9988776534841477e-05, + "loss": 0.9126, + "step": 232 + }, + { + "epoch": 0.04, + "learning_rate": 1.9988479294472098e-05, + "loss": 0.9336, + "step": 233 + }, + { + "epoch": 0.05, + "learning_rate": 1.9988178171612337e-05, + "loss": 0.8693, + "step": 234 + }, + { + "epoch": 0.05, + "learning_rate": 1.9987873166379245e-05, + "loss": 0.9025, + "step": 235 + }, + { + "epoch": 0.05, + "learning_rate": 1.998756427889137e-05, + "loss": 0.8997, + "step": 236 + }, + { + "epoch": 0.05, + "learning_rate": 1.998725150926878e-05, + "loss": 0.89, + "step": 237 + }, + { + "epoch": 0.05, + "learning_rate": 1.9986934857633053e-05, + "loss": 2.393, + "step": 238 + }, + { + "epoch": 0.05, + "learning_rate": 1.9986614324107255e-05, + "loss": 0.8828, + "step": 239 + }, + { + "epoch": 0.05, + "learning_rate": 1.9986289908815986e-05, + "loss": 2.6581, + "step": 240 + }, + { + "epoch": 0.05, + "learning_rate": 1.998596161188535e-05, + "loss": 0.9248, + "step": 241 + }, + { + "epoch": 0.05, + "learning_rate": 1.9985629433442944e-05, + "loss": 0.9042, + "step": 242 + }, + { + "epoch": 0.05, + "learning_rate": 1.9985293373617892e-05, + "loss": 0.9174, + "step": 243 + }, + { + "epoch": 0.05, + "learning_rate": 1.998495343254082e-05, + "loss": 0.9341, + "step": 244 + }, + { + "epoch": 0.05, + "learning_rate": 1.9984609610343857e-05, + "loss": 0.942, + "step": 245 + }, + { + "epoch": 0.05, + "learning_rate": 1.9984261907160653e-05, + "loss": 0.8998, + "step": 246 + }, + { + "epoch": 0.05, + "learning_rate": 1.9983910323126346e-05, + "loss": 0.8785, + "step": 247 + }, + { + "epoch": 0.05, + "learning_rate": 1.998355485837761e-05, + "loss": 0.8845, + "step": 248 + }, + { + "epoch": 0.05, + "learning_rate": 1.9983195513052605e-05, + "loss": 0.9347, + "step": 249 + }, + { + "epoch": 0.05, + "learning_rate": 1.998283228729101e-05, + "loss": 0.9176, + "step": 250 + }, + { + "epoch": 0.05, + "learning_rate": 1.9982465181234007e-05, + "loss": 0.9586, + "step": 251 + }, + { + "epoch": 0.05, + "learning_rate": 1.9982094195024294e-05, + "loss": 0.8903, + "step": 252 + }, + { + "epoch": 0.05, + "learning_rate": 1.9981719328806065e-05, + "loss": 0.9348, + "step": 253 + }, + { + "epoch": 0.05, + "learning_rate": 1.9981340582725038e-05, + "loss": 0.9763, + "step": 254 + }, + { + "epoch": 0.05, + "learning_rate": 1.9980957956928425e-05, + "loss": 2.5989, + "step": 255 + }, + { + "epoch": 0.05, + "learning_rate": 1.998057145156495e-05, + "loss": 0.9226, + "step": 256 + }, + { + "epoch": 0.05, + "learning_rate": 1.998018106678485e-05, + "loss": 0.891, + "step": 257 + }, + { + "epoch": 0.05, + "learning_rate": 1.9979786802739863e-05, + "loss": 0.9653, + "step": 258 + }, + { + "epoch": 0.05, + "learning_rate": 1.9979388659583246e-05, + "loss": 0.8909, + "step": 259 + }, + { + "epoch": 0.05, + "learning_rate": 1.9978986637469747e-05, + "loss": 0.9247, + "step": 260 + }, + { + "epoch": 0.05, + "learning_rate": 1.9978580736555633e-05, + "loss": 0.9055, + "step": 261 + }, + { + "epoch": 0.05, + "learning_rate": 1.9978170956998677e-05, + "loss": 0.8504, + "step": 262 + }, + { + "epoch": 0.05, + "learning_rate": 1.9977757298958164e-05, + "loss": 0.9052, + "step": 263 + }, + { + "epoch": 0.05, + "learning_rate": 1.9977339762594868e-05, + "loss": 0.9661, + "step": 264 + }, + { + "epoch": 0.05, + "learning_rate": 1.99769183480711e-05, + "loss": 0.952, + "step": 265 + }, + { + "epoch": 0.05, + "learning_rate": 1.9976493055550655e-05, + "loss": 0.8744, + "step": 266 + }, + { + "epoch": 0.05, + "learning_rate": 1.997606388519884e-05, + "loss": 0.8904, + "step": 267 + }, + { + "epoch": 0.05, + "learning_rate": 1.997563083718248e-05, + "loss": 0.8815, + "step": 268 + }, + { + "epoch": 0.05, + "learning_rate": 1.997519391166989e-05, + "loss": 2.3681, + "step": 269 + }, + { + "epoch": 0.05, + "learning_rate": 1.997475310883091e-05, + "loss": 0.8941, + "step": 270 + }, + { + "epoch": 0.05, + "learning_rate": 1.997430842883688e-05, + "loss": 0.9192, + "step": 271 + }, + { + "epoch": 0.05, + "learning_rate": 1.9973859871860635e-05, + "loss": 0.9162, + "step": 272 + }, + { + "epoch": 0.05, + "learning_rate": 1.9973407438076533e-05, + "loss": 0.9254, + "step": 273 + }, + { + "epoch": 0.05, + "learning_rate": 1.9972951127660434e-05, + "loss": 0.8783, + "step": 274 + }, + { + "epoch": 0.05, + "learning_rate": 1.9972490940789708e-05, + "loss": 0.902, + "step": 275 + }, + { + "epoch": 0.05, + "learning_rate": 1.9972026877643223e-05, + "loss": 0.9517, + "step": 276 + }, + { + "epoch": 0.05, + "learning_rate": 1.997155893840136e-05, + "loss": 0.9182, + "step": 277 + }, + { + "epoch": 0.05, + "learning_rate": 1.9971087123246008e-05, + "loss": 0.8874, + "step": 278 + }, + { + "epoch": 0.05, + "learning_rate": 1.9970611432360556e-05, + "loss": 2.3284, + "step": 279 + }, + { + "epoch": 0.05, + "learning_rate": 1.997013186592991e-05, + "loss": 0.8889, + "step": 280 + }, + { + "epoch": 0.05, + "learning_rate": 1.9969648424140467e-05, + "loss": 0.8681, + "step": 281 + }, + { + "epoch": 0.05, + "learning_rate": 1.9969161107180146e-05, + "loss": 2.4504, + "step": 282 + }, + { + "epoch": 0.05, + "learning_rate": 1.9968669915238364e-05, + "loss": 0.8838, + "step": 283 + }, + { + "epoch": 0.05, + "learning_rate": 1.9968174848506044e-05, + "loss": 0.9488, + "step": 284 + }, + { + "epoch": 0.05, + "learning_rate": 1.9967675907175617e-05, + "loss": 0.9117, + "step": 285 + }, + { + "epoch": 0.06, + "learning_rate": 1.9967173091441022e-05, + "loss": 0.8812, + "step": 286 + }, + { + "epoch": 0.06, + "learning_rate": 1.9966666401497707e-05, + "loss": 0.9091, + "step": 287 + }, + { + "epoch": 0.06, + "learning_rate": 1.9966155837542606e-05, + "loss": 0.9209, + "step": 288 + }, + { + "epoch": 0.06, + "learning_rate": 1.9965641399774187e-05, + "loss": 0.9242, + "step": 289 + }, + { + "epoch": 0.06, + "learning_rate": 1.9965123088392407e-05, + "loss": 0.9248, + "step": 290 + }, + { + "epoch": 0.06, + "learning_rate": 1.9964600903598724e-05, + "loss": 0.8664, + "step": 291 + }, + { + "epoch": 0.06, + "learning_rate": 1.9964074845596125e-05, + "loss": 0.8702, + "step": 292 + }, + { + "epoch": 0.06, + "learning_rate": 1.9963544914589073e-05, + "loss": 0.9963, + "step": 293 + }, + { + "epoch": 0.06, + "learning_rate": 1.996301111078356e-05, + "loss": 0.9096, + "step": 294 + }, + { + "epoch": 0.06, + "learning_rate": 1.9962473434387068e-05, + "loss": 0.8576, + "step": 295 + }, + { + "epoch": 0.06, + "learning_rate": 1.996193188560859e-05, + "loss": 0.9213, + "step": 296 + }, + { + "epoch": 0.06, + "learning_rate": 1.9961386464658626e-05, + "loss": 0.9229, + "step": 297 + }, + { + "epoch": 0.06, + "learning_rate": 1.9960837171749183e-05, + "loss": 0.9147, + "step": 298 + }, + { + "epoch": 0.06, + "learning_rate": 1.9960284007093764e-05, + "loss": 0.8636, + "step": 299 + }, + { + "epoch": 0.06, + "learning_rate": 1.995972697090738e-05, + "loss": 0.9169, + "step": 300 + }, + { + "epoch": 0.06, + "learning_rate": 1.9959166063406563e-05, + "loss": 0.8673, + "step": 301 + }, + { + "epoch": 0.06, + "learning_rate": 1.995860128480932e-05, + "loss": 0.8394, + "step": 302 + }, + { + "epoch": 0.06, + "learning_rate": 1.9958032635335187e-05, + "loss": 0.9012, + "step": 303 + }, + { + "epoch": 0.06, + "learning_rate": 1.9957460115205192e-05, + "loss": 0.8976, + "step": 304 + }, + { + "epoch": 0.06, + "learning_rate": 1.995688372464188e-05, + "loss": 0.8455, + "step": 305 + }, + { + "epoch": 0.06, + "learning_rate": 1.9956303463869285e-05, + "loss": 0.9157, + "step": 306 + }, + { + "epoch": 0.06, + "learning_rate": 1.995571933311295e-05, + "loss": 0.9118, + "step": 307 + }, + { + "epoch": 0.06, + "learning_rate": 1.9955131332599934e-05, + "loss": 0.9537, + "step": 308 + }, + { + "epoch": 0.06, + "learning_rate": 1.995453946255878e-05, + "loss": 0.9398, + "step": 309 + }, + { + "epoch": 0.06, + "learning_rate": 1.9953943723219553e-05, + "loss": 0.8884, + "step": 310 + }, + { + "epoch": 0.06, + "learning_rate": 1.9953344114813816e-05, + "loss": 0.8945, + "step": 311 + }, + { + "epoch": 0.06, + "learning_rate": 1.995274063757463e-05, + "loss": 0.9177, + "step": 312 + }, + { + "epoch": 0.06, + "learning_rate": 1.995213329173657e-05, + "loss": 0.8921, + "step": 313 + }, + { + "epoch": 0.06, + "learning_rate": 1.995152207753571e-05, + "loss": 2.3773, + "step": 314 + }, + { + "epoch": 0.06, + "learning_rate": 1.9950906995209617e-05, + "loss": 0.8849, + "step": 315 + }, + { + "epoch": 0.06, + "learning_rate": 1.995028804499738e-05, + "loss": 0.8814, + "step": 316 + }, + { + "epoch": 0.06, + "learning_rate": 1.9949665227139583e-05, + "loss": 2.2589, + "step": 317 + }, + { + "epoch": 0.06, + "learning_rate": 1.9949038541878312e-05, + "loss": 0.9221, + "step": 318 + }, + { + "epoch": 0.06, + "learning_rate": 1.9948407989457156e-05, + "loss": 0.8814, + "step": 319 + }, + { + "epoch": 0.06, + "learning_rate": 1.994777357012121e-05, + "loss": 0.859, + "step": 320 + }, + { + "epoch": 0.06, + "learning_rate": 1.994713528411707e-05, + "loss": 2.2627, + "step": 321 + }, + { + "epoch": 0.06, + "learning_rate": 1.9946493131692837e-05, + "loss": 2.1708, + "step": 322 + }, + { + "epoch": 0.06, + "learning_rate": 1.9945847113098112e-05, + "loss": 0.9061, + "step": 323 + }, + { + "epoch": 0.06, + "learning_rate": 1.9945197228584006e-05, + "loss": 0.8706, + "step": 324 + }, + { + "epoch": 0.06, + "learning_rate": 1.994454347840312e-05, + "loss": 0.9008, + "step": 325 + }, + { + "epoch": 0.06, + "learning_rate": 1.9943885862809566e-05, + "loss": 0.8927, + "step": 326 + }, + { + "epoch": 0.06, + "learning_rate": 1.994322438205896e-05, + "loss": 0.9191, + "step": 327 + }, + { + "epoch": 0.06, + "learning_rate": 1.9942559036408413e-05, + "loss": 0.8505, + "step": 328 + }, + { + "epoch": 0.06, + "learning_rate": 1.9941889826116546e-05, + "loss": 0.9509, + "step": 329 + }, + { + "epoch": 0.06, + "learning_rate": 1.9941216751443485e-05, + "loss": 0.8894, + "step": 330 + }, + { + "epoch": 0.06, + "learning_rate": 1.994053981265084e-05, + "loss": 0.871, + "step": 331 + }, + { + "epoch": 0.06, + "learning_rate": 1.993985901000174e-05, + "loss": 0.8624, + "step": 332 + }, + { + "epoch": 0.06, + "learning_rate": 1.9939174343760813e-05, + "loss": 0.8688, + "step": 333 + }, + { + "epoch": 0.06, + "learning_rate": 1.9938485814194182e-05, + "loss": 2.4733, + "step": 334 + }, + { + "epoch": 0.06, + "learning_rate": 1.9937793421569482e-05, + "loss": 0.9278, + "step": 335 + }, + { + "epoch": 0.06, + "learning_rate": 1.993709716615584e-05, + "loss": 0.8676, + "step": 336 + }, + { + "epoch": 0.06, + "learning_rate": 1.993639704822389e-05, + "loss": 0.8876, + "step": 337 + }, + { + "epoch": 0.07, + "learning_rate": 1.9935693068045765e-05, + "loss": 0.917, + "step": 338 + }, + { + "epoch": 0.07, + "learning_rate": 1.99349852258951e-05, + "loss": 0.9018, + "step": 339 + }, + { + "epoch": 0.07, + "learning_rate": 1.9934273522047028e-05, + "loss": 0.8855, + "step": 340 + }, + { + "epoch": 0.07, + "learning_rate": 1.9933557956778192e-05, + "loss": 0.8936, + "step": 341 + }, + { + "epoch": 0.07, + "learning_rate": 1.9932838530366726e-05, + "loss": 0.9035, + "step": 342 + }, + { + "epoch": 0.07, + "learning_rate": 1.993211524309227e-05, + "loss": 0.8944, + "step": 343 + }, + { + "epoch": 0.07, + "learning_rate": 1.9931388095235964e-05, + "loss": 0.8541, + "step": 344 + }, + { + "epoch": 0.07, + "learning_rate": 1.9930657087080446e-05, + "loss": 0.9378, + "step": 345 + }, + { + "epoch": 0.07, + "learning_rate": 1.9929922218909855e-05, + "loss": 0.8988, + "step": 346 + }, + { + "epoch": 0.07, + "learning_rate": 1.9929183491009837e-05, + "loss": 0.8937, + "step": 347 + }, + { + "epoch": 0.07, + "learning_rate": 1.9928440903667532e-05, + "loss": 0.8783, + "step": 348 + }, + { + "epoch": 0.07, + "learning_rate": 1.992769445717158e-05, + "loss": 0.9128, + "step": 349 + }, + { + "epoch": 0.07, + "learning_rate": 1.9926944151812124e-05, + "loss": 0.855, + "step": 350 + }, + { + "epoch": 0.07, + "learning_rate": 1.99261899878808e-05, + "loss": 0.8777, + "step": 351 + }, + { + "epoch": 0.07, + "learning_rate": 1.9925431965670752e-05, + "loss": 0.8686, + "step": 352 + }, + { + "epoch": 0.07, + "learning_rate": 1.9924670085476626e-05, + "loss": 0.9014, + "step": 353 + }, + { + "epoch": 0.07, + "learning_rate": 1.9923904347594558e-05, + "loss": 0.8633, + "step": 354 + }, + { + "epoch": 0.07, + "learning_rate": 1.9923134752322187e-05, + "loss": 0.8612, + "step": 355 + }, + { + "epoch": 0.07, + "learning_rate": 1.9922361299958654e-05, + "loss": 0.8516, + "step": 356 + }, + { + "epoch": 0.07, + "learning_rate": 1.99215839908046e-05, + "loss": 0.8701, + "step": 357 + }, + { + "epoch": 0.07, + "learning_rate": 1.9920802825162153e-05, + "loss": 0.8995, + "step": 358 + }, + { + "epoch": 0.07, + "learning_rate": 1.992001780333496e-05, + "loss": 0.9227, + "step": 359 + }, + { + "epoch": 0.07, + "learning_rate": 1.9919228925628152e-05, + "loss": 0.8678, + "step": 360 + }, + { + "epoch": 0.07, + "learning_rate": 1.9918436192348362e-05, + "loss": 0.9593, + "step": 361 + }, + { + "epoch": 0.07, + "learning_rate": 1.991763960380373e-05, + "loss": 0.8926, + "step": 362 + }, + { + "epoch": 0.07, + "learning_rate": 1.9916839160303878e-05, + "loss": 0.9093, + "step": 363 + }, + { + "epoch": 0.07, + "learning_rate": 1.9916034862159943e-05, + "loss": 0.9356, + "step": 364 + }, + { + "epoch": 0.07, + "learning_rate": 1.991522670968455e-05, + "loss": 0.9201, + "step": 365 + }, + { + "epoch": 0.07, + "learning_rate": 1.9914414703191823e-05, + "loss": 0.8757, + "step": 366 + }, + { + "epoch": 0.07, + "learning_rate": 1.9913598842997394e-05, + "loss": 0.9001, + "step": 367 + }, + { + "epoch": 0.07, + "learning_rate": 1.9912779129418377e-05, + "loss": 0.8995, + "step": 368 + }, + { + "epoch": 0.07, + "learning_rate": 1.991195556277339e-05, + "loss": 0.8323, + "step": 369 + }, + { + "epoch": 0.07, + "learning_rate": 1.991112814338257e-05, + "loss": 0.889, + "step": 370 + }, + { + "epoch": 0.07, + "learning_rate": 1.9910296871567508e-05, + "loss": 0.916, + "step": 371 + }, + { + "epoch": 0.07, + "learning_rate": 1.990946174765133e-05, + "loss": 0.8501, + "step": 372 + }, + { + "epoch": 0.07, + "learning_rate": 1.990862277195864e-05, + "loss": 2.7066, + "step": 373 + }, + { + "epoch": 0.07, + "learning_rate": 1.9907779944815554e-05, + "loss": 0.9214, + "step": 374 + }, + { + "epoch": 0.07, + "learning_rate": 1.9906933266549665e-05, + "loss": 0.9269, + "step": 375 + }, + { + "epoch": 0.07, + "learning_rate": 1.9906082737490086e-05, + "loss": 0.9524, + "step": 376 + }, + { + "epoch": 0.07, + "learning_rate": 1.9905228357967403e-05, + "loss": 0.8736, + "step": 377 + }, + { + "epoch": 0.07, + "learning_rate": 1.990437012831372e-05, + "loss": 0.884, + "step": 378 + }, + { + "epoch": 0.07, + "learning_rate": 1.9903508048862626e-05, + "loss": 0.8941, + "step": 379 + }, + { + "epoch": 0.07, + "learning_rate": 1.9902642119949203e-05, + "loss": 0.9201, + "step": 380 + }, + { + "epoch": 0.07, + "learning_rate": 1.9901772341910043e-05, + "loss": 2.5242, + "step": 381 + }, + { + "epoch": 0.07, + "learning_rate": 1.9900898715083218e-05, + "loss": 0.8817, + "step": 382 + }, + { + "epoch": 0.07, + "learning_rate": 1.9900021239808312e-05, + "loss": 0.901, + "step": 383 + }, + { + "epoch": 0.07, + "learning_rate": 1.989913991642639e-05, + "loss": 0.8847, + "step": 384 + }, + { + "epoch": 0.07, + "learning_rate": 1.9898254745280024e-05, + "loss": 2.4684, + "step": 385 + }, + { + "epoch": 0.07, + "learning_rate": 1.9897365726713277e-05, + "loss": 0.9136, + "step": 386 + }, + { + "epoch": 0.07, + "learning_rate": 1.9896472861071704e-05, + "loss": 0.9159, + "step": 387 + }, + { + "epoch": 0.07, + "learning_rate": 1.989557614870236e-05, + "loss": 0.9223, + "step": 388 + }, + { + "epoch": 0.07, + "learning_rate": 1.98946755899538e-05, + "loss": 0.9004, + "step": 389 + }, + { + "epoch": 0.08, + "learning_rate": 1.989377118517606e-05, + "loss": 0.79, + "step": 390 + }, + { + "epoch": 0.08, + "learning_rate": 1.9892862934720685e-05, + "loss": 0.9284, + "step": 391 + }, + { + "epoch": 0.08, + "learning_rate": 1.9891950838940708e-05, + "loss": 0.8883, + "step": 392 + }, + { + "epoch": 0.08, + "learning_rate": 1.9891034898190657e-05, + "loss": 0.9104, + "step": 393 + }, + { + "epoch": 0.08, + "learning_rate": 1.9890115112826556e-05, + "loss": 0.8942, + "step": 394 + }, + { + "epoch": 0.08, + "learning_rate": 1.988919148320592e-05, + "loss": 0.8627, + "step": 395 + }, + { + "epoch": 0.08, + "learning_rate": 1.9888264009687765e-05, + "loss": 0.9196, + "step": 396 + }, + { + "epoch": 0.08, + "learning_rate": 1.9887332692632596e-05, + "loss": 2.224, + "step": 397 + }, + { + "epoch": 0.08, + "learning_rate": 1.988639753240241e-05, + "loss": 0.9412, + "step": 398 + }, + { + "epoch": 0.08, + "learning_rate": 1.9885458529360704e-05, + "loss": 2.226, + "step": 399 + }, + { + "epoch": 0.08, + "learning_rate": 1.9884515683872464e-05, + "loss": 0.9191, + "step": 400 + }, + { + "epoch": 0.08, + "learning_rate": 1.988356899630417e-05, + "loss": 0.8795, + "step": 401 + }, + { + "epoch": 0.08, + "learning_rate": 1.9882618467023804e-05, + "loss": 0.8568, + "step": 402 + }, + { + "epoch": 0.08, + "learning_rate": 1.988166409640082e-05, + "loss": 0.8616, + "step": 403 + }, + { + "epoch": 0.08, + "learning_rate": 1.988070588480619e-05, + "loss": 0.9114, + "step": 404 + }, + { + "epoch": 0.08, + "learning_rate": 1.9879743832612367e-05, + "loss": 0.9165, + "step": 405 + }, + { + "epoch": 0.08, + "learning_rate": 1.9878777940193294e-05, + "loss": 0.9183, + "step": 406 + }, + { + "epoch": 0.08, + "learning_rate": 1.9877808207924406e-05, + "loss": 0.9264, + "step": 407 + }, + { + "epoch": 0.08, + "learning_rate": 1.9876834636182644e-05, + "loss": 0.8964, + "step": 408 + }, + { + "epoch": 0.08, + "learning_rate": 1.987585722534643e-05, + "loss": 2.1586, + "step": 409 + }, + { + "epoch": 0.08, + "learning_rate": 1.9874875975795677e-05, + "loss": 0.8004, + "step": 410 + }, + { + "epoch": 0.08, + "learning_rate": 1.9873890887911796e-05, + "loss": 0.8615, + "step": 411 + }, + { + "epoch": 0.08, + "learning_rate": 1.9872901962077687e-05, + "loss": 0.8753, + "step": 412 + }, + { + "epoch": 0.08, + "learning_rate": 1.9871909198677744e-05, + "loss": 0.8499, + "step": 413 + }, + { + "epoch": 0.08, + "learning_rate": 1.9870912598097847e-05, + "loss": 0.8729, + "step": 414 + }, + { + "epoch": 0.08, + "learning_rate": 1.986991216072538e-05, + "loss": 0.8856, + "step": 415 + }, + { + "epoch": 0.08, + "learning_rate": 1.9868907886949197e-05, + "loss": 0.8347, + "step": 416 + }, + { + "epoch": 0.08, + "learning_rate": 1.9867899777159665e-05, + "loss": 0.8403, + "step": 417 + }, + { + "epoch": 0.08, + "learning_rate": 1.9866887831748633e-05, + "loss": 0.9432, + "step": 418 + }, + { + "epoch": 0.08, + "learning_rate": 1.9865872051109435e-05, + "loss": 0.9856, + "step": 419 + }, + { + "epoch": 0.08, + "learning_rate": 1.986485243563691e-05, + "loss": 0.8538, + "step": 420 + }, + { + "epoch": 0.08, + "learning_rate": 1.9863828985727373e-05, + "loss": 0.9194, + "step": 421 + }, + { + "epoch": 0.08, + "learning_rate": 1.9862801701778637e-05, + "loss": 0.9017, + "step": 422 + }, + { + "epoch": 0.08, + "learning_rate": 1.986177058419001e-05, + "loss": 0.8562, + "step": 423 + }, + { + "epoch": 0.08, + "learning_rate": 1.9860735633362273e-05, + "loss": 0.8679, + "step": 424 + }, + { + "epoch": 0.08, + "learning_rate": 1.9859696849697718e-05, + "loss": 0.8983, + "step": 425 + }, + { + "epoch": 0.08, + "learning_rate": 1.9858654233600107e-05, + "loss": 0.885, + "step": 426 + }, + { + "epoch": 0.08, + "learning_rate": 1.9857607785474713e-05, + "loss": 0.9417, + "step": 427 + }, + { + "epoch": 0.08, + "learning_rate": 1.985655750572828e-05, + "loss": 2.3205, + "step": 428 + }, + { + "epoch": 0.08, + "learning_rate": 1.985550339476905e-05, + "loss": 2.2915, + "step": 429 + }, + { + "epoch": 0.08, + "learning_rate": 1.9854445453006753e-05, + "loss": 0.9068, + "step": 430 + }, + { + "epoch": 0.08, + "learning_rate": 1.985338368085261e-05, + "loss": 0.8349, + "step": 431 + }, + { + "epoch": 0.08, + "learning_rate": 1.9852318078719324e-05, + "loss": 0.8665, + "step": 432 + }, + { + "epoch": 0.08, + "learning_rate": 1.985124864702109e-05, + "loss": 0.9272, + "step": 433 + }, + { + "epoch": 0.08, + "learning_rate": 1.9850175386173596e-05, + "loss": 2.1325, + "step": 434 + }, + { + "epoch": 0.08, + "learning_rate": 1.984909829659402e-05, + "loss": 0.8765, + "step": 435 + }, + { + "epoch": 0.08, + "learning_rate": 1.9848017378701018e-05, + "loss": 0.9026, + "step": 436 + }, + { + "epoch": 0.08, + "learning_rate": 1.9846932632914733e-05, + "loss": 0.8801, + "step": 437 + }, + { + "epoch": 0.08, + "learning_rate": 1.9845844059656814e-05, + "loss": 0.8453, + "step": 438 + }, + { + "epoch": 0.08, + "learning_rate": 1.984475165935038e-05, + "loss": 0.8812, + "step": 439 + }, + { + "epoch": 0.08, + "learning_rate": 1.9843655432420045e-05, + "loss": 0.8965, + "step": 440 + }, + { + "epoch": 0.08, + "learning_rate": 1.9842555379291907e-05, + "loss": 0.8934, + "step": 441 + }, + { + "epoch": 0.09, + "learning_rate": 1.9841451500393552e-05, + "loss": 0.8806, + "step": 442 + }, + { + "epoch": 0.09, + "learning_rate": 1.984034379615406e-05, + "loss": 0.8848, + "step": 443 + }, + { + "epoch": 0.09, + "learning_rate": 1.9839232267003988e-05, + "loss": 0.8571, + "step": 444 + }, + { + "epoch": 0.09, + "learning_rate": 1.9838116913375386e-05, + "loss": 0.928, + "step": 445 + }, + { + "epoch": 0.09, + "learning_rate": 1.9836997735701788e-05, + "loss": 0.8896, + "step": 446 + }, + { + "epoch": 0.09, + "learning_rate": 1.983587473441821e-05, + "loss": 0.8484, + "step": 447 + }, + { + "epoch": 0.09, + "learning_rate": 1.9834747909961166e-05, + "loss": 0.8917, + "step": 448 + }, + { + "epoch": 0.09, + "learning_rate": 1.9833617262768644e-05, + "loss": 2.278, + "step": 449 + }, + { + "epoch": 0.09, + "learning_rate": 1.983248279328013e-05, + "loss": 0.8912, + "step": 450 + }, + { + "epoch": 0.09, + "learning_rate": 1.9831344501936578e-05, + "loss": 0.8804, + "step": 451 + }, + { + "epoch": 0.09, + "learning_rate": 1.983020238918045e-05, + "loss": 0.88, + "step": 452 + }, + { + "epoch": 0.09, + "learning_rate": 1.982905645545567e-05, + "loss": 0.8896, + "step": 453 + }, + { + "epoch": 0.09, + "learning_rate": 1.9827906701207667e-05, + "loss": 0.8869, + "step": 454 + }, + { + "epoch": 0.09, + "learning_rate": 1.9826753126883346e-05, + "loss": 0.9485, + "step": 455 + }, + { + "epoch": 0.09, + "learning_rate": 1.9825595732931092e-05, + "loss": 0.8552, + "step": 456 + }, + { + "epoch": 0.09, + "learning_rate": 1.9824434519800788e-05, + "loss": 0.9151, + "step": 457 + }, + { + "epoch": 0.09, + "learning_rate": 1.9823269487943787e-05, + "loss": 0.9058, + "step": 458 + }, + { + "epoch": 0.09, + "learning_rate": 1.982210063781294e-05, + "loss": 0.8899, + "step": 459 + }, + { + "epoch": 0.09, + "learning_rate": 1.9820927969862573e-05, + "loss": 2.187, + "step": 460 + }, + { + "epoch": 0.09, + "learning_rate": 1.9819751484548496e-05, + "loss": 2.1938, + "step": 461 + }, + { + "epoch": 0.09, + "learning_rate": 1.9818571182328003e-05, + "loss": 0.8661, + "step": 462 + }, + { + "epoch": 0.09, + "learning_rate": 1.981738706365988e-05, + "loss": 0.8885, + "step": 463 + }, + { + "epoch": 0.09, + "learning_rate": 1.9816199129004387e-05, + "loss": 0.9885, + "step": 464 + }, + { + "epoch": 0.09, + "learning_rate": 1.9815007378823273e-05, + "loss": 0.9154, + "step": 465 + }, + { + "epoch": 0.09, + "learning_rate": 1.981381181357976e-05, + "loss": 0.8881, + "step": 466 + }, + { + "epoch": 0.09, + "learning_rate": 1.9812612433738572e-05, + "loss": 0.8978, + "step": 467 + }, + { + "epoch": 0.09, + "learning_rate": 1.9811409239765896e-05, + "loss": 0.841, + "step": 468 + }, + { + "epoch": 0.09, + "learning_rate": 1.981020223212941e-05, + "loss": 0.8902, + "step": 469 + }, + { + "epoch": 0.09, + "learning_rate": 1.9808991411298276e-05, + "loss": 0.8813, + "step": 470 + }, + { + "epoch": 0.09, + "learning_rate": 1.9807776777743136e-05, + "loss": 0.9064, + "step": 471 + }, + { + "epoch": 0.09, + "learning_rate": 1.9806558331936118e-05, + "loss": 0.8918, + "step": 472 + }, + { + "epoch": 0.09, + "learning_rate": 1.9805336074350817e-05, + "loss": 0.8283, + "step": 473 + }, + { + "epoch": 0.09, + "learning_rate": 1.9804110005462332e-05, + "loss": 0.9719, + "step": 474 + }, + { + "epoch": 0.09, + "learning_rate": 1.9802880125747227e-05, + "loss": 0.931, + "step": 475 + }, + { + "epoch": 0.09, + "learning_rate": 1.9801646435683556e-05, + "loss": 0.8596, + "step": 476 + }, + { + "epoch": 0.09, + "learning_rate": 1.9800408935750846e-05, + "loss": 2.2522, + "step": 477 + }, + { + "epoch": 0.09, + "learning_rate": 1.979916762643011e-05, + "loss": 2.3196, + "step": 478 + }, + { + "epoch": 0.09, + "learning_rate": 1.9797922508203843e-05, + "loss": 0.8702, + "step": 479 + }, + { + "epoch": 0.09, + "learning_rate": 1.979667358155602e-05, + "loss": 0.8356, + "step": 480 + }, + { + "epoch": 0.09, + "learning_rate": 1.9795420846972088e-05, + "loss": 0.8778, + "step": 481 + }, + { + "epoch": 0.09, + "learning_rate": 1.9794164304938985e-05, + "loss": 0.8719, + "step": 482 + }, + { + "epoch": 0.09, + "learning_rate": 1.979290395594513e-05, + "loss": 0.8731, + "step": 483 + }, + { + "epoch": 0.09, + "learning_rate": 1.9791639800480408e-05, + "loss": 2.2153, + "step": 484 + }, + { + "epoch": 0.09, + "learning_rate": 1.97903718390362e-05, + "loss": 0.9212, + "step": 485 + }, + { + "epoch": 0.09, + "learning_rate": 1.9789100072105353e-05, + "loss": 0.8142, + "step": 486 + }, + { + "epoch": 0.09, + "learning_rate": 1.97878245001822e-05, + "loss": 0.9199, + "step": 487 + }, + { + "epoch": 0.09, + "learning_rate": 1.9786545123762556e-05, + "loss": 0.9506, + "step": 488 + }, + { + "epoch": 0.09, + "learning_rate": 1.9785261943343702e-05, + "loss": 0.8306, + "step": 489 + }, + { + "epoch": 0.09, + "learning_rate": 1.9783974959424412e-05, + "loss": 0.8832, + "step": 490 + }, + { + "epoch": 0.09, + "learning_rate": 1.9782684172504933e-05, + "loss": 0.8651, + "step": 491 + }, + { + "epoch": 0.09, + "learning_rate": 1.978138958308699e-05, + "loss": 0.9126, + "step": 492 + }, + { + "epoch": 0.09, + "learning_rate": 1.9780091191673784e-05, + "loss": 0.8705, + "step": 493 + }, + { + "epoch": 0.1, + "learning_rate": 1.9778788998769994e-05, + "loss": 0.895, + "step": 494 + }, + { + "epoch": 0.1, + "learning_rate": 1.9777483004881785e-05, + "loss": 0.8644, + "step": 495 + }, + { + "epoch": 0.1, + "learning_rate": 1.9776173210516783e-05, + "loss": 2.1701, + "step": 496 + }, + { + "epoch": 0.1, + "learning_rate": 1.9774859616184106e-05, + "loss": 0.9324, + "step": 497 + }, + { + "epoch": 0.1, + "learning_rate": 1.977354222239435e-05, + "loss": 0.9036, + "step": 498 + }, + { + "epoch": 0.1, + "learning_rate": 1.977222102965957e-05, + "loss": 0.8742, + "step": 499 + }, + { + "epoch": 0.1, + "learning_rate": 1.9770896038493317e-05, + "loss": 0.8798, + "step": 500 + }, + { + "epoch": 0.1, + "learning_rate": 1.976956724941061e-05, + "loss": 2.2773, + "step": 501 + }, + { + "epoch": 0.1, + "learning_rate": 1.9768234662927942e-05, + "loss": 0.9096, + "step": 502 + }, + { + "epoch": 0.1, + "learning_rate": 1.976689827956329e-05, + "loss": 2.0418, + "step": 503 + }, + { + "epoch": 0.1, + "learning_rate": 1.97655580998361e-05, + "loss": 0.8622, + "step": 504 + }, + { + "epoch": 0.1, + "learning_rate": 1.976421412426729e-05, + "loss": 2.0362, + "step": 505 + }, + { + "epoch": 0.1, + "learning_rate": 1.976286635337927e-05, + "loss": 0.8618, + "step": 506 + }, + { + "epoch": 0.1, + "learning_rate": 1.9761514787695903e-05, + "loss": 0.8195, + "step": 507 + }, + { + "epoch": 0.1, + "learning_rate": 1.9760159427742547e-05, + "loss": 0.9455, + "step": 508 + }, + { + "epoch": 0.1, + "learning_rate": 1.9758800274046022e-05, + "loss": 0.8624, + "step": 509 + }, + { + "epoch": 0.1, + "learning_rate": 1.9757437327134627e-05, + "loss": 1.9268, + "step": 510 + }, + { + "epoch": 0.1, + "learning_rate": 1.9756070587538136e-05, + "loss": 0.923, + "step": 511 + }, + { + "epoch": 0.1, + "learning_rate": 1.9754700055787798e-05, + "loss": 0.8727, + "step": 512 + }, + { + "epoch": 0.1, + "learning_rate": 1.975332573241633e-05, + "loss": 2.0775, + "step": 513 + }, + { + "epoch": 0.1, + "learning_rate": 1.975194761795793e-05, + "loss": 0.8691, + "step": 514 + }, + { + "epoch": 0.1, + "learning_rate": 1.975056571294827e-05, + "loss": 0.8607, + "step": 515 + }, + { + "epoch": 0.1, + "learning_rate": 1.9749180017924484e-05, + "loss": 0.8794, + "step": 516 + }, + { + "epoch": 0.1, + "learning_rate": 1.9747790533425192e-05, + "loss": 0.8425, + "step": 517 + }, + { + "epoch": 0.1, + "learning_rate": 1.9746397259990485e-05, + "loss": 0.8417, + "step": 518 + }, + { + "epoch": 0.1, + "learning_rate": 1.974500019816192e-05, + "loss": 0.9344, + "step": 519 + }, + { + "epoch": 0.1, + "learning_rate": 1.974359934848253e-05, + "loss": 0.8074, + "step": 520 + }, + { + "epoch": 0.1, + "learning_rate": 1.9742194711496823e-05, + "loss": 0.9141, + "step": 521 + }, + { + "epoch": 0.1, + "learning_rate": 1.9740786287750778e-05, + "loss": 0.8646, + "step": 522 + }, + { + "epoch": 0.1, + "learning_rate": 1.9739374077791843e-05, + "loss": 0.9109, + "step": 523 + }, + { + "epoch": 0.1, + "learning_rate": 1.9737958082168936e-05, + "loss": 0.9403, + "step": 524 + }, + { + "epoch": 0.1, + "learning_rate": 1.9736538301432457e-05, + "loss": 0.8529, + "step": 525 + }, + { + "epoch": 0.1, + "learning_rate": 1.9735114736134266e-05, + "loss": 0.8636, + "step": 526 + }, + { + "epoch": 0.1, + "learning_rate": 1.97336873868277e-05, + "loss": 0.8864, + "step": 527 + }, + { + "epoch": 0.1, + "learning_rate": 1.9732256254067567e-05, + "loss": 0.9097, + "step": 528 + }, + { + "epoch": 0.1, + "learning_rate": 1.973082133841014e-05, + "loss": 0.9274, + "step": 529 + }, + { + "epoch": 0.1, + "learning_rate": 1.9729382640413163e-05, + "loss": 0.8982, + "step": 530 + }, + { + "epoch": 0.1, + "learning_rate": 1.9727940160635862e-05, + "loss": 0.8219, + "step": 531 + }, + { + "epoch": 0.1, + "learning_rate": 1.972649389963892e-05, + "loss": 0.8965, + "step": 532 + }, + { + "epoch": 0.1, + "learning_rate": 1.9725043857984493e-05, + "loss": 0.9066, + "step": 533 + }, + { + "epoch": 0.1, + "learning_rate": 1.972359003623621e-05, + "loss": 2.0273, + "step": 534 + }, + { + "epoch": 0.1, + "learning_rate": 1.9722132434959163e-05, + "loss": 0.8955, + "step": 535 + }, + { + "epoch": 0.1, + "learning_rate": 1.9720671054719927e-05, + "loss": 0.9072, + "step": 536 + }, + { + "epoch": 0.1, + "learning_rate": 1.9719205896086522e-05, + "loss": 0.8935, + "step": 537 + }, + { + "epoch": 0.1, + "learning_rate": 1.971773695962846e-05, + "loss": 0.8417, + "step": 538 + }, + { + "epoch": 0.1, + "learning_rate": 1.971626424591671e-05, + "loss": 0.8562, + "step": 539 + }, + { + "epoch": 0.1, + "learning_rate": 1.971478775552371e-05, + "loss": 0.8834, + "step": 540 + }, + { + "epoch": 0.1, + "learning_rate": 1.9713307489023368e-05, + "loss": 0.8216, + "step": 541 + }, + { + "epoch": 0.1, + "learning_rate": 1.9711823446991056e-05, + "loss": 0.8705, + "step": 542 + }, + { + "epoch": 0.1, + "learning_rate": 1.9710335630003623e-05, + "loss": 0.8728, + "step": 543 + }, + { + "epoch": 0.1, + "learning_rate": 1.9708844038639373e-05, + "loss": 0.8557, + "step": 544 + }, + { + "epoch": 0.1, + "learning_rate": 1.9707348673478083e-05, + "loss": 1.9381, + "step": 545 + }, + { + "epoch": 0.11, + "learning_rate": 1.9705849535101e-05, + "loss": 0.8903, + "step": 546 + }, + { + "epoch": 0.11, + "learning_rate": 1.9704346624090833e-05, + "loss": 0.8862, + "step": 547 + }, + { + "epoch": 0.11, + "learning_rate": 1.9702839941031758e-05, + "loss": 0.9135, + "step": 548 + }, + { + "epoch": 0.11, + "learning_rate": 1.970132948650942e-05, + "loss": 0.9116, + "step": 549 + }, + { + "epoch": 0.11, + "learning_rate": 1.9699815261110925e-05, + "loss": 0.8216, + "step": 550 + }, + { + "epoch": 0.11, + "learning_rate": 1.9698297265424848e-05, + "loss": 0.9355, + "step": 551 + }, + { + "epoch": 0.11, + "learning_rate": 1.9696775500041227e-05, + "loss": 0.8924, + "step": 552 + }, + { + "epoch": 0.11, + "learning_rate": 1.9695249965551574e-05, + "loss": 0.9105, + "step": 553 + }, + { + "epoch": 0.11, + "learning_rate": 1.969372066254886e-05, + "loss": 0.8302, + "step": 554 + }, + { + "epoch": 0.11, + "learning_rate": 1.969218759162751e-05, + "loss": 0.8756, + "step": 555 + }, + { + "epoch": 0.11, + "learning_rate": 1.9690650753383434e-05, + "loss": 2.2122, + "step": 556 + }, + { + "epoch": 0.11, + "learning_rate": 1.968911014841399e-05, + "loss": 0.8221, + "step": 557 + }, + { + "epoch": 0.11, + "learning_rate": 1.9687565777318008e-05, + "loss": 0.8695, + "step": 558 + }, + { + "epoch": 0.11, + "learning_rate": 1.9686017640695783e-05, + "loss": 0.8514, + "step": 559 + }, + { + "epoch": 0.11, + "learning_rate": 1.9684465739149066e-05, + "loss": 0.8399, + "step": 560 + }, + { + "epoch": 0.11, + "learning_rate": 1.968291007328108e-05, + "loss": 0.8971, + "step": 561 + }, + { + "epoch": 0.11, + "learning_rate": 1.968135064369651e-05, + "loss": 0.8107, + "step": 562 + }, + { + "epoch": 0.11, + "learning_rate": 1.9679787451001492e-05, + "loss": 0.9083, + "step": 563 + }, + { + "epoch": 0.11, + "learning_rate": 1.967822049580364e-05, + "loss": 0.9752, + "step": 564 + }, + { + "epoch": 0.11, + "learning_rate": 1.9676649778712023e-05, + "loss": 0.8837, + "step": 565 + }, + { + "epoch": 0.11, + "learning_rate": 1.9675075300337177e-05, + "loss": 0.9044, + "step": 566 + }, + { + "epoch": 0.11, + "learning_rate": 1.9673497061291096e-05, + "loss": 0.8906, + "step": 567 + }, + { + "epoch": 0.11, + "learning_rate": 1.9671915062187236e-05, + "loss": 0.9388, + "step": 568 + }, + { + "epoch": 0.11, + "learning_rate": 1.9670329303640508e-05, + "loss": 0.8719, + "step": 569 + }, + { + "epoch": 0.11, + "learning_rate": 1.9668739786267305e-05, + "loss": 0.9038, + "step": 570 + }, + { + "epoch": 0.11, + "learning_rate": 1.9667146510685457e-05, + "loss": 0.8419, + "step": 571 + }, + { + "epoch": 0.11, + "learning_rate": 1.966554947751427e-05, + "loss": 0.8479, + "step": 572 + }, + { + "epoch": 0.11, + "learning_rate": 1.96639486873745e-05, + "loss": 0.8749, + "step": 573 + }, + { + "epoch": 0.11, + "learning_rate": 1.9662344140888373e-05, + "loss": 0.9301, + "step": 574 + }, + { + "epoch": 0.11, + "learning_rate": 1.9660735838679575e-05, + "loss": 0.8432, + "step": 575 + }, + { + "epoch": 0.11, + "learning_rate": 1.9659123781373243e-05, + "loss": 0.8843, + "step": 576 + }, + { + "epoch": 0.11, + "learning_rate": 1.9657507969595974e-05, + "loss": 0.8868, + "step": 577 + }, + { + "epoch": 0.11, + "learning_rate": 1.965588840397584e-05, + "loss": 0.8831, + "step": 578 + }, + { + "epoch": 0.11, + "learning_rate": 1.9654265085142356e-05, + "loss": 0.9226, + "step": 579 + }, + { + "epoch": 0.11, + "learning_rate": 1.96526380137265e-05, + "loss": 0.8238, + "step": 580 + }, + { + "epoch": 0.11, + "learning_rate": 1.965100719036071e-05, + "loss": 0.8839, + "step": 581 + }, + { + "epoch": 0.11, + "learning_rate": 1.9649372615678883e-05, + "loss": 0.8648, + "step": 582 + }, + { + "epoch": 0.11, + "learning_rate": 1.964773429031637e-05, + "loss": 0.9046, + "step": 583 + }, + { + "epoch": 0.11, + "learning_rate": 1.9646092214909985e-05, + "loss": 0.9295, + "step": 584 + }, + { + "epoch": 0.11, + "learning_rate": 1.9644446390098e-05, + "loss": 0.8591, + "step": 585 + }, + { + "epoch": 0.11, + "learning_rate": 1.9642796816520134e-05, + "loss": 0.8256, + "step": 586 + }, + { + "epoch": 0.11, + "learning_rate": 1.964114349481758e-05, + "loss": 0.9197, + "step": 587 + }, + { + "epoch": 0.11, + "learning_rate": 1.9639486425632978e-05, + "loss": 0.8519, + "step": 588 + }, + { + "epoch": 0.11, + "learning_rate": 1.963782560961042e-05, + "loss": 0.8848, + "step": 589 + }, + { + "epoch": 0.11, + "learning_rate": 1.9636161047395464e-05, + "loss": 0.8409, + "step": 590 + }, + { + "epoch": 0.11, + "learning_rate": 1.9634492739635117e-05, + "loss": 0.8821, + "step": 591 + }, + { + "epoch": 0.11, + "learning_rate": 1.963282068697785e-05, + "loss": 0.8602, + "step": 592 + }, + { + "epoch": 0.11, + "learning_rate": 1.9631144890073577e-05, + "loss": 0.8957, + "step": 593 + }, + { + "epoch": 0.11, + "learning_rate": 1.9629465349573686e-05, + "loss": 2.1188, + "step": 594 + }, + { + "epoch": 0.11, + "learning_rate": 1.9627782066131e-05, + "loss": 0.7983, + "step": 595 + }, + { + "epoch": 0.11, + "learning_rate": 1.9626095040399807e-05, + "loss": 0.8505, + "step": 596 + }, + { + "epoch": 0.11, + "learning_rate": 1.962440427303585e-05, + "loss": 0.9251, + "step": 597 + }, + { + "epoch": 0.12, + "learning_rate": 1.9622709764696323e-05, + "loss": 0.8512, + "step": 598 + }, + { + "epoch": 0.12, + "learning_rate": 1.9621011516039882e-05, + "loss": 0.9174, + "step": 599 + }, + { + "epoch": 0.12, + "learning_rate": 1.9619309527726624e-05, + "loss": 0.84, + "step": 600 + }, + { + "epoch": 0.12, + "learning_rate": 1.9617603800418113e-05, + "loss": 0.8534, + "step": 601 + }, + { + "epoch": 0.12, + "learning_rate": 1.961589433477735e-05, + "loss": 0.8736, + "step": 602 + }, + { + "epoch": 0.12, + "learning_rate": 1.9614181131468815e-05, + "loss": 0.8835, + "step": 603 + }, + { + "epoch": 0.12, + "learning_rate": 1.961246419115841e-05, + "loss": 0.8491, + "step": 604 + }, + { + "epoch": 0.12, + "learning_rate": 1.9610743514513507e-05, + "loss": 0.8787, + "step": 605 + }, + { + "epoch": 0.12, + "learning_rate": 1.960901910220293e-05, + "loss": 0.9005, + "step": 606 + }, + { + "epoch": 0.12, + "learning_rate": 1.9607290954896952e-05, + "loss": 0.9102, + "step": 607 + }, + { + "epoch": 0.12, + "learning_rate": 1.96055590732673e-05, + "loss": 0.8503, + "step": 608 + }, + { + "epoch": 0.12, + "learning_rate": 1.9603823457987153e-05, + "loss": 0.8691, + "step": 609 + }, + { + "epoch": 0.12, + "learning_rate": 1.9602084109731132e-05, + "loss": 0.9273, + "step": 610 + }, + { + "epoch": 0.12, + "learning_rate": 1.9600341029175323e-05, + "loss": 0.9245, + "step": 611 + }, + { + "epoch": 0.12, + "learning_rate": 1.959859421699725e-05, + "loss": 0.9015, + "step": 612 + }, + { + "epoch": 0.12, + "learning_rate": 1.95968436738759e-05, + "loss": 0.8847, + "step": 613 + }, + { + "epoch": 0.12, + "learning_rate": 1.9595089400491697e-05, + "loss": 0.856, + "step": 614 + }, + { + "epoch": 0.12, + "learning_rate": 1.9593331397526524e-05, + "loss": 0.7942, + "step": 615 + }, + { + "epoch": 0.12, + "learning_rate": 1.959156966566371e-05, + "loss": 0.8934, + "step": 616 + }, + { + "epoch": 0.12, + "learning_rate": 1.9589804205588043e-05, + "loss": 0.9177, + "step": 617 + }, + { + "epoch": 0.12, + "learning_rate": 1.958803501798574e-05, + "loss": 0.8901, + "step": 618 + }, + { + "epoch": 0.12, + "learning_rate": 1.9586262103544484e-05, + "loss": 0.8884, + "step": 619 + }, + { + "epoch": 0.12, + "learning_rate": 1.9584485462953404e-05, + "loss": 2.0931, + "step": 620 + }, + { + "epoch": 0.12, + "learning_rate": 1.9582705096903068e-05, + "loss": 0.8792, + "step": 621 + }, + { + "epoch": 0.12, + "learning_rate": 1.9580921006085506e-05, + "loss": 0.8693, + "step": 622 + }, + { + "epoch": 0.12, + "learning_rate": 1.957913319119418e-05, + "loss": 2.0109, + "step": 623 + }, + { + "epoch": 0.12, + "learning_rate": 1.9577341652924016e-05, + "loss": 2.1153, + "step": 624 + }, + { + "epoch": 0.12, + "learning_rate": 1.9575546391971376e-05, + "loss": 0.8229, + "step": 625 + }, + { + "epoch": 0.12, + "learning_rate": 1.957374740903407e-05, + "loss": 0.8667, + "step": 626 + }, + { + "epoch": 0.12, + "learning_rate": 1.957194470481136e-05, + "loss": 0.9419, + "step": 627 + }, + { + "epoch": 0.12, + "learning_rate": 1.957013828000395e-05, + "loss": 0.9232, + "step": 628 + }, + { + "epoch": 0.12, + "learning_rate": 1.9568328135313995e-05, + "loss": 0.8608, + "step": 629 + }, + { + "epoch": 0.12, + "learning_rate": 1.9566514271445086e-05, + "loss": 0.896, + "step": 630 + }, + { + "epoch": 0.12, + "learning_rate": 1.9564696689102274e-05, + "loss": 0.8773, + "step": 631 + }, + { + "epoch": 0.12, + "learning_rate": 1.956287538899204e-05, + "loss": 0.9829, + "step": 632 + }, + { + "epoch": 0.12, + "learning_rate": 1.9561050371822325e-05, + "loss": 0.9084, + "step": 633 + }, + { + "epoch": 0.12, + "learning_rate": 1.9559221638302502e-05, + "loss": 0.9247, + "step": 634 + }, + { + "epoch": 0.12, + "learning_rate": 1.9557389189143392e-05, + "loss": 1.9523, + "step": 635 + }, + { + "epoch": 0.12, + "learning_rate": 1.955555302505727e-05, + "loss": 0.8928, + "step": 636 + }, + { + "epoch": 0.12, + "learning_rate": 1.955371314675784e-05, + "loss": 0.8833, + "step": 637 + }, + { + "epoch": 0.12, + "learning_rate": 1.9551869554960263e-05, + "loss": 0.9029, + "step": 638 + }, + { + "epoch": 0.12, + "learning_rate": 1.955002225038113e-05, + "loss": 0.9104, + "step": 639 + }, + { + "epoch": 0.12, + "learning_rate": 1.954817123373849e-05, + "loss": 0.8972, + "step": 640 + }, + { + "epoch": 0.12, + "learning_rate": 1.9546316505751823e-05, + "loss": 0.9438, + "step": 641 + }, + { + "epoch": 0.12, + "learning_rate": 1.9544458067142056e-05, + "loss": 1.9818, + "step": 642 + }, + { + "epoch": 0.12, + "learning_rate": 1.954259591863156e-05, + "loss": 0.8804, + "step": 643 + }, + { + "epoch": 0.12, + "learning_rate": 1.9540730060944142e-05, + "loss": 0.8838, + "step": 644 + }, + { + "epoch": 0.12, + "learning_rate": 1.953886049480506e-05, + "loss": 0.8327, + "step": 645 + }, + { + "epoch": 0.12, + "learning_rate": 1.953698722094101e-05, + "loss": 0.8597, + "step": 646 + }, + { + "epoch": 0.12, + "learning_rate": 1.953511024008012e-05, + "loss": 0.8605, + "step": 647 + }, + { + "epoch": 0.12, + "learning_rate": 1.9533229552951972e-05, + "loss": 1.8238, + "step": 648 + }, + { + "epoch": 0.12, + "learning_rate": 1.9531345160287582e-05, + "loss": 0.8499, + "step": 649 + }, + { + "epoch": 0.13, + "learning_rate": 1.9529457062819408e-05, + "loss": 1.8133, + "step": 650 + }, + { + "epoch": 0.13, + "learning_rate": 1.9527565261281346e-05, + "loss": 0.975, + "step": 651 + }, + { + "epoch": 0.13, + "learning_rate": 1.9525669756408737e-05, + "loss": 0.8545, + "step": 652 + }, + { + "epoch": 0.13, + "learning_rate": 1.9523770548938352e-05, + "loss": 0.8604, + "step": 653 + }, + { + "epoch": 0.13, + "learning_rate": 1.9521867639608412e-05, + "loss": 0.8803, + "step": 654 + }, + { + "epoch": 0.13, + "learning_rate": 1.951996102915857e-05, + "loss": 0.8892, + "step": 655 + }, + { + "epoch": 0.13, + "learning_rate": 1.9518050718329918e-05, + "loss": 0.8221, + "step": 656 + }, + { + "epoch": 0.13, + "learning_rate": 1.951613670786499e-05, + "loss": 0.8612, + "step": 657 + }, + { + "epoch": 0.13, + "learning_rate": 1.9514218998507754e-05, + "loss": 0.863, + "step": 658 + }, + { + "epoch": 0.13, + "learning_rate": 1.951229759100362e-05, + "loss": 0.8964, + "step": 659 + }, + { + "epoch": 0.13, + "learning_rate": 1.951037248609943e-05, + "loss": 0.7953, + "step": 660 + }, + { + "epoch": 0.13, + "learning_rate": 1.9508443684543468e-05, + "loss": 0.8492, + "step": 661 + }, + { + "epoch": 0.13, + "learning_rate": 1.9506511187085455e-05, + "loss": 0.9282, + "step": 662 + }, + { + "epoch": 0.13, + "learning_rate": 1.950457499447654e-05, + "loss": 1.9091, + "step": 663 + }, + { + "epoch": 0.13, + "learning_rate": 1.9502635107469326e-05, + "loss": 0.8868, + "step": 664 + }, + { + "epoch": 0.13, + "learning_rate": 1.950069152681783e-05, + "loss": 0.8996, + "step": 665 + }, + { + "epoch": 0.13, + "learning_rate": 1.9498744253277522e-05, + "loss": 0.9014, + "step": 666 + }, + { + "epoch": 0.13, + "learning_rate": 1.9496793287605294e-05, + "loss": 0.8978, + "step": 667 + }, + { + "epoch": 0.13, + "learning_rate": 1.949483863055949e-05, + "loss": 0.8086, + "step": 668 + }, + { + "epoch": 0.13, + "learning_rate": 1.9492880282899876e-05, + "loss": 0.9433, + "step": 669 + }, + { + "epoch": 0.13, + "learning_rate": 1.949091824538765e-05, + "loss": 0.8898, + "step": 670 + }, + { + "epoch": 0.13, + "learning_rate": 1.9488952518785455e-05, + "loss": 0.8698, + "step": 671 + }, + { + "epoch": 0.13, + "learning_rate": 1.948698310385736e-05, + "loss": 0.9142, + "step": 672 + }, + { + "epoch": 0.13, + "learning_rate": 1.9485010001368878e-05, + "loss": 0.867, + "step": 673 + }, + { + "epoch": 0.13, + "learning_rate": 1.9483033212086936e-05, + "loss": 0.8496, + "step": 674 + }, + { + "epoch": 0.13, + "learning_rate": 1.9481052736779914e-05, + "loss": 0.8595, + "step": 675 + }, + { + "epoch": 0.13, + "learning_rate": 1.947906857621761e-05, + "loss": 0.802, + "step": 676 + }, + { + "epoch": 0.13, + "learning_rate": 1.9477080731171267e-05, + "loss": 0.8684, + "step": 677 + }, + { + "epoch": 0.13, + "learning_rate": 1.947508920241355e-05, + "loss": 0.8849, + "step": 678 + }, + { + "epoch": 0.13, + "learning_rate": 1.9473093990718567e-05, + "loss": 0.8859, + "step": 679 + }, + { + "epoch": 0.13, + "learning_rate": 1.9471095096861843e-05, + "loss": 0.9454, + "step": 680 + }, + { + "epoch": 0.13, + "learning_rate": 1.9469092521620342e-05, + "loss": 0.8724, + "step": 681 + }, + { + "epoch": 0.13, + "learning_rate": 1.946708626577246e-05, + "loss": 0.8913, + "step": 682 + }, + { + "epoch": 0.13, + "learning_rate": 1.9465076330098025e-05, + "loss": 0.9397, + "step": 683 + }, + { + "epoch": 0.13, + "learning_rate": 1.946306271537829e-05, + "loss": 0.8886, + "step": 684 + }, + { + "epoch": 0.13, + "learning_rate": 1.9461045422395943e-05, + "loss": 0.8837, + "step": 685 + }, + { + "epoch": 0.13, + "learning_rate": 1.9459024451935097e-05, + "loss": 0.8523, + "step": 686 + }, + { + "epoch": 0.13, + "learning_rate": 1.9456999804781298e-05, + "loss": 0.912, + "step": 687 + }, + { + "epoch": 0.13, + "learning_rate": 1.9454971481721515e-05, + "loss": 0.853, + "step": 688 + }, + { + "epoch": 0.13, + "learning_rate": 1.945293948354416e-05, + "loss": 0.8732, + "step": 689 + }, + { + "epoch": 0.13, + "learning_rate": 1.945090381103906e-05, + "loss": 0.8319, + "step": 690 + }, + { + "epoch": 0.13, + "learning_rate": 1.9448864464997474e-05, + "loss": 0.9067, + "step": 691 + }, + { + "epoch": 0.13, + "learning_rate": 1.9446821446212087e-05, + "loss": 0.8413, + "step": 692 + }, + { + "epoch": 0.13, + "learning_rate": 1.944477475547702e-05, + "loss": 0.8596, + "step": 693 + }, + { + "epoch": 0.13, + "learning_rate": 1.9442724393587806e-05, + "loss": 1.9811, + "step": 694 + }, + { + "epoch": 0.13, + "learning_rate": 1.9440670361341422e-05, + "loss": 0.8762, + "step": 695 + }, + { + "epoch": 0.13, + "learning_rate": 1.9438612659536265e-05, + "loss": 0.8925, + "step": 696 + }, + { + "epoch": 0.13, + "learning_rate": 1.943655128897215e-05, + "loss": 0.8583, + "step": 697 + }, + { + "epoch": 0.13, + "learning_rate": 1.943448625045033e-05, + "loss": 0.855, + "step": 698 + }, + { + "epoch": 0.13, + "learning_rate": 1.943241754477348e-05, + "loss": 0.8727, + "step": 699 + }, + { + "epoch": 0.13, + "learning_rate": 1.9430345172745694e-05, + "loss": 0.9028, + "step": 700 + }, + { + "epoch": 0.13, + "learning_rate": 1.9428269135172503e-05, + "loss": 0.8321, + "step": 701 + }, + { + "epoch": 0.14, + "learning_rate": 1.9426189432860853e-05, + "loss": 0.8855, + "step": 702 + }, + { + "epoch": 0.14, + "learning_rate": 1.9424106066619117e-05, + "loss": 0.8865, + "step": 703 + }, + { + "epoch": 0.14, + "learning_rate": 1.9422019037257093e-05, + "loss": 0.9184, + "step": 704 + }, + { + "epoch": 0.14, + "learning_rate": 1.9419928345586007e-05, + "loss": 0.8623, + "step": 705 + }, + { + "epoch": 0.14, + "learning_rate": 1.9417833992418495e-05, + "loss": 0.8802, + "step": 706 + }, + { + "epoch": 0.14, + "learning_rate": 1.9415735978568636e-05, + "loss": 0.8327, + "step": 707 + }, + { + "epoch": 0.14, + "learning_rate": 1.9413634304851918e-05, + "loss": 0.901, + "step": 708 + }, + { + "epoch": 0.14, + "learning_rate": 1.9411528972085248e-05, + "loss": 0.887, + "step": 709 + }, + { + "epoch": 0.14, + "learning_rate": 1.9409419981086966e-05, + "loss": 0.8469, + "step": 710 + }, + { + "epoch": 0.14, + "learning_rate": 1.940730733267684e-05, + "loss": 0.852, + "step": 711 + }, + { + "epoch": 0.14, + "learning_rate": 1.9405191027676036e-05, + "loss": 0.8505, + "step": 712 + }, + { + "epoch": 0.14, + "learning_rate": 1.940307106690716e-05, + "loss": 0.8865, + "step": 713 + }, + { + "epoch": 0.14, + "learning_rate": 1.9400947451194242e-05, + "loss": 0.8612, + "step": 714 + }, + { + "epoch": 0.14, + "learning_rate": 1.9398820181362713e-05, + "loss": 0.8542, + "step": 715 + }, + { + "epoch": 0.14, + "learning_rate": 1.939668925823944e-05, + "loss": 0.8302, + "step": 716 + }, + { + "epoch": 0.14, + "learning_rate": 1.9394554682652705e-05, + "loss": 0.8421, + "step": 717 + }, + { + "epoch": 0.14, + "learning_rate": 1.9392416455432216e-05, + "loss": 0.8609, + "step": 718 + }, + { + "epoch": 0.14, + "learning_rate": 1.939027457740909e-05, + "loss": 0.927, + "step": 719 + }, + { + "epoch": 0.14, + "learning_rate": 1.938812904941587e-05, + "loss": 0.8404, + "step": 720 + }, + { + "epoch": 0.14, + "learning_rate": 1.9385979872286516e-05, + "loss": 0.8801, + "step": 721 + }, + { + "epoch": 0.14, + "learning_rate": 1.9383827046856405e-05, + "loss": 0.8907, + "step": 722 + }, + { + "epoch": 0.14, + "learning_rate": 1.9381670573962338e-05, + "loss": 0.8869, + "step": 723 + }, + { + "epoch": 0.14, + "learning_rate": 1.937951045444252e-05, + "loss": 0.8716, + "step": 724 + }, + { + "epoch": 0.14, + "learning_rate": 1.937734668913659e-05, + "loss": 0.8687, + "step": 725 + }, + { + "epoch": 0.14, + "learning_rate": 1.93751792788856e-05, + "loss": 0.8647, + "step": 726 + }, + { + "epoch": 0.14, + "learning_rate": 1.937300822453201e-05, + "loss": 0.8559, + "step": 727 + }, + { + "epoch": 0.14, + "learning_rate": 1.93708335269197e-05, + "loss": 0.8217, + "step": 728 + }, + { + "epoch": 0.14, + "learning_rate": 1.936865518689397e-05, + "loss": 0.9501, + "step": 729 + }, + { + "epoch": 0.14, + "learning_rate": 1.9366473205301536e-05, + "loss": 0.8201, + "step": 730 + }, + { + "epoch": 0.14, + "learning_rate": 1.9364287582990526e-05, + "loss": 0.9139, + "step": 731 + }, + { + "epoch": 0.14, + "learning_rate": 1.9362098320810486e-05, + "loss": 0.8904, + "step": 732 + }, + { + "epoch": 0.14, + "learning_rate": 1.935990541961237e-05, + "loss": 2.0239, + "step": 733 + }, + { + "epoch": 0.14, + "learning_rate": 1.9357708880248563e-05, + "loss": 0.8731, + "step": 734 + }, + { + "epoch": 0.14, + "learning_rate": 1.9355508703572837e-05, + "loss": 0.918, + "step": 735 + }, + { + "epoch": 0.14, + "learning_rate": 1.935330489044041e-05, + "loss": 0.829, + "step": 736 + }, + { + "epoch": 0.14, + "learning_rate": 1.9351097441707885e-05, + "loss": 0.8486, + "step": 737 + }, + { + "epoch": 0.14, + "learning_rate": 1.9348886358233295e-05, + "loss": 0.8167, + "step": 738 + }, + { + "epoch": 0.14, + "learning_rate": 1.934667164087608e-05, + "loss": 0.8382, + "step": 739 + }, + { + "epoch": 0.14, + "learning_rate": 1.9344453290497097e-05, + "loss": 0.8167, + "step": 740 + }, + { + "epoch": 0.14, + "learning_rate": 1.934223130795861e-05, + "loss": 0.8882, + "step": 741 + }, + { + "epoch": 0.14, + "learning_rate": 1.9340005694124294e-05, + "loss": 0.8594, + "step": 742 + }, + { + "epoch": 0.14, + "learning_rate": 1.9337776449859243e-05, + "loss": 0.8371, + "step": 743 + }, + { + "epoch": 0.14, + "learning_rate": 1.9335543576029952e-05, + "loss": 0.8908, + "step": 744 + }, + { + "epoch": 0.14, + "learning_rate": 1.9333307073504336e-05, + "loss": 0.7918, + "step": 745 + }, + { + "epoch": 0.14, + "learning_rate": 1.9331066943151714e-05, + "loss": 0.8961, + "step": 746 + }, + { + "epoch": 0.14, + "learning_rate": 1.9328823185842816e-05, + "loss": 1.9781, + "step": 747 + }, + { + "epoch": 0.14, + "learning_rate": 1.932657580244979e-05, + "loss": 0.8739, + "step": 748 + }, + { + "epoch": 0.14, + "learning_rate": 1.932432479384618e-05, + "loss": 0.8734, + "step": 749 + }, + { + "epoch": 0.14, + "learning_rate": 1.9322070160906946e-05, + "loss": 1.851, + "step": 750 + }, + { + "epoch": 0.14, + "learning_rate": 1.9319811904508464e-05, + "loss": 0.8423, + "step": 751 + }, + { + "epoch": 0.14, + "learning_rate": 1.9317550025528505e-05, + "loss": 0.8527, + "step": 752 + }, + { + "epoch": 0.14, + "learning_rate": 1.9315284524846257e-05, + "loss": 0.8168, + "step": 753 + }, + { + "epoch": 0.15, + "learning_rate": 1.931301540334231e-05, + "loss": 0.9058, + "step": 754 + }, + { + "epoch": 0.15, + "learning_rate": 1.9310742661898666e-05, + "loss": 0.8983, + "step": 755 + }, + { + "epoch": 0.15, + "learning_rate": 1.9308466301398734e-05, + "loss": 0.8756, + "step": 756 + }, + { + "epoch": 0.15, + "learning_rate": 1.9306186322727325e-05, + "loss": 0.8961, + "step": 757 + }, + { + "epoch": 0.15, + "learning_rate": 1.930390272677066e-05, + "loss": 0.8812, + "step": 758 + }, + { + "epoch": 0.15, + "learning_rate": 1.930161551441637e-05, + "loss": 0.8903, + "step": 759 + }, + { + "epoch": 0.15, + "learning_rate": 1.929932468655348e-05, + "loss": 0.8206, + "step": 760 + }, + { + "epoch": 0.15, + "learning_rate": 1.9297030244072436e-05, + "loss": 0.8757, + "step": 761 + }, + { + "epoch": 0.15, + "learning_rate": 1.929473218786507e-05, + "loss": 0.8794, + "step": 762 + }, + { + "epoch": 0.15, + "learning_rate": 1.9292430518824642e-05, + "loss": 0.8377, + "step": 763 + }, + { + "epoch": 0.15, + "learning_rate": 1.9290125237845793e-05, + "loss": 0.83, + "step": 764 + }, + { + "epoch": 0.15, + "learning_rate": 1.928781634582458e-05, + "loss": 0.8953, + "step": 765 + }, + { + "epoch": 0.15, + "learning_rate": 1.9285503843658468e-05, + "loss": 0.8498, + "step": 766 + }, + { + "epoch": 0.15, + "learning_rate": 1.9283187732246315e-05, + "loss": 0.8585, + "step": 767 + }, + { + "epoch": 0.15, + "learning_rate": 1.9280868012488386e-05, + "loss": 0.8535, + "step": 768 + }, + { + "epoch": 0.15, + "learning_rate": 1.9278544685286347e-05, + "loss": 0.8518, + "step": 769 + }, + { + "epoch": 0.15, + "learning_rate": 1.9276217751543274e-05, + "loss": 0.8809, + "step": 770 + }, + { + "epoch": 0.15, + "learning_rate": 1.927388721216363e-05, + "loss": 0.8461, + "step": 771 + }, + { + "epoch": 0.15, + "learning_rate": 1.92715530680533e-05, + "loss": 0.9018, + "step": 772 + }, + { + "epoch": 0.15, + "learning_rate": 1.9269215320119547e-05, + "loss": 0.8726, + "step": 773 + }, + { + "epoch": 0.15, + "learning_rate": 1.9266873969271053e-05, + "loss": 0.8377, + "step": 774 + }, + { + "epoch": 0.15, + "learning_rate": 1.926452901641789e-05, + "loss": 0.8281, + "step": 775 + }, + { + "epoch": 0.15, + "learning_rate": 1.9262180462471538e-05, + "loss": 0.8872, + "step": 776 + }, + { + "epoch": 0.15, + "learning_rate": 1.925982830834487e-05, + "loss": 0.8049, + "step": 777 + }, + { + "epoch": 0.15, + "learning_rate": 1.925747255495216e-05, + "loss": 0.9033, + "step": 778 + }, + { + "epoch": 0.15, + "learning_rate": 1.9255113203209083e-05, + "loss": 0.8644, + "step": 779 + }, + { + "epoch": 0.15, + "learning_rate": 1.9252750254032712e-05, + "loss": 0.8596, + "step": 780 + }, + { + "epoch": 0.15, + "learning_rate": 1.925038370834152e-05, + "loss": 0.9318, + "step": 781 + }, + { + "epoch": 0.15, + "learning_rate": 1.924801356705537e-05, + "loss": 0.9098, + "step": 782 + }, + { + "epoch": 0.15, + "learning_rate": 1.924563983109553e-05, + "loss": 0.8574, + "step": 783 + }, + { + "epoch": 0.15, + "learning_rate": 1.924326250138467e-05, + "loss": 0.908, + "step": 784 + }, + { + "epoch": 0.15, + "learning_rate": 1.9240881578846838e-05, + "loss": 0.8794, + "step": 785 + }, + { + "epoch": 0.15, + "learning_rate": 1.9238497064407505e-05, + "loss": 0.8415, + "step": 786 + }, + { + "epoch": 0.15, + "learning_rate": 1.9236108958993517e-05, + "loss": 0.8942, + "step": 787 + }, + { + "epoch": 0.15, + "learning_rate": 1.9233717263533124e-05, + "loss": 0.887, + "step": 788 + }, + { + "epoch": 0.15, + "learning_rate": 1.923132197895597e-05, + "loss": 0.9117, + "step": 789 + }, + { + "epoch": 0.15, + "learning_rate": 1.9228923106193098e-05, + "loss": 0.8875, + "step": 790 + }, + { + "epoch": 0.15, + "learning_rate": 1.9226520646176937e-05, + "loss": 0.8072, + "step": 791 + }, + { + "epoch": 0.15, + "learning_rate": 1.922411459984132e-05, + "loss": 0.8604, + "step": 792 + }, + { + "epoch": 0.15, + "learning_rate": 1.9221704968121467e-05, + "loss": 0.8764, + "step": 793 + }, + { + "epoch": 0.15, + "learning_rate": 1.9219291751953993e-05, + "loss": 0.8258, + "step": 794 + }, + { + "epoch": 0.15, + "learning_rate": 1.9216874952276914e-05, + "loss": 0.8293, + "step": 795 + }, + { + "epoch": 0.15, + "learning_rate": 1.9214454570029624e-05, + "loss": 2.0036, + "step": 796 + }, + { + "epoch": 0.15, + "learning_rate": 1.9212030606152922e-05, + "loss": 0.9099, + "step": 797 + }, + { + "epoch": 0.15, + "learning_rate": 1.9209603061588997e-05, + "loss": 0.8709, + "step": 798 + }, + { + "epoch": 0.15, + "learning_rate": 1.9207171937281423e-05, + "loss": 0.8771, + "step": 799 + }, + { + "epoch": 0.15, + "learning_rate": 1.9204737234175178e-05, + "loss": 0.8718, + "step": 800 + }, + { + "epoch": 0.15, + "learning_rate": 1.9202298953216613e-05, + "loss": 0.8508, + "step": 801 + }, + { + "epoch": 0.15, + "learning_rate": 1.919985709535349e-05, + "loss": 0.8956, + "step": 802 + }, + { + "epoch": 0.15, + "learning_rate": 1.9197411661534945e-05, + "loss": 0.8416, + "step": 803 + }, + { + "epoch": 0.15, + "learning_rate": 1.9194962652711515e-05, + "loss": 0.8845, + "step": 804 + }, + { + "epoch": 0.15, + "learning_rate": 1.919251006983512e-05, + "loss": 0.828, + "step": 805 + }, + { + "epoch": 0.16, + "learning_rate": 1.919005391385907e-05, + "loss": 2.0, + "step": 806 + }, + { + "epoch": 0.16, + "learning_rate": 1.918759418573806e-05, + "loss": 0.8745, + "step": 807 + }, + { + "epoch": 0.16, + "learning_rate": 1.9185130886428188e-05, + "loss": 0.8803, + "step": 808 + }, + { + "epoch": 0.16, + "learning_rate": 1.918266401688693e-05, + "loss": 0.8094, + "step": 809 + }, + { + "epoch": 0.16, + "learning_rate": 1.9180193578073146e-05, + "loss": 0.8225, + "step": 810 + }, + { + "epoch": 0.16, + "learning_rate": 1.917771957094709e-05, + "loss": 0.8184, + "step": 811 + }, + { + "epoch": 0.16, + "learning_rate": 1.91752419964704e-05, + "loss": 0.8828, + "step": 812 + }, + { + "epoch": 0.16, + "learning_rate": 1.91727608556061e-05, + "loss": 0.8603, + "step": 813 + }, + { + "epoch": 0.16, + "learning_rate": 1.9170276149318606e-05, + "loss": 0.8326, + "step": 814 + }, + { + "epoch": 0.16, + "learning_rate": 1.916778787857371e-05, + "loss": 0.8389, + "step": 815 + }, + { + "epoch": 0.16, + "learning_rate": 1.9165296044338597e-05, + "loss": 0.8178, + "step": 816 + }, + { + "epoch": 0.16, + "learning_rate": 1.9162800647581837e-05, + "loss": 0.8665, + "step": 817 + }, + { + "epoch": 0.16, + "learning_rate": 1.9160301689273382e-05, + "loss": 0.8591, + "step": 818 + }, + { + "epoch": 0.16, + "learning_rate": 1.915779917038457e-05, + "loss": 0.897, + "step": 819 + }, + { + "epoch": 0.16, + "learning_rate": 1.915529309188812e-05, + "loss": 0.8462, + "step": 820 + }, + { + "epoch": 0.16, + "learning_rate": 1.9152783454758133e-05, + "loss": 0.8587, + "step": 821 + }, + { + "epoch": 0.16, + "learning_rate": 1.915027025997011e-05, + "loss": 0.89, + "step": 822 + }, + { + "epoch": 0.16, + "learning_rate": 1.9147753508500907e-05, + "loss": 1.9879, + "step": 823 + }, + { + "epoch": 0.16, + "learning_rate": 1.9145233201328786e-05, + "loss": 0.8877, + "step": 824 + }, + { + "epoch": 0.16, + "learning_rate": 1.914270933943338e-05, + "loss": 0.8262, + "step": 825 + }, + { + "epoch": 0.16, + "learning_rate": 1.9140181923795706e-05, + "loss": 0.8673, + "step": 826 + }, + { + "epoch": 0.16, + "learning_rate": 1.9137650955398163e-05, + "loss": 0.865, + "step": 827 + }, + { + "epoch": 0.16, + "learning_rate": 1.9135116435224535e-05, + "loss": 1.8647, + "step": 828 + }, + { + "epoch": 0.16, + "learning_rate": 1.9132578364259973e-05, + "loss": 0.8592, + "step": 829 + }, + { + "epoch": 0.16, + "learning_rate": 1.9130036743491023e-05, + "loss": 0.8648, + "step": 830 + }, + { + "epoch": 0.16, + "learning_rate": 1.9127491573905603e-05, + "loss": 0.8433, + "step": 831 + }, + { + "epoch": 0.16, + "learning_rate": 1.9124942856493013e-05, + "loss": 0.7873, + "step": 832 + }, + { + "epoch": 0.16, + "learning_rate": 1.912239059224393e-05, + "loss": 0.9177, + "step": 833 + }, + { + "epoch": 0.16, + "learning_rate": 1.9119834782150416e-05, + "loss": 0.8094, + "step": 834 + }, + { + "epoch": 0.16, + "learning_rate": 1.9117275427205904e-05, + "loss": 0.9025, + "step": 835 + }, + { + "epoch": 0.16, + "learning_rate": 1.9114712528405202e-05, + "loss": 0.8593, + "step": 836 + }, + { + "epoch": 0.16, + "learning_rate": 1.9112146086744504e-05, + "loss": 0.8279, + "step": 837 + }, + { + "epoch": 0.16, + "learning_rate": 1.910957610322138e-05, + "loss": 0.8588, + "step": 838 + }, + { + "epoch": 0.16, + "learning_rate": 1.9107002578834778e-05, + "loss": 0.8506, + "step": 839 + }, + { + "epoch": 0.16, + "learning_rate": 1.9104425514585005e-05, + "loss": 0.8724, + "step": 840 + }, + { + "epoch": 0.16, + "learning_rate": 1.910184491147377e-05, + "loss": 0.8339, + "step": 841 + }, + { + "epoch": 0.16, + "learning_rate": 1.9099260770504143e-05, + "loss": 0.858, + "step": 842 + }, + { + "epoch": 0.16, + "learning_rate": 1.9096673092680572e-05, + "loss": 0.8862, + "step": 843 + }, + { + "epoch": 0.16, + "learning_rate": 1.9094081879008873e-05, + "loss": 0.8468, + "step": 844 + }, + { + "epoch": 0.16, + "learning_rate": 1.909148713049625e-05, + "loss": 0.8562, + "step": 845 + }, + { + "epoch": 0.16, + "learning_rate": 1.908888884815127e-05, + "loss": 0.8522, + "step": 846 + }, + { + "epoch": 0.16, + "learning_rate": 1.9086287032983878e-05, + "loss": 0.8307, + "step": 847 + }, + { + "epoch": 0.16, + "learning_rate": 1.908368168600539e-05, + "loss": 0.8709, + "step": 848 + }, + { + "epoch": 0.16, + "learning_rate": 1.9081072808228497e-05, + "loss": 0.8176, + "step": 849 + }, + { + "epoch": 0.16, + "learning_rate": 1.9078460400667263e-05, + "loss": 0.829, + "step": 850 + }, + { + "epoch": 0.16, + "learning_rate": 1.9075844464337117e-05, + "loss": 0.8459, + "step": 851 + }, + { + "epoch": 0.16, + "learning_rate": 1.9073225000254876e-05, + "loss": 0.8469, + "step": 852 + }, + { + "epoch": 0.16, + "learning_rate": 1.9070602009438707e-05, + "loss": 0.8751, + "step": 853 + }, + { + "epoch": 0.16, + "learning_rate": 1.9067975492908167e-05, + "loss": 0.8625, + "step": 854 + }, + { + "epoch": 0.16, + "learning_rate": 1.9065345451684166e-05, + "loss": 0.8598, + "step": 855 + }, + { + "epoch": 0.16, + "learning_rate": 1.9062711886788997e-05, + "loss": 0.8253, + "step": 856 + }, + { + "epoch": 0.16, + "learning_rate": 1.9060074799246316e-05, + "loss": 0.9365, + "step": 857 + }, + { + "epoch": 0.17, + "learning_rate": 1.9057434190081154e-05, + "loss": 0.8732, + "step": 858 + }, + { + "epoch": 0.17, + "learning_rate": 1.9054790060319908e-05, + "loss": 0.8479, + "step": 859 + }, + { + "epoch": 0.17, + "learning_rate": 1.905214241099034e-05, + "loss": 0.8697, + "step": 860 + }, + { + "epoch": 0.17, + "learning_rate": 1.904949124312158e-05, + "loss": 0.8957, + "step": 861 + }, + { + "epoch": 0.17, + "learning_rate": 1.9046836557744135e-05, + "loss": 0.8531, + "step": 862 + }, + { + "epoch": 0.17, + "learning_rate": 1.904417835588987e-05, + "loss": 0.8828, + "step": 863 + }, + { + "epoch": 0.17, + "learning_rate": 1.9041516638592025e-05, + "loss": 0.8692, + "step": 864 + }, + { + "epoch": 0.17, + "learning_rate": 1.903885140688519e-05, + "loss": 0.8396, + "step": 865 + }, + { + "epoch": 0.17, + "learning_rate": 1.903618266180534e-05, + "loss": 0.852, + "step": 866 + }, + { + "epoch": 0.17, + "learning_rate": 1.9033510404389806e-05, + "loss": 0.8906, + "step": 867 + }, + { + "epoch": 0.17, + "learning_rate": 1.9030834635677285e-05, + "loss": 0.8855, + "step": 868 + }, + { + "epoch": 0.17, + "learning_rate": 1.9028155356707843e-05, + "loss": 0.8598, + "step": 869 + }, + { + "epoch": 0.17, + "learning_rate": 1.9025472568522906e-05, + "loss": 0.8597, + "step": 870 + }, + { + "epoch": 0.17, + "learning_rate": 1.902278627216526e-05, + "loss": 0.7999, + "step": 871 + }, + { + "epoch": 0.17, + "learning_rate": 1.902009646867907e-05, + "loss": 1.7423, + "step": 872 + }, + { + "epoch": 0.17, + "learning_rate": 1.9017403159109844e-05, + "loss": 0.866, + "step": 873 + }, + { + "epoch": 0.17, + "learning_rate": 1.9014706344504467e-05, + "loss": 0.8374, + "step": 874 + }, + { + "epoch": 0.17, + "learning_rate": 1.901200602591119e-05, + "loss": 0.8578, + "step": 875 + }, + { + "epoch": 0.17, + "learning_rate": 1.9009302204379604e-05, + "loss": 0.8213, + "step": 876 + }, + { + "epoch": 0.17, + "learning_rate": 1.900659488096068e-05, + "loss": 0.8102, + "step": 877 + }, + { + "epoch": 0.17, + "learning_rate": 1.9003884056706758e-05, + "loss": 0.8773, + "step": 878 + }, + { + "epoch": 0.17, + "learning_rate": 1.900116973267151e-05, + "loss": 0.837, + "step": 879 + }, + { + "epoch": 0.17, + "learning_rate": 1.899845190991e-05, + "loss": 0.9111, + "step": 880 + }, + { + "epoch": 0.17, + "learning_rate": 1.8995730589478628e-05, + "loss": 0.8565, + "step": 881 + }, + { + "epoch": 0.17, + "learning_rate": 1.8993005772435162e-05, + "loss": 0.8207, + "step": 882 + }, + { + "epoch": 0.17, + "learning_rate": 1.8990277459838734e-05, + "loss": 0.8645, + "step": 883 + }, + { + "epoch": 0.17, + "learning_rate": 1.898754565274983e-05, + "loss": 0.8795, + "step": 884 + }, + { + "epoch": 0.17, + "learning_rate": 1.8984810352230295e-05, + "loss": 0.8706, + "step": 885 + }, + { + "epoch": 0.17, + "learning_rate": 1.898207155934333e-05, + "loss": 0.8597, + "step": 886 + }, + { + "epoch": 0.17, + "learning_rate": 1.8979329275153492e-05, + "loss": 0.8078, + "step": 887 + }, + { + "epoch": 0.17, + "learning_rate": 1.8976583500726706e-05, + "loss": 0.8416, + "step": 888 + }, + { + "epoch": 0.17, + "learning_rate": 1.897383423713024e-05, + "loss": 0.8651, + "step": 889 + }, + { + "epoch": 0.17, + "learning_rate": 1.897108148543273e-05, + "loss": 0.8698, + "step": 890 + }, + { + "epoch": 0.17, + "learning_rate": 1.896832524670415e-05, + "loss": 0.8997, + "step": 891 + }, + { + "epoch": 0.17, + "learning_rate": 1.8965565522015856e-05, + "loss": 0.8408, + "step": 892 + }, + { + "epoch": 0.17, + "learning_rate": 1.8962802312440533e-05, + "loss": 0.839, + "step": 893 + }, + { + "epoch": 0.17, + "learning_rate": 1.896003561905224e-05, + "loss": 1.7908, + "step": 894 + }, + { + "epoch": 0.17, + "learning_rate": 1.8957265442926376e-05, + "loss": 0.8504, + "step": 895 + }, + { + "epoch": 0.17, + "learning_rate": 1.8954491785139703e-05, + "loss": 0.8284, + "step": 896 + }, + { + "epoch": 0.17, + "learning_rate": 1.8951714646770332e-05, + "loss": 0.8635, + "step": 897 + }, + { + "epoch": 0.17, + "learning_rate": 1.8948934028897725e-05, + "loss": 0.8793, + "step": 898 + }, + { + "epoch": 0.17, + "learning_rate": 1.8946149932602708e-05, + "loss": 0.9216, + "step": 899 + }, + { + "epoch": 0.17, + "learning_rate": 1.8943362358967442e-05, + "loss": 0.8784, + "step": 900 + }, + { + "epoch": 0.17, + "learning_rate": 1.8940571309075445e-05, + "loss": 0.8246, + "step": 901 + }, + { + "epoch": 0.17, + "learning_rate": 1.8937776784011603e-05, + "loss": 0.7751, + "step": 902 + }, + { + "epoch": 0.17, + "learning_rate": 1.893497878486213e-05, + "loss": 0.8965, + "step": 903 + }, + { + "epoch": 0.17, + "learning_rate": 1.8932177312714595e-05, + "loss": 0.8838, + "step": 904 + }, + { + "epoch": 0.17, + "learning_rate": 1.8929372368657933e-05, + "loss": 0.8169, + "step": 905 + }, + { + "epoch": 0.17, + "learning_rate": 1.8926563953782407e-05, + "loss": 0.833, + "step": 906 + }, + { + "epoch": 0.17, + "learning_rate": 1.8923752069179646e-05, + "loss": 0.8662, + "step": 907 + }, + { + "epoch": 0.17, + "learning_rate": 1.8920936715942614e-05, + "loss": 0.8803, + "step": 908 + }, + { + "epoch": 0.17, + "learning_rate": 1.8918117895165636e-05, + "loss": 0.9285, + "step": 909 + }, + { + "epoch": 0.18, + "learning_rate": 1.8915295607944374e-05, + "loss": 0.8695, + "step": 910 + }, + { + "epoch": 0.18, + "learning_rate": 1.8912469855375847e-05, + "loss": 0.8262, + "step": 911 + }, + { + "epoch": 0.18, + "learning_rate": 1.8909640638558415e-05, + "loss": 0.8702, + "step": 912 + }, + { + "epoch": 0.18, + "learning_rate": 1.890680795859178e-05, + "loss": 0.8553, + "step": 913 + }, + { + "epoch": 0.18, + "learning_rate": 1.8903971816577e-05, + "loss": 0.7744, + "step": 914 + }, + { + "epoch": 0.18, + "learning_rate": 1.8901132213616477e-05, + "loss": 0.8519, + "step": 915 + }, + { + "epoch": 0.18, + "learning_rate": 1.8898289150813954e-05, + "loss": 0.8275, + "step": 916 + }, + { + "epoch": 0.18, + "learning_rate": 1.8895442629274516e-05, + "loss": 0.8741, + "step": 917 + }, + { + "epoch": 0.18, + "learning_rate": 1.88925926501046e-05, + "loss": 0.7955, + "step": 918 + }, + { + "epoch": 0.18, + "learning_rate": 1.8889739214411987e-05, + "loss": 0.8977, + "step": 919 + }, + { + "epoch": 0.18, + "learning_rate": 1.8886882323305796e-05, + "loss": 0.8997, + "step": 920 + }, + { + "epoch": 0.18, + "learning_rate": 1.8884021977896493e-05, + "loss": 0.809, + "step": 921 + }, + { + "epoch": 0.18, + "learning_rate": 1.888115817929588e-05, + "loss": 0.8396, + "step": 922 + }, + { + "epoch": 0.18, + "learning_rate": 1.887829092861711e-05, + "loss": 0.8637, + "step": 923 + }, + { + "epoch": 0.18, + "learning_rate": 1.8875420226974676e-05, + "loss": 0.9193, + "step": 924 + }, + { + "epoch": 0.18, + "learning_rate": 1.887254607548441e-05, + "loss": 0.8592, + "step": 925 + }, + { + "epoch": 0.18, + "learning_rate": 1.8869668475263484e-05, + "loss": 0.8746, + "step": 926 + }, + { + "epoch": 0.18, + "learning_rate": 1.886678742743041e-05, + "loss": 0.854, + "step": 927 + }, + { + "epoch": 0.18, + "learning_rate": 1.886390293310505e-05, + "loss": 0.9089, + "step": 928 + }, + { + "epoch": 0.18, + "learning_rate": 1.886101499340859e-05, + "loss": 0.9015, + "step": 929 + }, + { + "epoch": 0.18, + "learning_rate": 1.8858123609463565e-05, + "loss": 0.8472, + "step": 930 + }, + { + "epoch": 0.18, + "learning_rate": 1.885522878239385e-05, + "loss": 0.8878, + "step": 931 + }, + { + "epoch": 0.18, + "learning_rate": 1.885233051332465e-05, + "loss": 0.8702, + "step": 932 + }, + { + "epoch": 0.18, + "learning_rate": 1.884942880338252e-05, + "loss": 0.8413, + "step": 933 + }, + { + "epoch": 0.18, + "learning_rate": 1.884652365369534e-05, + "loss": 1.9238, + "step": 934 + }, + { + "epoch": 0.18, + "learning_rate": 1.884361506539233e-05, + "loss": 0.8753, + "step": 935 + }, + { + "epoch": 0.18, + "learning_rate": 1.8840703039604058e-05, + "loss": 0.8783, + "step": 936 + }, + { + "epoch": 0.18, + "learning_rate": 1.883778757746241e-05, + "loss": 0.8666, + "step": 937 + }, + { + "epoch": 0.18, + "learning_rate": 1.8834868680100623e-05, + "loss": 0.8095, + "step": 938 + }, + { + "epoch": 0.18, + "learning_rate": 1.8831946348653263e-05, + "loss": 0.867, + "step": 939 + }, + { + "epoch": 0.18, + "learning_rate": 1.882902058425623e-05, + "loss": 0.8048, + "step": 940 + }, + { + "epoch": 0.18, + "learning_rate": 1.8826091388046753e-05, + "loss": 0.8042, + "step": 941 + }, + { + "epoch": 0.18, + "learning_rate": 1.8823158761163415e-05, + "loss": 0.8386, + "step": 942 + }, + { + "epoch": 0.18, + "learning_rate": 1.8820222704746106e-05, + "loss": 1.8891, + "step": 943 + }, + { + "epoch": 0.18, + "learning_rate": 1.8817283219936066e-05, + "loss": 0.8651, + "step": 944 + }, + { + "epoch": 0.18, + "learning_rate": 1.8814340307875866e-05, + "loss": 0.9014, + "step": 945 + }, + { + "epoch": 0.18, + "learning_rate": 1.8811393969709405e-05, + "loss": 0.9171, + "step": 946 + }, + { + "epoch": 0.18, + "learning_rate": 1.8808444206581918e-05, + "loss": 0.8447, + "step": 947 + }, + { + "epoch": 0.18, + "learning_rate": 1.880549101963996e-05, + "loss": 0.9168, + "step": 948 + }, + { + "epoch": 0.18, + "learning_rate": 1.8802534410031436e-05, + "loss": 0.8727, + "step": 949 + }, + { + "epoch": 0.18, + "learning_rate": 1.8799574378905567e-05, + "loss": 0.817, + "step": 950 + }, + { + "epoch": 0.18, + "learning_rate": 1.87966109274129e-05, + "loss": 0.8332, + "step": 951 + }, + { + "epoch": 0.18, + "learning_rate": 1.879364405670533e-05, + "loss": 0.8275, + "step": 952 + }, + { + "epoch": 0.18, + "learning_rate": 1.8790673767936068e-05, + "loss": 0.9103, + "step": 953 + }, + { + "epoch": 0.18, + "learning_rate": 1.8787700062259652e-05, + "loss": 0.8516, + "step": 954 + }, + { + "epoch": 0.18, + "learning_rate": 1.8784722940831956e-05, + "loss": 0.8814, + "step": 955 + }, + { + "epoch": 0.18, + "learning_rate": 1.8781742404810176e-05, + "loss": 0.8656, + "step": 956 + }, + { + "epoch": 0.18, + "learning_rate": 1.8778758455352836e-05, + "loss": 0.8612, + "step": 957 + }, + { + "epoch": 0.18, + "learning_rate": 1.877577109361979e-05, + "loss": 0.839, + "step": 958 + }, + { + "epoch": 0.18, + "learning_rate": 1.8772780320772214e-05, + "loss": 0.8666, + "step": 959 + }, + { + "epoch": 0.18, + "learning_rate": 1.876978613797261e-05, + "loss": 0.7871, + "step": 960 + }, + { + "epoch": 0.18, + "learning_rate": 1.8766788546384815e-05, + "loss": 0.8567, + "step": 961 + }, + { + "epoch": 0.19, + "learning_rate": 1.8763787547173976e-05, + "loss": 0.8126, + "step": 962 + }, + { + "epoch": 0.19, + "learning_rate": 1.8760783141506573e-05, + "loss": 0.9003, + "step": 963 + }, + { + "epoch": 0.19, + "learning_rate": 1.8757775330550413e-05, + "loss": 0.8303, + "step": 964 + }, + { + "epoch": 0.19, + "learning_rate": 1.8754764115474616e-05, + "loss": 0.8538, + "step": 965 + }, + { + "epoch": 0.19, + "learning_rate": 1.8751749497449642e-05, + "loss": 0.8058, + "step": 966 + }, + { + "epoch": 0.19, + "learning_rate": 1.8748731477647253e-05, + "loss": 0.8297, + "step": 967 + }, + { + "epoch": 0.19, + "learning_rate": 1.874571005724055e-05, + "loss": 0.8169, + "step": 968 + }, + { + "epoch": 0.19, + "learning_rate": 1.8742685237403946e-05, + "loss": 0.8926, + "step": 969 + }, + { + "epoch": 0.19, + "learning_rate": 1.8739657019313183e-05, + "loss": 0.8506, + "step": 970 + }, + { + "epoch": 0.19, + "learning_rate": 1.8736625404145316e-05, + "loss": 0.8649, + "step": 971 + }, + { + "epoch": 0.19, + "learning_rate": 1.8733590393078723e-05, + "loss": 0.8535, + "step": 972 + }, + { + "epoch": 0.19, + "learning_rate": 1.8730551987293112e-05, + "loss": 0.8369, + "step": 973 + }, + { + "epoch": 0.19, + "learning_rate": 1.872751018796949e-05, + "loss": 0.8594, + "step": 974 + }, + { + "epoch": 0.19, + "learning_rate": 1.8724464996290203e-05, + "loss": 0.8346, + "step": 975 + }, + { + "epoch": 0.19, + "learning_rate": 1.8721416413438906e-05, + "loss": 0.8633, + "step": 976 + }, + { + "epoch": 0.19, + "learning_rate": 1.871836444060057e-05, + "loss": 0.8637, + "step": 977 + }, + { + "epoch": 0.19, + "learning_rate": 1.8715309078961494e-05, + "loss": 0.8714, + "step": 978 + }, + { + "epoch": 0.19, + "learning_rate": 1.871225032970928e-05, + "loss": 0.9083, + "step": 979 + }, + { + "epoch": 0.19, + "learning_rate": 1.8709188194032854e-05, + "loss": 0.8289, + "step": 980 + }, + { + "epoch": 0.19, + "learning_rate": 1.8706122673122464e-05, + "loss": 0.8584, + "step": 981 + }, + { + "epoch": 0.19, + "learning_rate": 1.870305376816967e-05, + "loss": 0.8928, + "step": 982 + }, + { + "epoch": 0.19, + "learning_rate": 1.8699981480367335e-05, + "loss": 0.8339, + "step": 983 + }, + { + "epoch": 0.19, + "learning_rate": 1.869690581090966e-05, + "loss": 0.8881, + "step": 984 + }, + { + "epoch": 0.19, + "learning_rate": 1.869382676099214e-05, + "loss": 1.7877, + "step": 985 + }, + { + "epoch": 0.19, + "learning_rate": 1.8690744331811592e-05, + "loss": 0.872, + "step": 986 + }, + { + "epoch": 0.19, + "learning_rate": 1.868765852456615e-05, + "loss": 0.7828, + "step": 987 + }, + { + "epoch": 0.19, + "learning_rate": 1.8684569340455256e-05, + "loss": 0.9042, + "step": 988 + }, + { + "epoch": 0.19, + "learning_rate": 1.8681476780679668e-05, + "loss": 0.8865, + "step": 989 + }, + { + "epoch": 0.19, + "learning_rate": 1.8678380846441457e-05, + "loss": 0.8155, + "step": 990 + }, + { + "epoch": 0.19, + "learning_rate": 1.867528153894399e-05, + "loss": 0.8594, + "step": 991 + }, + { + "epoch": 0.19, + "learning_rate": 1.8672178859391968e-05, + "loss": 0.7884, + "step": 992 + }, + { + "epoch": 0.19, + "learning_rate": 1.8669072808991394e-05, + "loss": 1.8222, + "step": 993 + }, + { + "epoch": 0.19, + "learning_rate": 1.8665963388949577e-05, + "loss": 1.8262, + "step": 994 + }, + { + "epoch": 0.19, + "learning_rate": 1.8662850600475138e-05, + "loss": 0.8107, + "step": 995 + }, + { + "epoch": 0.19, + "learning_rate": 1.8659734444778014e-05, + "loss": 0.9152, + "step": 996 + }, + { + "epoch": 0.19, + "learning_rate": 1.8656614923069433e-05, + "loss": 0.8458, + "step": 997 + }, + { + "epoch": 0.19, + "learning_rate": 1.8653492036561952e-05, + "loss": 0.8629, + "step": 998 + }, + { + "epoch": 0.19, + "learning_rate": 1.8650365786469425e-05, + "loss": 0.898, + "step": 999 + }, + { + "epoch": 0.19, + "learning_rate": 1.864723617400702e-05, + "loss": 0.8968, + "step": 1000 + }, + { + "epoch": 0.19, + "learning_rate": 1.86441032003912e-05, + "loss": 0.8836, + "step": 1001 + }, + { + "epoch": 0.19, + "learning_rate": 1.8640966866839746e-05, + "loss": 0.8187, + "step": 1002 + }, + { + "epoch": 0.19, + "learning_rate": 1.863782717457174e-05, + "loss": 1.8772, + "step": 1003 + }, + { + "epoch": 0.19, + "learning_rate": 1.863468412480757e-05, + "loss": 0.8107, + "step": 1004 + }, + { + "epoch": 0.19, + "learning_rate": 1.8631537718768927e-05, + "loss": 0.9199, + "step": 1005 + }, + { + "epoch": 0.19, + "learning_rate": 1.862838795767882e-05, + "loss": 0.8908, + "step": 1006 + }, + { + "epoch": 0.19, + "learning_rate": 1.862523484276154e-05, + "loss": 0.8966, + "step": 1007 + }, + { + "epoch": 0.19, + "learning_rate": 1.8622078375242696e-05, + "loss": 0.8979, + "step": 1008 + }, + { + "epoch": 0.19, + "learning_rate": 1.86189185563492e-05, + "loss": 0.8301, + "step": 1009 + }, + { + "epoch": 0.19, + "learning_rate": 1.8615755387309257e-05, + "loss": 0.838, + "step": 1010 + }, + { + "epoch": 0.19, + "learning_rate": 1.8612588869352387e-05, + "loss": 0.8735, + "step": 1011 + }, + { + "epoch": 0.19, + "learning_rate": 1.86094190037094e-05, + "loss": 0.8798, + "step": 1012 + }, + { + "epoch": 0.19, + "learning_rate": 1.860624579161242e-05, + "loss": 0.9072, + "step": 1013 + }, + { + "epoch": 0.2, + "learning_rate": 1.860306923429486e-05, + "loss": 0.837, + "step": 1014 + }, + { + "epoch": 0.2, + "learning_rate": 1.8599889332991438e-05, + "loss": 0.9098, + "step": 1015 + }, + { + "epoch": 0.2, + "learning_rate": 1.8596706088938172e-05, + "loss": 0.8586, + "step": 1016 + }, + { + "epoch": 0.2, + "learning_rate": 1.8593519503372378e-05, + "loss": 0.8595, + "step": 1017 + }, + { + "epoch": 0.2, + "learning_rate": 1.8590329577532674e-05, + "loss": 0.8073, + "step": 1018 + }, + { + "epoch": 0.2, + "learning_rate": 1.8587136312658972e-05, + "loss": 0.802, + "step": 1019 + }, + { + "epoch": 0.2, + "learning_rate": 1.8583939709992486e-05, + "loss": 0.8625, + "step": 1020 + }, + { + "epoch": 0.2, + "learning_rate": 1.8580739770775723e-05, + "loss": 0.8449, + "step": 1021 + }, + { + "epoch": 0.2, + "learning_rate": 1.8577536496252492e-05, + "loss": 0.8828, + "step": 1022 + }, + { + "epoch": 0.2, + "learning_rate": 1.857432988766789e-05, + "loss": 0.8971, + "step": 1023 + }, + { + "epoch": 0.2, + "learning_rate": 1.8571119946268327e-05, + "loss": 0.8234, + "step": 1024 + }, + { + "epoch": 0.2, + "learning_rate": 1.8567906673301484e-05, + "loss": 0.8028, + "step": 1025 + }, + { + "epoch": 0.2, + "learning_rate": 1.8564690070016358e-05, + "loss": 0.8711, + "step": 1026 + }, + { + "epoch": 0.2, + "learning_rate": 1.856147013766323e-05, + "loss": 0.8088, + "step": 1027 + }, + { + "epoch": 0.2, + "learning_rate": 1.855824687749368e-05, + "loss": 0.9014, + "step": 1028 + }, + { + "epoch": 0.2, + "learning_rate": 1.8555020290760572e-05, + "loss": 0.8771, + "step": 1029 + }, + { + "epoch": 0.2, + "learning_rate": 1.855179037871808e-05, + "loss": 0.8165, + "step": 1030 + }, + { + "epoch": 0.2, + "learning_rate": 1.8548557142621656e-05, + "loss": 0.8953, + "step": 1031 + }, + { + "epoch": 0.2, + "learning_rate": 1.8545320583728044e-05, + "loss": 0.8323, + "step": 1032 + }, + { + "epoch": 0.2, + "learning_rate": 1.8542080703295293e-05, + "loss": 0.9192, + "step": 1033 + }, + { + "epoch": 0.2, + "learning_rate": 1.8538837502582727e-05, + "loss": 0.8773, + "step": 1034 + }, + { + "epoch": 0.2, + "learning_rate": 1.8535590982850972e-05, + "loss": 0.8896, + "step": 1035 + }, + { + "epoch": 0.2, + "learning_rate": 1.853234114536194e-05, + "loss": 0.8545, + "step": 1036 + }, + { + "epoch": 0.2, + "learning_rate": 1.852908799137883e-05, + "loss": 0.8561, + "step": 1037 + }, + { + "epoch": 0.2, + "learning_rate": 1.8525831522166135e-05, + "loss": 0.8434, + "step": 1038 + }, + { + "epoch": 0.2, + "learning_rate": 1.852257173898963e-05, + "loss": 0.8554, + "step": 1039 + }, + { + "epoch": 0.2, + "learning_rate": 1.851930864311639e-05, + "loss": 0.7747, + "step": 1040 + }, + { + "epoch": 0.2, + "learning_rate": 1.8516042235814767e-05, + "loss": 0.9023, + "step": 1041 + }, + { + "epoch": 0.2, + "learning_rate": 1.85127725183544e-05, + "loss": 0.8577, + "step": 1042 + }, + { + "epoch": 0.2, + "learning_rate": 1.8509499492006216e-05, + "loss": 0.8616, + "step": 1043 + }, + { + "epoch": 0.2, + "learning_rate": 1.8506223158042442e-05, + "loss": 0.8272, + "step": 1044 + }, + { + "epoch": 0.2, + "learning_rate": 1.8502943517736566e-05, + "loss": 0.8076, + "step": 1045 + }, + { + "epoch": 0.2, + "learning_rate": 1.8499660572363377e-05, + "loss": 0.7438, + "step": 1046 + }, + { + "epoch": 0.2, + "learning_rate": 1.849637432319895e-05, + "loss": 0.8486, + "step": 1047 + }, + { + "epoch": 0.2, + "learning_rate": 1.8493084771520635e-05, + "loss": 0.8493, + "step": 1048 + }, + { + "epoch": 0.2, + "learning_rate": 1.8489791918607075e-05, + "loss": 0.8088, + "step": 1049 + }, + { + "epoch": 0.2, + "learning_rate": 1.8486495765738187e-05, + "loss": 0.8345, + "step": 1050 + }, + { + "epoch": 0.2, + "learning_rate": 1.8483196314195174e-05, + "loss": 0.9013, + "step": 1051 + }, + { + "epoch": 0.2, + "learning_rate": 1.8479893565260525e-05, + "loss": 0.797, + "step": 1052 + }, + { + "epoch": 0.2, + "learning_rate": 1.8476587520218013e-05, + "loss": 0.8801, + "step": 1053 + }, + { + "epoch": 0.2, + "learning_rate": 1.847327818035268e-05, + "loss": 0.8436, + "step": 1054 + }, + { + "epoch": 0.2, + "learning_rate": 1.846996554695086e-05, + "loss": 0.8206, + "step": 1055 + }, + { + "epoch": 0.2, + "learning_rate": 1.846664962130016e-05, + "loss": 0.8285, + "step": 1056 + }, + { + "epoch": 0.2, + "learning_rate": 1.846333040468947e-05, + "loss": 0.8749, + "step": 1057 + }, + { + "epoch": 0.2, + "learning_rate": 1.846000789840896e-05, + "loss": 0.9032, + "step": 1058 + }, + { + "epoch": 0.2, + "learning_rate": 1.845668210375008e-05, + "loss": 0.91, + "step": 1059 + }, + { + "epoch": 0.2, + "learning_rate": 1.8453353022005557e-05, + "loss": 1.8954, + "step": 1060 + }, + { + "epoch": 0.2, + "learning_rate": 1.8450020654469388e-05, + "loss": 0.834, + "step": 1061 + }, + { + "epoch": 0.2, + "learning_rate": 1.844668500243686e-05, + "loss": 0.8378, + "step": 1062 + }, + { + "epoch": 0.2, + "learning_rate": 1.8443346067204525e-05, + "loss": 0.8826, + "step": 1063 + }, + { + "epoch": 0.2, + "learning_rate": 1.8440003850070222e-05, + "loss": 0.8121, + "step": 1064 + }, + { + "epoch": 0.21, + "learning_rate": 1.8436658352333056e-05, + "loss": 0.8299, + "step": 1065 + }, + { + "epoch": 0.21, + "learning_rate": 1.8433309575293414e-05, + "loss": 0.8593, + "step": 1066 + }, + { + "epoch": 0.21, + "learning_rate": 1.8429957520252953e-05, + "loss": 0.8542, + "step": 1067 + }, + { + "epoch": 0.21, + "learning_rate": 1.842660218851461e-05, + "loss": 0.7941, + "step": 1068 + }, + { + "epoch": 0.21, + "learning_rate": 1.842324358138259e-05, + "loss": 0.825, + "step": 1069 + }, + { + "epoch": 0.21, + "learning_rate": 1.8419881700162365e-05, + "loss": 0.8745, + "step": 1070 + }, + { + "epoch": 0.21, + "learning_rate": 1.84165165461607e-05, + "loss": 0.8386, + "step": 1071 + }, + { + "epoch": 0.21, + "learning_rate": 1.8413148120685616e-05, + "loss": 0.9064, + "step": 1072 + }, + { + "epoch": 0.21, + "learning_rate": 1.8409776425046404e-05, + "loss": 0.868, + "step": 1073 + }, + { + "epoch": 0.21, + "learning_rate": 1.840640146055364e-05, + "loss": 0.8705, + "step": 1074 + }, + { + "epoch": 0.21, + "learning_rate": 1.8403023228519155e-05, + "loss": 0.8762, + "step": 1075 + }, + { + "epoch": 0.21, + "learning_rate": 1.8399641730256057e-05, + "loss": 0.8368, + "step": 1076 + }, + { + "epoch": 0.21, + "learning_rate": 1.839625696707873e-05, + "loss": 0.8745, + "step": 1077 + }, + { + "epoch": 0.21, + "learning_rate": 1.8392868940302815e-05, + "loss": 0.8563, + "step": 1078 + }, + { + "epoch": 0.21, + "learning_rate": 1.838947765124523e-05, + "loss": 0.8857, + "step": 1079 + }, + { + "epoch": 0.21, + "learning_rate": 1.8386083101224158e-05, + "loss": 0.7878, + "step": 1080 + }, + { + "epoch": 0.21, + "learning_rate": 1.838268529155905e-05, + "loss": 0.8264, + "step": 1081 + }, + { + "epoch": 0.21, + "learning_rate": 1.8379284223570624e-05, + "loss": 0.8511, + "step": 1082 + }, + { + "epoch": 0.21, + "learning_rate": 1.8375879898580862e-05, + "loss": 0.837, + "step": 1083 + }, + { + "epoch": 0.21, + "learning_rate": 1.8372472317913018e-05, + "loss": 0.8903, + "step": 1084 + }, + { + "epoch": 0.21, + "learning_rate": 1.8369061482891606e-05, + "loss": 0.8835, + "step": 1085 + }, + { + "epoch": 0.21, + "learning_rate": 1.8365647394842404e-05, + "loss": 0.8752, + "step": 1086 + }, + { + "epoch": 0.21, + "learning_rate": 1.8362230055092463e-05, + "loss": 0.7988, + "step": 1087 + }, + { + "epoch": 0.21, + "learning_rate": 1.835880946497009e-05, + "loss": 0.9097, + "step": 1088 + }, + { + "epoch": 0.21, + "learning_rate": 1.8355385625804854e-05, + "loss": 0.7838, + "step": 1089 + }, + { + "epoch": 0.21, + "learning_rate": 1.8351958538927598e-05, + "loss": 0.8854, + "step": 1090 + }, + { + "epoch": 0.21, + "learning_rate": 1.834852820567041e-05, + "loss": 0.8473, + "step": 1091 + }, + { + "epoch": 0.21, + "learning_rate": 1.8345094627366657e-05, + "loss": 0.871, + "step": 1092 + }, + { + "epoch": 0.21, + "learning_rate": 1.8341657805350957e-05, + "loss": 0.8566, + "step": 1093 + }, + { + "epoch": 0.21, + "learning_rate": 1.8338217740959197e-05, + "loss": 0.8475, + "step": 1094 + }, + { + "epoch": 0.21, + "learning_rate": 1.8334774435528514e-05, + "loss": 0.8956, + "step": 1095 + }, + { + "epoch": 0.21, + "learning_rate": 1.833132789039731e-05, + "loss": 0.8986, + "step": 1096 + }, + { + "epoch": 0.21, + "learning_rate": 1.8327878106905242e-05, + "loss": 0.8859, + "step": 1097 + }, + { + "epoch": 0.21, + "learning_rate": 1.8324425086393243e-05, + "loss": 0.8271, + "step": 1098 + }, + { + "epoch": 0.21, + "learning_rate": 1.8320968830203482e-05, + "loss": 0.8638, + "step": 1099 + }, + { + "epoch": 0.21, + "learning_rate": 1.8317509339679392e-05, + "loss": 0.8239, + "step": 1100 + }, + { + "epoch": 0.21, + "learning_rate": 1.8314046616165675e-05, + "loss": 0.8214, + "step": 1101 + }, + { + "epoch": 0.21, + "learning_rate": 1.8310580661008272e-05, + "loss": 0.8217, + "step": 1102 + }, + { + "epoch": 0.21, + "learning_rate": 1.8307111475554396e-05, + "loss": 0.8505, + "step": 1103 + }, + { + "epoch": 0.21, + "learning_rate": 1.83036390611525e-05, + "loss": 0.8585, + "step": 1104 + }, + { + "epoch": 0.21, + "learning_rate": 1.8300163419152316e-05, + "loss": 0.8566, + "step": 1105 + }, + { + "epoch": 0.21, + "learning_rate": 1.8296684550904794e-05, + "loss": 0.8324, + "step": 1106 + }, + { + "epoch": 0.21, + "learning_rate": 1.8293202457762177e-05, + "loss": 0.8306, + "step": 1107 + }, + { + "epoch": 0.21, + "learning_rate": 1.828971714107793e-05, + "loss": 0.8884, + "step": 1108 + }, + { + "epoch": 0.21, + "learning_rate": 1.82862286022068e-05, + "loss": 0.8544, + "step": 1109 + }, + { + "epoch": 0.21, + "learning_rate": 1.828273684250476e-05, + "loss": 0.8451, + "step": 1110 + }, + { + "epoch": 0.21, + "learning_rate": 1.8279241863329043e-05, + "loss": 0.8479, + "step": 1111 + }, + { + "epoch": 0.21, + "learning_rate": 1.8275743666038144e-05, + "loss": 0.9265, + "step": 1112 + }, + { + "epoch": 0.21, + "learning_rate": 1.82722422519918e-05, + "loss": 0.8745, + "step": 1113 + }, + { + "epoch": 0.21, + "learning_rate": 1.8268737622550996e-05, + "loss": 0.8622, + "step": 1114 + }, + { + "epoch": 0.21, + "learning_rate": 1.8265229779077976e-05, + "loss": 0.8766, + "step": 1115 + }, + { + "epoch": 0.21, + "learning_rate": 1.8261718722936225e-05, + "loss": 0.9092, + "step": 1116 + }, + { + "epoch": 0.22, + "learning_rate": 1.8258204455490475e-05, + "loss": 0.8282, + "step": 1117 + }, + { + "epoch": 0.22, + "learning_rate": 1.8254686978106717e-05, + "loss": 0.8842, + "step": 1118 + }, + { + "epoch": 0.22, + "learning_rate": 1.825116629215218e-05, + "loss": 0.8078, + "step": 1119 + }, + { + "epoch": 0.22, + "learning_rate": 1.8247642398995347e-05, + "loss": 0.8122, + "step": 1120 + }, + { + "epoch": 0.22, + "learning_rate": 1.824411530000594e-05, + "loss": 0.8708, + "step": 1121 + }, + { + "epoch": 0.22, + "learning_rate": 1.8240584996554932e-05, + "loss": 0.8435, + "step": 1122 + }, + { + "epoch": 0.22, + "learning_rate": 1.8237051490014545e-05, + "loss": 0.86, + "step": 1123 + }, + { + "epoch": 0.22, + "learning_rate": 1.8233514781758233e-05, + "loss": 0.901, + "step": 1124 + }, + { + "epoch": 0.22, + "learning_rate": 1.822997487316071e-05, + "loss": 1.8032, + "step": 1125 + }, + { + "epoch": 0.22, + "learning_rate": 1.822643176559793e-05, + "loss": 0.8724, + "step": 1126 + }, + { + "epoch": 0.22, + "learning_rate": 1.8222885460447083e-05, + "loss": 0.8357, + "step": 1127 + }, + { + "epoch": 0.22, + "learning_rate": 1.8219335959086606e-05, + "loss": 0.8654, + "step": 1128 + }, + { + "epoch": 0.22, + "learning_rate": 1.821578326289618e-05, + "loss": 0.852, + "step": 1129 + }, + { + "epoch": 0.22, + "learning_rate": 1.821222737325673e-05, + "loss": 0.8593, + "step": 1130 + }, + { + "epoch": 0.22, + "learning_rate": 1.8208668291550414e-05, + "loss": 0.9151, + "step": 1131 + }, + { + "epoch": 0.22, + "learning_rate": 1.820510601916064e-05, + "loss": 0.8508, + "step": 1132 + }, + { + "epoch": 0.22, + "learning_rate": 1.820154055747205e-05, + "loss": 0.8512, + "step": 1133 + }, + { + "epoch": 0.22, + "learning_rate": 1.8197971907870528e-05, + "loss": 0.8896, + "step": 1134 + }, + { + "epoch": 0.22, + "learning_rate": 1.8194400071743196e-05, + "loss": 0.8246, + "step": 1135 + }, + { + "epoch": 0.22, + "learning_rate": 1.8190825050478414e-05, + "loss": 0.9053, + "step": 1136 + }, + { + "epoch": 0.22, + "learning_rate": 1.8187246845465787e-05, + "loss": 0.8408, + "step": 1137 + }, + { + "epoch": 0.22, + "learning_rate": 1.8183665458096147e-05, + "loss": 0.7969, + "step": 1138 + }, + { + "epoch": 0.22, + "learning_rate": 1.8180080889761573e-05, + "loss": 0.8399, + "step": 1139 + }, + { + "epoch": 0.22, + "learning_rate": 1.8176493141855368e-05, + "loss": 0.8567, + "step": 1140 + }, + { + "epoch": 0.22, + "learning_rate": 1.8172902215772084e-05, + "loss": 0.8328, + "step": 1141 + }, + { + "epoch": 0.22, + "learning_rate": 1.81693081129075e-05, + "loss": 0.8845, + "step": 1142 + }, + { + "epoch": 0.22, + "learning_rate": 1.8165710834658635e-05, + "loss": 0.8854, + "step": 1143 + }, + { + "epoch": 0.22, + "learning_rate": 1.8162110382423738e-05, + "loss": 0.881, + "step": 1144 + }, + { + "epoch": 0.22, + "learning_rate": 1.8158506757602296e-05, + "loss": 0.8746, + "step": 1145 + }, + { + "epoch": 0.22, + "learning_rate": 1.815489996159502e-05, + "loss": 0.8301, + "step": 1146 + }, + { + "epoch": 0.22, + "learning_rate": 1.8151289995803866e-05, + "loss": 0.7774, + "step": 1147 + }, + { + "epoch": 0.22, + "learning_rate": 1.8147676861632014e-05, + "loss": 1.8419, + "step": 1148 + }, + { + "epoch": 0.22, + "learning_rate": 1.8144060560483878e-05, + "loss": 0.8321, + "step": 1149 + }, + { + "epoch": 0.22, + "learning_rate": 1.8140441093765103e-05, + "loss": 0.876, + "step": 1150 + }, + { + "epoch": 0.22, + "learning_rate": 1.813681846288257e-05, + "loss": 0.8403, + "step": 1151 + }, + { + "epoch": 0.22, + "learning_rate": 1.8133192669244373e-05, + "loss": 0.7902, + "step": 1152 + }, + { + "epoch": 0.22, + "learning_rate": 1.8129563714259854e-05, + "loss": 0.864, + "step": 1153 + }, + { + "epoch": 0.22, + "learning_rate": 1.8125931599339575e-05, + "loss": 0.7606, + "step": 1154 + }, + { + "epoch": 0.22, + "learning_rate": 1.8122296325895327e-05, + "loss": 0.8309, + "step": 1155 + }, + { + "epoch": 0.22, + "learning_rate": 1.811865789534013e-05, + "loss": 0.788, + "step": 1156 + }, + { + "epoch": 0.22, + "learning_rate": 1.811501630908823e-05, + "loss": 0.8859, + "step": 1157 + }, + { + "epoch": 0.22, + "learning_rate": 1.8111371568555102e-05, + "loss": 0.8283, + "step": 1158 + }, + { + "epoch": 0.22, + "learning_rate": 1.8107723675157442e-05, + "loss": 0.8749, + "step": 1159 + }, + { + "epoch": 0.22, + "learning_rate": 1.8104072630313176e-05, + "loss": 0.776, + "step": 1160 + }, + { + "epoch": 0.22, + "learning_rate": 1.8100418435441454e-05, + "loss": 0.8932, + "step": 1161 + }, + { + "epoch": 0.22, + "learning_rate": 1.809676109196265e-05, + "loss": 0.8657, + "step": 1162 + }, + { + "epoch": 0.22, + "learning_rate": 1.809310060129836e-05, + "loss": 1.8987, + "step": 1163 + }, + { + "epoch": 0.22, + "learning_rate": 1.8089436964871407e-05, + "loss": 0.8831, + "step": 1164 + }, + { + "epoch": 0.22, + "learning_rate": 1.8085770184105837e-05, + "loss": 0.8574, + "step": 1165 + }, + { + "epoch": 0.22, + "learning_rate": 1.808210026042691e-05, + "loss": 0.8898, + "step": 1166 + }, + { + "epoch": 0.22, + "learning_rate": 1.807842719526112e-05, + "loss": 0.8305, + "step": 1167 + }, + { + "epoch": 0.22, + "learning_rate": 1.8074750990036176e-05, + "loss": 0.915, + "step": 1168 + }, + { + "epoch": 0.23, + "learning_rate": 1.8071071646181e-05, + "loss": 0.8682, + "step": 1169 + }, + { + "epoch": 0.23, + "learning_rate": 1.8067389165125752e-05, + "loss": 0.909, + "step": 1170 + }, + { + "epoch": 0.23, + "learning_rate": 1.8063703548301787e-05, + "loss": 0.7659, + "step": 1171 + }, + { + "epoch": 0.23, + "learning_rate": 1.8060014797141705e-05, + "loss": 0.8886, + "step": 1172 + }, + { + "epoch": 0.23, + "learning_rate": 1.8056322913079303e-05, + "loss": 0.8451, + "step": 1173 + }, + { + "epoch": 0.23, + "learning_rate": 1.8052627897549614e-05, + "loss": 0.8756, + "step": 1174 + }, + { + "epoch": 0.23, + "learning_rate": 1.8048929751988873e-05, + "loss": 0.8779, + "step": 1175 + }, + { + "epoch": 0.23, + "learning_rate": 1.8045228477834536e-05, + "loss": 0.8537, + "step": 1176 + }, + { + "epoch": 0.23, + "learning_rate": 1.8041524076525285e-05, + "loss": 0.8551, + "step": 1177 + }, + { + "epoch": 0.23, + "learning_rate": 1.8037816549500996e-05, + "loss": 0.8875, + "step": 1178 + }, + { + "epoch": 0.23, + "learning_rate": 1.8034105898202785e-05, + "loss": 0.8643, + "step": 1179 + }, + { + "epoch": 0.23, + "learning_rate": 1.8030392124072963e-05, + "loss": 0.845, + "step": 1180 + }, + { + "epoch": 0.23, + "learning_rate": 1.8026675228555066e-05, + "loss": 1.7516, + "step": 1181 + }, + { + "epoch": 0.23, + "learning_rate": 1.802295521309384e-05, + "loss": 0.8958, + "step": 1182 + }, + { + "epoch": 0.23, + "learning_rate": 1.801923207913524e-05, + "loss": 0.8256, + "step": 1183 + }, + { + "epoch": 0.23, + "learning_rate": 1.8015505828126438e-05, + "loss": 0.9215, + "step": 1184 + }, + { + "epoch": 0.23, + "learning_rate": 1.801177646151582e-05, + "loss": 0.8475, + "step": 1185 + }, + { + "epoch": 0.23, + "learning_rate": 1.8008043980752967e-05, + "loss": 0.8053, + "step": 1186 + }, + { + "epoch": 0.23, + "learning_rate": 1.8004308387288697e-05, + "loss": 1.8174, + "step": 1187 + }, + { + "epoch": 0.23, + "learning_rate": 1.8000569682575016e-05, + "loss": 0.8164, + "step": 1188 + }, + { + "epoch": 0.23, + "learning_rate": 1.7996827868065145e-05, + "loss": 0.8403, + "step": 1189 + }, + { + "epoch": 0.23, + "learning_rate": 1.7993082945213522e-05, + "loss": 0.8428, + "step": 1190 + }, + { + "epoch": 0.23, + "learning_rate": 1.798933491547578e-05, + "loss": 0.8677, + "step": 1191 + }, + { + "epoch": 0.23, + "learning_rate": 1.798558378030877e-05, + "loss": 0.8296, + "step": 1192 + }, + { + "epoch": 0.23, + "learning_rate": 1.7981829541170547e-05, + "loss": 0.8454, + "step": 1193 + }, + { + "epoch": 0.23, + "learning_rate": 1.797807219952037e-05, + "loss": 0.8547, + "step": 1194 + }, + { + "epoch": 0.23, + "learning_rate": 1.797431175681871e-05, + "loss": 0.7966, + "step": 1195 + }, + { + "epoch": 0.23, + "learning_rate": 1.797054821452723e-05, + "loss": 0.8561, + "step": 1196 + }, + { + "epoch": 0.23, + "learning_rate": 1.7966781574108815e-05, + "loss": 0.8459, + "step": 1197 + }, + { + "epoch": 0.23, + "learning_rate": 1.7963011837027544e-05, + "loss": 0.8423, + "step": 1198 + }, + { + "epoch": 0.23, + "learning_rate": 1.79592390047487e-05, + "loss": 0.8452, + "step": 1199 + }, + { + "epoch": 0.23, + "learning_rate": 1.7955463078738777e-05, + "loss": 0.8832, + "step": 1200 + }, + { + "epoch": 0.23, + "learning_rate": 1.7951684060465456e-05, + "loss": 0.8104, + "step": 1201 + }, + { + "epoch": 0.23, + "learning_rate": 1.794790195139764e-05, + "loss": 0.8145, + "step": 1202 + }, + { + "epoch": 0.23, + "learning_rate": 1.7944116753005416e-05, + "loss": 0.8953, + "step": 1203 + }, + { + "epoch": 0.23, + "learning_rate": 1.794032846676008e-05, + "loss": 0.8428, + "step": 1204 + }, + { + "epoch": 0.23, + "learning_rate": 1.7936537094134127e-05, + "loss": 0.834, + "step": 1205 + }, + { + "epoch": 0.23, + "learning_rate": 1.7932742636601252e-05, + "loss": 0.8944, + "step": 1206 + }, + { + "epoch": 0.23, + "learning_rate": 1.792894509563635e-05, + "loss": 0.84, + "step": 1207 + }, + { + "epoch": 0.23, + "learning_rate": 1.792514447271551e-05, + "loss": 0.8788, + "step": 1208 + }, + { + "epoch": 0.23, + "learning_rate": 1.7921340769316024e-05, + "loss": 0.9051, + "step": 1209 + }, + { + "epoch": 0.23, + "learning_rate": 1.791753398691638e-05, + "loss": 1.8386, + "step": 1210 + }, + { + "epoch": 0.23, + "learning_rate": 1.7913724126996263e-05, + "loss": 0.8356, + "step": 1211 + }, + { + "epoch": 0.23, + "learning_rate": 1.7909911191036548e-05, + "loss": 0.8676, + "step": 1212 + }, + { + "epoch": 0.23, + "learning_rate": 1.7906095180519317e-05, + "loss": 0.8033, + "step": 1213 + }, + { + "epoch": 0.23, + "learning_rate": 1.790227609692784e-05, + "loss": 0.829, + "step": 1214 + }, + { + "epoch": 0.23, + "learning_rate": 1.7898453941746585e-05, + "loss": 0.8496, + "step": 1215 + }, + { + "epoch": 0.23, + "learning_rate": 1.7894628716461205e-05, + "loss": 0.8423, + "step": 1216 + }, + { + "epoch": 0.23, + "learning_rate": 1.7890800422558562e-05, + "loss": 0.8678, + "step": 1217 + }, + { + "epoch": 0.23, + "learning_rate": 1.788696906152669e-05, + "loss": 0.9093, + "step": 1218 + }, + { + "epoch": 0.23, + "learning_rate": 1.788313463485484e-05, + "loss": 0.8698, + "step": 1219 + }, + { + "epoch": 0.23, + "learning_rate": 1.787929714403343e-05, + "loss": 0.8843, + "step": 1220 + }, + { + "epoch": 0.24, + "learning_rate": 1.787545659055409e-05, + "loss": 0.7939, + "step": 1221 + }, + { + "epoch": 0.24, + "learning_rate": 1.7871612975909623e-05, + "loss": 0.8241, + "step": 1222 + }, + { + "epoch": 0.24, + "learning_rate": 1.786776630159404e-05, + "loss": 0.8665, + "step": 1223 + }, + { + "epoch": 0.24, + "learning_rate": 1.786391656910252e-05, + "loss": 0.8686, + "step": 1224 + }, + { + "epoch": 0.24, + "learning_rate": 1.786006377993145e-05, + "loss": 0.8307, + "step": 1225 + }, + { + "epoch": 0.24, + "learning_rate": 1.785620793557839e-05, + "loss": 0.8649, + "step": 1226 + }, + { + "epoch": 0.24, + "learning_rate": 1.78523490375421e-05, + "loss": 0.8615, + "step": 1227 + }, + { + "epoch": 0.24, + "learning_rate": 1.784848708732252e-05, + "loss": 0.8072, + "step": 1228 + }, + { + "epoch": 0.24, + "learning_rate": 1.7844622086420775e-05, + "loss": 0.8663, + "step": 1229 + }, + { + "epoch": 0.24, + "learning_rate": 1.7840754036339185e-05, + "loss": 0.8678, + "step": 1230 + }, + { + "epoch": 0.24, + "learning_rate": 1.783688293858124e-05, + "loss": 0.8877, + "step": 1231 + }, + { + "epoch": 0.24, + "learning_rate": 1.7833008794651632e-05, + "loss": 0.7926, + "step": 1232 + }, + { + "epoch": 0.24, + "learning_rate": 1.7829131606056228e-05, + "loss": 0.8355, + "step": 1233 + }, + { + "epoch": 0.24, + "learning_rate": 1.7825251374302073e-05, + "loss": 0.808, + "step": 1234 + }, + { + "epoch": 0.24, + "learning_rate": 1.7821368100897404e-05, + "loss": 0.8718, + "step": 1235 + }, + { + "epoch": 0.24, + "learning_rate": 1.781748178735164e-05, + "loss": 0.8748, + "step": 1236 + }, + { + "epoch": 0.24, + "learning_rate": 1.781359243517537e-05, + "loss": 0.8689, + "step": 1237 + }, + { + "epoch": 0.24, + "learning_rate": 1.7809700045880383e-05, + "loss": 0.8604, + "step": 1238 + }, + { + "epoch": 0.24, + "learning_rate": 1.7805804620979633e-05, + "loss": 0.7991, + "step": 1239 + }, + { + "epoch": 0.24, + "learning_rate": 1.780190616198726e-05, + "loss": 0.8309, + "step": 1240 + }, + { + "epoch": 0.24, + "learning_rate": 1.7798004670418587e-05, + "loss": 0.8856, + "step": 1241 + }, + { + "epoch": 0.24, + "learning_rate": 1.7794100147790105e-05, + "loss": 0.9274, + "step": 1242 + }, + { + "epoch": 0.24, + "learning_rate": 1.7790192595619494e-05, + "loss": 0.8363, + "step": 1243 + }, + { + "epoch": 0.24, + "learning_rate": 1.7786282015425605e-05, + "loss": 0.8763, + "step": 1244 + }, + { + "epoch": 0.24, + "learning_rate": 1.7782368408728468e-05, + "loss": 1.7543, + "step": 1245 + }, + { + "epoch": 0.24, + "learning_rate": 1.7778451777049288e-05, + "loss": 0.8383, + "step": 1246 + }, + { + "epoch": 0.24, + "learning_rate": 1.7774532121910452e-05, + "loss": 0.8198, + "step": 1247 + }, + { + "epoch": 0.24, + "learning_rate": 1.7770609444835517e-05, + "loss": 0.8555, + "step": 1248 + }, + { + "epoch": 0.24, + "learning_rate": 1.776668374734921e-05, + "loss": 0.8394, + "step": 1249 + }, + { + "epoch": 0.24, + "learning_rate": 1.7762755030977444e-05, + "loss": 0.8871, + "step": 1250 + }, + { + "epoch": 0.24, + "learning_rate": 1.7758823297247293e-05, + "loss": 0.818, + "step": 1251 + }, + { + "epoch": 0.24, + "learning_rate": 1.7754888547687013e-05, + "loss": 0.8558, + "step": 1252 + }, + { + "epoch": 0.24, + "learning_rate": 1.7750950783826027e-05, + "loss": 0.8184, + "step": 1253 + }, + { + "epoch": 0.24, + "learning_rate": 1.7747010007194934e-05, + "loss": 0.8478, + "step": 1254 + }, + { + "epoch": 0.24, + "learning_rate": 1.7743066219325497e-05, + "loss": 0.8309, + "step": 1255 + }, + { + "epoch": 0.24, + "learning_rate": 1.7739119421750657e-05, + "loss": 0.8312, + "step": 1256 + }, + { + "epoch": 0.24, + "learning_rate": 1.7735169616004522e-05, + "loss": 0.8239, + "step": 1257 + }, + { + "epoch": 0.24, + "learning_rate": 1.7731216803622367e-05, + "loss": 0.9024, + "step": 1258 + }, + { + "epoch": 0.24, + "learning_rate": 1.7727260986140642e-05, + "loss": 0.9217, + "step": 1259 + }, + { + "epoch": 0.24, + "learning_rate": 1.7723302165096953e-05, + "loss": 0.8395, + "step": 1260 + }, + { + "epoch": 0.24, + "learning_rate": 1.771934034203009e-05, + "loss": 0.8614, + "step": 1261 + }, + { + "epoch": 0.24, + "learning_rate": 1.7715375518479995e-05, + "loss": 0.8729, + "step": 1262 + }, + { + "epoch": 0.24, + "learning_rate": 1.7711407695987783e-05, + "loss": 1.7704, + "step": 1263 + }, + { + "epoch": 0.24, + "learning_rate": 1.7707436876095736e-05, + "loss": 0.8176, + "step": 1264 + }, + { + "epoch": 0.24, + "learning_rate": 1.77034630603473e-05, + "loss": 0.8964, + "step": 1265 + }, + { + "epoch": 0.24, + "learning_rate": 1.7699486250287083e-05, + "loss": 0.8538, + "step": 1266 + }, + { + "epoch": 0.24, + "learning_rate": 1.769550644746086e-05, + "loss": 0.7981, + "step": 1267 + }, + { + "epoch": 0.24, + "learning_rate": 1.7691523653415562e-05, + "loss": 0.8831, + "step": 1268 + }, + { + "epoch": 0.24, + "learning_rate": 1.7687537869699296e-05, + "loss": 0.8137, + "step": 1269 + }, + { + "epoch": 0.24, + "learning_rate": 1.768354909786132e-05, + "loss": 0.8422, + "step": 1270 + }, + { + "epoch": 0.24, + "learning_rate": 1.7679557339452057e-05, + "loss": 0.8776, + "step": 1271 + }, + { + "epoch": 0.24, + "learning_rate": 1.7675562596023095e-05, + "loss": 0.8741, + "step": 1272 + }, + { + "epoch": 0.25, + "learning_rate": 1.767156486912717e-05, + "loss": 0.8671, + "step": 1273 + }, + { + "epoch": 0.25, + "learning_rate": 1.7667564160318195e-05, + "loss": 0.7862, + "step": 1274 + }, + { + "epoch": 0.25, + "learning_rate": 1.7663560471151227e-05, + "loss": 0.8761, + "step": 1275 + }, + { + "epoch": 0.25, + "learning_rate": 1.7659553803182486e-05, + "loss": 0.852, + "step": 1276 + }, + { + "epoch": 0.25, + "learning_rate": 1.7655544157969355e-05, + "loss": 0.8378, + "step": 1277 + }, + { + "epoch": 0.25, + "learning_rate": 1.765153153707037e-05, + "loss": 0.8167, + "step": 1278 + }, + { + "epoch": 0.25, + "learning_rate": 1.7647515942045227e-05, + "loss": 0.844, + "step": 1279 + }, + { + "epoch": 0.25, + "learning_rate": 1.7643497374454767e-05, + "loss": 0.8278, + "step": 1280 + }, + { + "epoch": 0.25, + "learning_rate": 1.7639475835861e-05, + "loss": 0.8179, + "step": 1281 + }, + { + "epoch": 0.25, + "learning_rate": 1.7635451327827087e-05, + "loss": 0.8621, + "step": 1282 + }, + { + "epoch": 0.25, + "learning_rate": 1.7631423851917334e-05, + "loss": 0.8506, + "step": 1283 + }, + { + "epoch": 0.25, + "learning_rate": 1.7627393409697217e-05, + "loss": 0.7965, + "step": 1284 + }, + { + "epoch": 0.25, + "learning_rate": 1.762336000273335e-05, + "loss": 0.844, + "step": 1285 + }, + { + "epoch": 0.25, + "learning_rate": 1.761932363259351e-05, + "loss": 0.8444, + "step": 1286 + }, + { + "epoch": 0.25, + "learning_rate": 1.761528430084662e-05, + "loss": 0.8392, + "step": 1287 + }, + { + "epoch": 0.25, + "learning_rate": 1.7611242009062754e-05, + "loss": 0.7927, + "step": 1288 + }, + { + "epoch": 0.25, + "learning_rate": 1.760719675881314e-05, + "loss": 0.8191, + "step": 1289 + }, + { + "epoch": 0.25, + "learning_rate": 1.7603148551670152e-05, + "loss": 0.8652, + "step": 1290 + }, + { + "epoch": 0.25, + "learning_rate": 1.7599097389207313e-05, + "loss": 0.8502, + "step": 1291 + }, + { + "epoch": 0.25, + "learning_rate": 1.7595043272999306e-05, + "loss": 0.8202, + "step": 1292 + }, + { + "epoch": 0.25, + "learning_rate": 1.7590986204621943e-05, + "loss": 0.8186, + "step": 1293 + }, + { + "epoch": 0.25, + "learning_rate": 1.75869261856522e-05, + "loss": 0.8169, + "step": 1294 + }, + { + "epoch": 0.25, + "learning_rate": 1.7582863217668192e-05, + "loss": 0.811, + "step": 1295 + }, + { + "epoch": 0.25, + "learning_rate": 1.757879730224918e-05, + "loss": 0.8408, + "step": 1296 + }, + { + "epoch": 0.25, + "learning_rate": 1.7574728440975574e-05, + "loss": 0.8646, + "step": 1297 + }, + { + "epoch": 0.25, + "learning_rate": 1.757065663542893e-05, + "loss": 0.8249, + "step": 1298 + }, + { + "epoch": 0.25, + "learning_rate": 1.756658188719194e-05, + "loss": 0.819, + "step": 1299 + }, + { + "epoch": 0.25, + "learning_rate": 1.7562504197848452e-05, + "loss": 0.8411, + "step": 1300 + }, + { + "epoch": 0.25, + "learning_rate": 1.7558423568983446e-05, + "loss": 0.8301, + "step": 1301 + }, + { + "epoch": 0.25, + "learning_rate": 1.7554340002183053e-05, + "loss": 0.8325, + "step": 1302 + }, + { + "epoch": 0.25, + "learning_rate": 1.755025349903454e-05, + "loss": 0.8784, + "step": 1303 + }, + { + "epoch": 0.25, + "learning_rate": 1.7546164061126322e-05, + "loss": 0.9125, + "step": 1304 + }, + { + "epoch": 0.25, + "learning_rate": 1.7542071690047947e-05, + "loss": 0.8356, + "step": 1305 + }, + { + "epoch": 0.25, + "learning_rate": 1.7537976387390107e-05, + "loss": 0.8738, + "step": 1306 + }, + { + "epoch": 0.25, + "learning_rate": 1.7533878154744634e-05, + "loss": 0.8039, + "step": 1307 + }, + { + "epoch": 0.25, + "learning_rate": 1.75297769937045e-05, + "loss": 0.815, + "step": 1308 + }, + { + "epoch": 0.25, + "learning_rate": 1.7525672905863808e-05, + "loss": 0.8537, + "step": 1309 + }, + { + "epoch": 0.25, + "learning_rate": 1.7521565892817808e-05, + "loss": 0.8326, + "step": 1310 + }, + { + "epoch": 0.25, + "learning_rate": 1.751745595616288e-05, + "loss": 0.8746, + "step": 1311 + }, + { + "epoch": 0.25, + "learning_rate": 1.751334309749655e-05, + "loss": 0.814, + "step": 1312 + }, + { + "epoch": 0.25, + "learning_rate": 1.7509227318417465e-05, + "loss": 0.8988, + "step": 1313 + }, + { + "epoch": 0.25, + "learning_rate": 1.7505108620525425e-05, + "loss": 0.842, + "step": 1314 + }, + { + "epoch": 0.25, + "learning_rate": 1.7500987005421345e-05, + "loss": 0.8591, + "step": 1315 + }, + { + "epoch": 0.25, + "learning_rate": 1.7496862474707287e-05, + "loss": 0.833, + "step": 1316 + }, + { + "epoch": 0.25, + "learning_rate": 1.7492735029986442e-05, + "loss": 0.8228, + "step": 1317 + }, + { + "epoch": 0.25, + "learning_rate": 1.7488604672863144e-05, + "loss": 0.7992, + "step": 1318 + }, + { + "epoch": 0.25, + "learning_rate": 1.7484471404942836e-05, + "loss": 1.8106, + "step": 1319 + }, + { + "epoch": 0.25, + "learning_rate": 1.7480335227832115e-05, + "loss": 0.8568, + "step": 1320 + }, + { + "epoch": 0.25, + "learning_rate": 1.7476196143138695e-05, + "loss": 0.8067, + "step": 1321 + }, + { + "epoch": 0.25, + "learning_rate": 1.7472054152471432e-05, + "loss": 0.8333, + "step": 1322 + }, + { + "epoch": 0.25, + "learning_rate": 1.74679092574403e-05, + "loss": 0.8012, + "step": 1323 + }, + { + "epoch": 0.25, + "learning_rate": 1.7463761459656402e-05, + "loss": 0.8462, + "step": 1324 + }, + { + "epoch": 0.26, + "learning_rate": 1.7459610760731984e-05, + "loss": 0.8184, + "step": 1325 + }, + { + "epoch": 0.26, + "learning_rate": 1.74554571622804e-05, + "loss": 0.8853, + "step": 1326 + }, + { + "epoch": 0.26, + "learning_rate": 1.745130066591615e-05, + "loss": 0.801, + "step": 1327 + }, + { + "epoch": 0.26, + "learning_rate": 1.7447141273254845e-05, + "loss": 0.8147, + "step": 1328 + }, + { + "epoch": 0.26, + "learning_rate": 1.7442978985913227e-05, + "loss": 0.8099, + "step": 1329 + }, + { + "epoch": 0.26, + "learning_rate": 1.7438813805509168e-05, + "loss": 1.6249, + "step": 1330 + }, + { + "epoch": 0.26, + "learning_rate": 1.743464573366166e-05, + "loss": 0.7834, + "step": 1331 + }, + { + "epoch": 0.26, + "learning_rate": 1.7430474771990816e-05, + "loss": 0.9115, + "step": 1332 + }, + { + "epoch": 0.26, + "learning_rate": 1.7426300922117877e-05, + "loss": 0.7822, + "step": 1333 + }, + { + "epoch": 0.26, + "learning_rate": 1.7422124185665203e-05, + "loss": 0.8433, + "step": 1334 + }, + { + "epoch": 0.26, + "learning_rate": 1.7417944564256285e-05, + "loss": 0.8887, + "step": 1335 + }, + { + "epoch": 0.26, + "learning_rate": 1.741376205951572e-05, + "loss": 0.8394, + "step": 1336 + }, + { + "epoch": 0.26, + "learning_rate": 1.7409576673069247e-05, + "loss": 0.8774, + "step": 1337 + }, + { + "epoch": 0.26, + "learning_rate": 1.7405388406543697e-05, + "loss": 0.8054, + "step": 1338 + }, + { + "epoch": 0.26, + "learning_rate": 1.7401197261567048e-05, + "loss": 0.8064, + "step": 1339 + }, + { + "epoch": 0.26, + "learning_rate": 1.739700323976838e-05, + "loss": 1.7548, + "step": 1340 + }, + { + "epoch": 0.26, + "learning_rate": 1.7392806342777897e-05, + "loss": 0.8788, + "step": 1341 + }, + { + "epoch": 0.26, + "learning_rate": 1.7388606572226912e-05, + "loss": 1.6834, + "step": 1342 + }, + { + "epoch": 0.26, + "learning_rate": 1.7384403929747877e-05, + "loss": 0.898, + "step": 1343 + }, + { + "epoch": 0.26, + "learning_rate": 1.7380198416974338e-05, + "loss": 0.7786, + "step": 1344 + }, + { + "epoch": 0.26, + "learning_rate": 1.737599003554096e-05, + "loss": 0.8113, + "step": 1345 + }, + { + "epoch": 0.26, + "learning_rate": 1.7371778787083538e-05, + "loss": 0.7925, + "step": 1346 + }, + { + "epoch": 0.26, + "learning_rate": 1.7367564673238962e-05, + "loss": 1.5851, + "step": 1347 + }, + { + "epoch": 0.26, + "learning_rate": 1.736334769564525e-05, + "loss": 0.8199, + "step": 1348 + }, + { + "epoch": 0.26, + "learning_rate": 1.7359127855941523e-05, + "loss": 0.8393, + "step": 1349 + }, + { + "epoch": 0.26, + "learning_rate": 1.7354905155768027e-05, + "loss": 0.8417, + "step": 1350 + }, + { + "epoch": 0.26, + "learning_rate": 1.7350679596766108e-05, + "loss": 0.8919, + "step": 1351 + }, + { + "epoch": 0.26, + "learning_rate": 1.7346451180578222e-05, + "loss": 0.8561, + "step": 1352 + }, + { + "epoch": 0.26, + "learning_rate": 1.734221990884795e-05, + "loss": 0.8676, + "step": 1353 + }, + { + "epoch": 0.26, + "learning_rate": 1.733798578321997e-05, + "loss": 0.8004, + "step": 1354 + }, + { + "epoch": 0.26, + "learning_rate": 1.7333748805340072e-05, + "loss": 0.851, + "step": 1355 + }, + { + "epoch": 0.26, + "learning_rate": 1.7329508976855162e-05, + "loss": 0.8417, + "step": 1356 + }, + { + "epoch": 0.26, + "learning_rate": 1.7325266299413237e-05, + "loss": 0.7874, + "step": 1357 + }, + { + "epoch": 0.26, + "learning_rate": 1.732102077466342e-05, + "loss": 0.854, + "step": 1358 + }, + { + "epoch": 0.26, + "learning_rate": 1.7316772404255934e-05, + "loss": 0.8809, + "step": 1359 + }, + { + "epoch": 0.26, + "learning_rate": 1.7312521189842108e-05, + "loss": 0.8877, + "step": 1360 + }, + { + "epoch": 0.26, + "learning_rate": 1.730826713307437e-05, + "loss": 1.806, + "step": 1361 + }, + { + "epoch": 0.26, + "learning_rate": 1.7304010235606256e-05, + "loss": 0.9063, + "step": 1362 + }, + { + "epoch": 0.26, + "learning_rate": 1.729975049909242e-05, + "loss": 0.8165, + "step": 1363 + }, + { + "epoch": 0.26, + "learning_rate": 1.7295487925188598e-05, + "loss": 0.8667, + "step": 1364 + }, + { + "epoch": 0.26, + "learning_rate": 1.7291222515551643e-05, + "loss": 0.8482, + "step": 1365 + }, + { + "epoch": 0.26, + "learning_rate": 1.7286954271839507e-05, + "loss": 0.8336, + "step": 1366 + }, + { + "epoch": 0.26, + "learning_rate": 1.728268319571124e-05, + "loss": 0.8388, + "step": 1367 + }, + { + "epoch": 0.26, + "learning_rate": 1.7278409288827002e-05, + "loss": 0.8516, + "step": 1368 + }, + { + "epoch": 0.26, + "learning_rate": 1.7274132552848042e-05, + "loss": 0.7786, + "step": 1369 + }, + { + "epoch": 0.26, + "learning_rate": 1.7269852989436713e-05, + "loss": 0.8013, + "step": 1370 + }, + { + "epoch": 0.26, + "learning_rate": 1.726557060025647e-05, + "loss": 0.7433, + "step": 1371 + }, + { + "epoch": 0.26, + "learning_rate": 1.7261285386971863e-05, + "loss": 0.8963, + "step": 1372 + }, + { + "epoch": 0.26, + "learning_rate": 1.725699735124854e-05, + "loss": 0.8206, + "step": 1373 + }, + { + "epoch": 0.26, + "learning_rate": 1.7252706494753254e-05, + "loss": 0.8627, + "step": 1374 + }, + { + "epoch": 0.26, + "learning_rate": 1.7248412819153835e-05, + "loss": 0.8815, + "step": 1375 + }, + { + "epoch": 0.26, + "learning_rate": 1.724411632611923e-05, + "loss": 0.8526, + "step": 1376 + }, + { + "epoch": 0.27, + "learning_rate": 1.7239817017319473e-05, + "loss": 0.8652, + "step": 1377 + }, + { + "epoch": 0.27, + "learning_rate": 1.7235514894425687e-05, + "loss": 0.8723, + "step": 1378 + }, + { + "epoch": 0.27, + "learning_rate": 1.7231209959110097e-05, + "loss": 0.7981, + "step": 1379 + }, + { + "epoch": 0.27, + "learning_rate": 1.7226902213046016e-05, + "loss": 0.8708, + "step": 1380 + }, + { + "epoch": 0.27, + "learning_rate": 1.722259165790785e-05, + "loss": 0.9044, + "step": 1381 + }, + { + "epoch": 0.27, + "learning_rate": 1.72182782953711e-05, + "loss": 0.8484, + "step": 1382 + }, + { + "epoch": 0.27, + "learning_rate": 1.7213962127112355e-05, + "loss": 0.8652, + "step": 1383 + }, + { + "epoch": 0.27, + "learning_rate": 1.7209643154809298e-05, + "loss": 0.8913, + "step": 1384 + }, + { + "epoch": 0.27, + "learning_rate": 1.72053213801407e-05, + "loss": 0.8035, + "step": 1385 + }, + { + "epoch": 0.27, + "learning_rate": 1.7200996804786423e-05, + "loss": 0.8028, + "step": 1386 + }, + { + "epoch": 0.27, + "learning_rate": 1.719666943042741e-05, + "loss": 0.8526, + "step": 1387 + }, + { + "epoch": 0.27, + "learning_rate": 1.71923392587457e-05, + "loss": 0.8902, + "step": 1388 + }, + { + "epoch": 0.27, + "learning_rate": 1.718800629142442e-05, + "loss": 0.8539, + "step": 1389 + }, + { + "epoch": 0.27, + "learning_rate": 1.718367053014778e-05, + "loss": 0.8222, + "step": 1390 + }, + { + "epoch": 0.27, + "learning_rate": 1.717933197660107e-05, + "loss": 0.7978, + "step": 1391 + }, + { + "epoch": 0.27, + "learning_rate": 1.7174990632470682e-05, + "loss": 0.8444, + "step": 1392 + }, + { + "epoch": 0.27, + "learning_rate": 1.717064649944408e-05, + "loss": 0.8333, + "step": 1393 + }, + { + "epoch": 0.27, + "learning_rate": 1.7166299579209806e-05, + "loss": 1.8398, + "step": 1394 + }, + { + "epoch": 0.27, + "learning_rate": 1.716194987345751e-05, + "loss": 0.7629, + "step": 1395 + }, + { + "epoch": 0.27, + "learning_rate": 1.715759738387789e-05, + "loss": 0.8554, + "step": 1396 + }, + { + "epoch": 0.27, + "learning_rate": 1.7153242112162763e-05, + "loss": 0.8713, + "step": 1397 + }, + { + "epoch": 0.27, + "learning_rate": 1.7148884060004997e-05, + "loss": 0.8026, + "step": 1398 + }, + { + "epoch": 0.27, + "learning_rate": 1.714452322909856e-05, + "loss": 0.8585, + "step": 1399 + }, + { + "epoch": 0.27, + "learning_rate": 1.714015962113849e-05, + "loss": 0.8849, + "step": 1400 + }, + { + "epoch": 0.27, + "learning_rate": 1.713579323782091e-05, + "loss": 0.8276, + "step": 1401 + }, + { + "epoch": 0.27, + "learning_rate": 1.7131424080843016e-05, + "loss": 0.8763, + "step": 1402 + }, + { + "epoch": 0.27, + "learning_rate": 1.7127052151903087e-05, + "loss": 0.876, + "step": 1403 + }, + { + "epoch": 0.27, + "learning_rate": 1.7122677452700477e-05, + "loss": 0.8984, + "step": 1404 + }, + { + "epoch": 0.27, + "learning_rate": 1.7118299984935622e-05, + "loss": 0.8012, + "step": 1405 + }, + { + "epoch": 0.27, + "learning_rate": 1.7113919750310026e-05, + "loss": 0.8115, + "step": 1406 + }, + { + "epoch": 0.27, + "learning_rate": 1.7109536750526273e-05, + "loss": 0.8273, + "step": 1407 + }, + { + "epoch": 0.27, + "learning_rate": 1.710515098728802e-05, + "loss": 0.8964, + "step": 1408 + }, + { + "epoch": 0.27, + "learning_rate": 1.7100762462300005e-05, + "loss": 0.878, + "step": 1409 + }, + { + "epoch": 0.27, + "learning_rate": 1.7096371177268026e-05, + "loss": 0.902, + "step": 1410 + }, + { + "epoch": 0.27, + "learning_rate": 1.7091977133898967e-05, + "loss": 0.8371, + "step": 1411 + }, + { + "epoch": 0.27, + "learning_rate": 1.7087580333900778e-05, + "loss": 0.8558, + "step": 1412 + }, + { + "epoch": 0.27, + "learning_rate": 1.7083180778982477e-05, + "loss": 0.8564, + "step": 1413 + }, + { + "epoch": 0.27, + "learning_rate": 1.7078778470854163e-05, + "loss": 0.8061, + "step": 1414 + }, + { + "epoch": 0.27, + "learning_rate": 1.7074373411226998e-05, + "loss": 0.8164, + "step": 1415 + }, + { + "epoch": 0.27, + "learning_rate": 1.706996560181321e-05, + "loss": 0.8727, + "step": 1416 + }, + { + "epoch": 0.27, + "learning_rate": 1.706555504432611e-05, + "loss": 0.836, + "step": 1417 + }, + { + "epoch": 0.27, + "learning_rate": 1.706114174048006e-05, + "loss": 0.8605, + "step": 1418 + }, + { + "epoch": 0.27, + "learning_rate": 1.7056725691990496e-05, + "loss": 0.8855, + "step": 1419 + }, + { + "epoch": 0.27, + "learning_rate": 1.7052306900573926e-05, + "loss": 0.8402, + "step": 1420 + }, + { + "epoch": 0.27, + "learning_rate": 1.704788536794792e-05, + "loss": 0.8197, + "step": 1421 + }, + { + "epoch": 0.27, + "learning_rate": 1.7043461095831113e-05, + "loss": 0.8182, + "step": 1422 + }, + { + "epoch": 0.27, + "learning_rate": 1.7039034085943206e-05, + "loss": 0.8335, + "step": 1423 + }, + { + "epoch": 0.27, + "learning_rate": 1.7034604340004967e-05, + "loss": 0.7831, + "step": 1424 + }, + { + "epoch": 0.27, + "learning_rate": 1.7030171859738217e-05, + "loss": 0.8162, + "step": 1425 + }, + { + "epoch": 0.27, + "learning_rate": 1.7025736646865852e-05, + "loss": 0.8223, + "step": 1426 + }, + { + "epoch": 0.27, + "learning_rate": 1.7021298703111824e-05, + "loss": 0.8487, + "step": 1427 + }, + { + "epoch": 0.27, + "learning_rate": 1.7016858030201154e-05, + "loss": 0.8462, + "step": 1428 + }, + { + "epoch": 0.28, + "learning_rate": 1.7012414629859905e-05, + "loss": 0.8741, + "step": 1429 + }, + { + "epoch": 0.28, + "learning_rate": 1.700796850381522e-05, + "loss": 0.8595, + "step": 1430 + }, + { + "epoch": 0.28, + "learning_rate": 1.70035196537953e-05, + "loss": 0.8784, + "step": 1431 + }, + { + "epoch": 0.28, + "learning_rate": 1.6999068081529385e-05, + "loss": 0.7547, + "step": 1432 + }, + { + "epoch": 0.28, + "learning_rate": 1.6994613788747797e-05, + "loss": 0.8337, + "step": 1433 + }, + { + "epoch": 0.28, + "learning_rate": 1.6990156777181903e-05, + "loss": 0.8824, + "step": 1434 + }, + { + "epoch": 0.28, + "learning_rate": 1.698569704856413e-05, + "loss": 0.848, + "step": 1435 + }, + { + "epoch": 0.28, + "learning_rate": 1.698123460462796e-05, + "loss": 0.8109, + "step": 1436 + }, + { + "epoch": 0.28, + "learning_rate": 1.697676944710793e-05, + "loss": 1.7661, + "step": 1437 + }, + { + "epoch": 0.28, + "learning_rate": 1.697230157773963e-05, + "loss": 0.8823, + "step": 1438 + }, + { + "epoch": 0.28, + "learning_rate": 1.6967830998259715e-05, + "loss": 0.8503, + "step": 1439 + }, + { + "epoch": 0.28, + "learning_rate": 1.696335771040588e-05, + "loss": 0.8708, + "step": 1440 + }, + { + "epoch": 0.28, + "learning_rate": 1.6958881715916878e-05, + "loss": 0.8191, + "step": 1441 + }, + { + "epoch": 0.28, + "learning_rate": 1.695440301653251e-05, + "loss": 0.8157, + "step": 1442 + }, + { + "epoch": 0.28, + "learning_rate": 1.6949921613993644e-05, + "loss": 0.8638, + "step": 1443 + }, + { + "epoch": 0.28, + "learning_rate": 1.694543751004217e-05, + "loss": 0.8387, + "step": 1444 + }, + { + "epoch": 0.28, + "learning_rate": 1.6940950706421062e-05, + "loss": 0.8661, + "step": 1445 + }, + { + "epoch": 0.28, + "learning_rate": 1.6936461204874318e-05, + "loss": 0.8051, + "step": 1446 + }, + { + "epoch": 0.28, + "learning_rate": 1.6931969007146988e-05, + "loss": 0.7785, + "step": 1447 + }, + { + "epoch": 0.28, + "learning_rate": 1.6927474114985186e-05, + "loss": 0.8714, + "step": 1448 + }, + { + "epoch": 0.28, + "learning_rate": 1.692297653013606e-05, + "loss": 0.8966, + "step": 1449 + }, + { + "epoch": 0.28, + "learning_rate": 1.69184762543478e-05, + "loss": 0.8205, + "step": 1450 + }, + { + "epoch": 0.28, + "learning_rate": 1.6913973289369657e-05, + "loss": 0.8285, + "step": 1451 + }, + { + "epoch": 0.28, + "learning_rate": 1.690946763695191e-05, + "loss": 0.8379, + "step": 1452 + }, + { + "epoch": 0.28, + "learning_rate": 1.69049592988459e-05, + "loss": 0.7809, + "step": 1453 + }, + { + "epoch": 0.28, + "learning_rate": 1.6900448276804004e-05, + "loss": 0.8077, + "step": 1454 + }, + { + "epoch": 0.28, + "learning_rate": 1.6895934572579637e-05, + "loss": 0.8302, + "step": 1455 + }, + { + "epoch": 0.28, + "learning_rate": 1.6891418187927265e-05, + "loss": 0.8465, + "step": 1456 + }, + { + "epoch": 0.28, + "learning_rate": 1.6886899124602392e-05, + "loss": 0.8203, + "step": 1457 + }, + { + "epoch": 0.28, + "learning_rate": 1.6882377384361562e-05, + "loss": 0.8165, + "step": 1458 + }, + { + "epoch": 0.28, + "learning_rate": 1.6877852968962363e-05, + "loss": 0.8386, + "step": 1459 + }, + { + "epoch": 0.28, + "learning_rate": 1.687332588016342e-05, + "loss": 0.8612, + "step": 1460 + }, + { + "epoch": 0.28, + "learning_rate": 1.6868796119724396e-05, + "loss": 0.7903, + "step": 1461 + }, + { + "epoch": 0.28, + "learning_rate": 1.6864263689406004e-05, + "loss": 0.9177, + "step": 1462 + }, + { + "epoch": 0.28, + "learning_rate": 1.685972859096997e-05, + "loss": 0.8649, + "step": 1463 + }, + { + "epoch": 0.28, + "learning_rate": 1.6855190826179088e-05, + "loss": 0.8463, + "step": 1464 + }, + { + "epoch": 0.28, + "learning_rate": 1.6850650396797163e-05, + "loss": 0.8863, + "step": 1465 + }, + { + "epoch": 0.28, + "learning_rate": 1.6846107304589047e-05, + "loss": 0.8522, + "step": 1466 + }, + { + "epoch": 0.28, + "learning_rate": 1.6841561551320628e-05, + "loss": 0.8844, + "step": 1467 + }, + { + "epoch": 0.28, + "learning_rate": 1.6837013138758824e-05, + "loss": 0.8606, + "step": 1468 + }, + { + "epoch": 0.28, + "learning_rate": 1.6832462068671588e-05, + "loss": 0.8243, + "step": 1469 + }, + { + "epoch": 0.28, + "learning_rate": 1.682790834282791e-05, + "loss": 0.7835, + "step": 1470 + }, + { + "epoch": 0.28, + "learning_rate": 1.6823351962997807e-05, + "loss": 0.7769, + "step": 1471 + }, + { + "epoch": 0.28, + "learning_rate": 1.6818792930952327e-05, + "loss": 0.8679, + "step": 1472 + }, + { + "epoch": 0.28, + "learning_rate": 1.6814231248463556e-05, + "loss": 0.939, + "step": 1473 + }, + { + "epoch": 0.28, + "learning_rate": 1.6809666917304603e-05, + "loss": 0.8642, + "step": 1474 + }, + { + "epoch": 0.28, + "learning_rate": 1.680509993924961e-05, + "loss": 0.886, + "step": 1475 + }, + { + "epoch": 0.28, + "learning_rate": 1.6800530316073748e-05, + "loss": 0.7648, + "step": 1476 + }, + { + "epoch": 0.28, + "learning_rate": 1.6795958049553208e-05, + "loss": 0.7842, + "step": 1477 + }, + { + "epoch": 0.28, + "learning_rate": 1.6791383141465222e-05, + "loss": 0.8959, + "step": 1478 + }, + { + "epoch": 0.28, + "learning_rate": 1.6786805593588045e-05, + "loss": 0.8031, + "step": 1479 + }, + { + "epoch": 0.28, + "learning_rate": 1.678222540770095e-05, + "loss": 0.8405, + "step": 1480 + }, + { + "epoch": 0.29, + "learning_rate": 1.6777642585584243e-05, + "loss": 0.8619, + "step": 1481 + }, + { + "epoch": 0.29, + "learning_rate": 1.677305712901925e-05, + "loss": 0.8663, + "step": 1482 + }, + { + "epoch": 0.29, + "learning_rate": 1.676846903978833e-05, + "loss": 0.7846, + "step": 1483 + }, + { + "epoch": 0.29, + "learning_rate": 1.6763878319674853e-05, + "loss": 0.8108, + "step": 1484 + }, + { + "epoch": 0.29, + "learning_rate": 1.6759284970463215e-05, + "loss": 0.8314, + "step": 1485 + }, + { + "epoch": 0.29, + "learning_rate": 1.6754688993938843e-05, + "loss": 0.9031, + "step": 1486 + }, + { + "epoch": 0.29, + "learning_rate": 1.6750090391888175e-05, + "loss": 0.8558, + "step": 1487 + }, + { + "epoch": 0.29, + "learning_rate": 1.6745489166098672e-05, + "loss": 0.9226, + "step": 1488 + }, + { + "epoch": 0.29, + "learning_rate": 1.6740885318358824e-05, + "loss": 0.8329, + "step": 1489 + }, + { + "epoch": 0.29, + "learning_rate": 1.6736278850458122e-05, + "loss": 0.8743, + "step": 1490 + }, + { + "epoch": 0.29, + "learning_rate": 1.6731669764187087e-05, + "loss": 0.8657, + "step": 1491 + }, + { + "epoch": 0.29, + "learning_rate": 1.6727058061337264e-05, + "loss": 0.8845, + "step": 1492 + }, + { + "epoch": 0.29, + "learning_rate": 1.6722443743701194e-05, + "loss": 0.8871, + "step": 1493 + }, + { + "epoch": 0.29, + "learning_rate": 1.671782681307246e-05, + "loss": 0.7874, + "step": 1494 + }, + { + "epoch": 0.29, + "learning_rate": 1.671320727124565e-05, + "loss": 0.8655, + "step": 1495 + }, + { + "epoch": 0.29, + "learning_rate": 1.6708585120016353e-05, + "loss": 0.8773, + "step": 1496 + }, + { + "epoch": 0.29, + "learning_rate": 1.670396036118119e-05, + "loss": 0.7845, + "step": 1497 + }, + { + "epoch": 0.29, + "learning_rate": 1.6699332996537795e-05, + "loss": 0.8221, + "step": 1498 + }, + { + "epoch": 0.29, + "learning_rate": 1.6694703027884802e-05, + "loss": 0.8959, + "step": 1499 + }, + { + "epoch": 0.29, + "learning_rate": 1.669007045702187e-05, + "loss": 0.8668, + "step": 1500 + }, + { + "epoch": 0.29, + "learning_rate": 1.668543528574967e-05, + "loss": 1.8623, + "step": 1501 + }, + { + "epoch": 0.29, + "learning_rate": 1.6680797515869868e-05, + "loss": 0.8455, + "step": 1502 + }, + { + "epoch": 0.29, + "learning_rate": 1.6676157149185152e-05, + "loss": 0.8584, + "step": 1503 + }, + { + "epoch": 0.29, + "learning_rate": 1.6671514187499226e-05, + "loss": 0.7923, + "step": 1504 + }, + { + "epoch": 0.29, + "learning_rate": 1.6666868632616786e-05, + "loss": 0.845, + "step": 1505 + }, + { + "epoch": 0.29, + "learning_rate": 1.6662220486343553e-05, + "loss": 0.8557, + "step": 1506 + }, + { + "epoch": 0.29, + "learning_rate": 1.6657569750486238e-05, + "loss": 0.8348, + "step": 1507 + }, + { + "epoch": 0.29, + "learning_rate": 1.665291642685257e-05, + "loss": 0.9038, + "step": 1508 + }, + { + "epoch": 0.29, + "learning_rate": 1.6648260517251286e-05, + "loss": 0.9114, + "step": 1509 + }, + { + "epoch": 0.29, + "learning_rate": 1.6643602023492116e-05, + "loss": 0.8913, + "step": 1510 + }, + { + "epoch": 0.29, + "learning_rate": 1.6638940947385806e-05, + "loss": 0.7826, + "step": 1511 + }, + { + "epoch": 0.29, + "learning_rate": 1.6634277290744105e-05, + "loss": 0.8305, + "step": 1512 + }, + { + "epoch": 0.29, + "learning_rate": 1.6629611055379754e-05, + "loss": 1.6209, + "step": 1513 + }, + { + "epoch": 0.29, + "learning_rate": 1.662494224310651e-05, + "loss": 0.8451, + "step": 1514 + }, + { + "epoch": 0.29, + "learning_rate": 1.662027085573912e-05, + "loss": 1.7254, + "step": 1515 + }, + { + "epoch": 0.29, + "learning_rate": 1.6615596895093342e-05, + "loss": 0.7847, + "step": 1516 + }, + { + "epoch": 0.29, + "learning_rate": 1.6610920362985932e-05, + "loss": 0.8087, + "step": 1517 + }, + { + "epoch": 0.29, + "learning_rate": 1.6606241261234637e-05, + "loss": 0.8333, + "step": 1518 + }, + { + "epoch": 0.29, + "learning_rate": 1.660155959165821e-05, + "loss": 0.8033, + "step": 1519 + }, + { + "epoch": 0.29, + "learning_rate": 1.6596875356076403e-05, + "loss": 0.8543, + "step": 1520 + }, + { + "epoch": 0.29, + "learning_rate": 1.659218855630997e-05, + "loss": 0.8511, + "step": 1521 + }, + { + "epoch": 0.29, + "learning_rate": 1.6587499194180644e-05, + "loss": 0.8544, + "step": 1522 + }, + { + "epoch": 0.29, + "learning_rate": 1.6582807271511172e-05, + "loss": 0.8746, + "step": 1523 + }, + { + "epoch": 0.29, + "learning_rate": 1.657811279012529e-05, + "loss": 0.8305, + "step": 1524 + }, + { + "epoch": 0.29, + "learning_rate": 1.6573415751847722e-05, + "loss": 0.8515, + "step": 1525 + }, + { + "epoch": 0.29, + "learning_rate": 1.6568716158504194e-05, + "loss": 0.8408, + "step": 1526 + }, + { + "epoch": 0.29, + "learning_rate": 1.656401401192143e-05, + "loss": 0.8428, + "step": 1527 + }, + { + "epoch": 0.29, + "learning_rate": 1.655930931392713e-05, + "loss": 0.8743, + "step": 1528 + }, + { + "epoch": 0.29, + "learning_rate": 1.6554602066350003e-05, + "loss": 0.7795, + "step": 1529 + }, + { + "epoch": 0.29, + "learning_rate": 1.654989227101974e-05, + "loss": 0.8939, + "step": 1530 + }, + { + "epoch": 0.29, + "learning_rate": 1.6545179929767017e-05, + "loss": 0.8193, + "step": 1531 + }, + { + "epoch": 0.29, + "learning_rate": 1.6540465044423513e-05, + "loss": 0.8758, + "step": 1532 + }, + { + "epoch": 0.3, + "learning_rate": 1.6535747616821884e-05, + "loss": 0.8739, + "step": 1533 + }, + { + "epoch": 0.3, + "learning_rate": 1.6531027648795784e-05, + "loss": 0.8514, + "step": 1534 + }, + { + "epoch": 0.3, + "learning_rate": 1.652630514217985e-05, + "loss": 0.8472, + "step": 1535 + }, + { + "epoch": 0.3, + "learning_rate": 1.65215800988097e-05, + "loss": 0.8152, + "step": 1536 + }, + { + "epoch": 0.3, + "learning_rate": 1.6516852520521946e-05, + "loss": 0.83, + "step": 1537 + }, + { + "epoch": 0.3, + "learning_rate": 1.6512122409154184e-05, + "loss": 0.8183, + "step": 1538 + }, + { + "epoch": 0.3, + "learning_rate": 1.6507389766544997e-05, + "loss": 1.8315, + "step": 1539 + }, + { + "epoch": 0.3, + "learning_rate": 1.6502654594533938e-05, + "loss": 0.7601, + "step": 1540 + }, + { + "epoch": 0.3, + "learning_rate": 1.649791689496156e-05, + "loss": 0.8073, + "step": 1541 + }, + { + "epoch": 0.3, + "learning_rate": 1.6493176669669396e-05, + "loss": 0.8772, + "step": 1542 + }, + { + "epoch": 0.3, + "learning_rate": 1.648843392049995e-05, + "loss": 0.8429, + "step": 1543 + }, + { + "epoch": 0.3, + "learning_rate": 1.6483688649296714e-05, + "loss": 0.8025, + "step": 1544 + }, + { + "epoch": 0.3, + "learning_rate": 1.6478940857904163e-05, + "loss": 0.8581, + "step": 1545 + }, + { + "epoch": 0.3, + "learning_rate": 1.6474190548167744e-05, + "loss": 0.8801, + "step": 1546 + }, + { + "epoch": 0.3, + "learning_rate": 1.6469437721933892e-05, + "loss": 0.8358, + "step": 1547 + }, + { + "epoch": 0.3, + "learning_rate": 1.6464682381050015e-05, + "loss": 0.8258, + "step": 1548 + }, + { + "epoch": 0.3, + "learning_rate": 1.6459924527364496e-05, + "loss": 0.8601, + "step": 1549 + }, + { + "epoch": 0.3, + "learning_rate": 1.64551641627267e-05, + "loss": 0.8507, + "step": 1550 + }, + { + "epoch": 0.3, + "learning_rate": 1.645040128898697e-05, + "loss": 0.8482, + "step": 1551 + }, + { + "epoch": 0.3, + "learning_rate": 1.6445635907996612e-05, + "loss": 0.8066, + "step": 1552 + }, + { + "epoch": 0.3, + "learning_rate": 1.6440868021607915e-05, + "loss": 0.8264, + "step": 1553 + }, + { + "epoch": 0.3, + "learning_rate": 1.6436097631674148e-05, + "loss": 0.888, + "step": 1554 + }, + { + "epoch": 0.3, + "learning_rate": 1.643132474004954e-05, + "loss": 0.7981, + "step": 1555 + }, + { + "epoch": 0.3, + "learning_rate": 1.64265493485893e-05, + "loss": 0.8505, + "step": 1556 + }, + { + "epoch": 0.3, + "learning_rate": 1.6421771459149615e-05, + "loss": 0.8453, + "step": 1557 + }, + { + "epoch": 0.3, + "learning_rate": 1.6416991073587628e-05, + "loss": 0.8966, + "step": 1558 + }, + { + "epoch": 0.3, + "learning_rate": 1.641220819376146e-05, + "loss": 0.8158, + "step": 1559 + }, + { + "epoch": 0.3, + "learning_rate": 1.6407422821530207e-05, + "loss": 0.874, + "step": 1560 + }, + { + "epoch": 0.3, + "learning_rate": 1.640263495875392e-05, + "loss": 0.8357, + "step": 1561 + }, + { + "epoch": 0.3, + "learning_rate": 1.639784460729363e-05, + "loss": 0.8826, + "step": 1562 + }, + { + "epoch": 0.3, + "learning_rate": 1.6393051769011333e-05, + "loss": 0.8547, + "step": 1563 + }, + { + "epoch": 0.3, + "learning_rate": 1.6388256445769987e-05, + "loss": 0.8261, + "step": 1564 + }, + { + "epoch": 0.3, + "learning_rate": 1.6383458639433522e-05, + "loss": 1.8858, + "step": 1565 + }, + { + "epoch": 0.3, + "learning_rate": 1.637865835186683e-05, + "loss": 0.9009, + "step": 1566 + }, + { + "epoch": 0.3, + "learning_rate": 1.6373855584935765e-05, + "loss": 0.8377, + "step": 1567 + }, + { + "epoch": 0.3, + "learning_rate": 1.6369050340507152e-05, + "loss": 0.85, + "step": 1568 + }, + { + "epoch": 0.3, + "learning_rate": 1.6364242620448767e-05, + "loss": 0.893, + "step": 1569 + }, + { + "epoch": 0.3, + "learning_rate": 1.6359432426629363e-05, + "loss": 0.8388, + "step": 1570 + }, + { + "epoch": 0.3, + "learning_rate": 1.635461976091864e-05, + "loss": 0.8559, + "step": 1571 + }, + { + "epoch": 0.3, + "learning_rate": 1.6349804625187275e-05, + "loss": 0.8778, + "step": 1572 + }, + { + "epoch": 0.3, + "learning_rate": 1.634498702130689e-05, + "loss": 0.7816, + "step": 1573 + }, + { + "epoch": 0.3, + "learning_rate": 1.634016695115007e-05, + "loss": 0.9, + "step": 1574 + }, + { + "epoch": 0.3, + "learning_rate": 1.633534441659037e-05, + "loss": 0.8755, + "step": 1575 + }, + { + "epoch": 0.3, + "learning_rate": 1.633051941950228e-05, + "loss": 0.8531, + "step": 1576 + }, + { + "epoch": 0.3, + "learning_rate": 1.632569196176128e-05, + "loss": 0.7804, + "step": 1577 + }, + { + "epoch": 0.3, + "learning_rate": 1.632086204524377e-05, + "loss": 0.8402, + "step": 1578 + }, + { + "epoch": 0.3, + "learning_rate": 1.6316029671827137e-05, + "loss": 0.8618, + "step": 1579 + }, + { + "epoch": 0.3, + "learning_rate": 1.6311194843389697e-05, + "loss": 0.7932, + "step": 1580 + }, + { + "epoch": 0.3, + "learning_rate": 1.6306357561810743e-05, + "loss": 0.8246, + "step": 1581 + }, + { + "epoch": 0.3, + "learning_rate": 1.63015178289705e-05, + "loss": 0.8525, + "step": 1582 + }, + { + "epoch": 0.3, + "learning_rate": 1.6296675646750168e-05, + "loss": 0.8044, + "step": 1583 + }, + { + "epoch": 0.3, + "learning_rate": 1.629183101703188e-05, + "loss": 0.8145, + "step": 1584 + }, + { + "epoch": 0.31, + "learning_rate": 1.6286983941698737e-05, + "loss": 0.8282, + "step": 1585 + }, + { + "epoch": 0.31, + "learning_rate": 1.6282134422634778e-05, + "loss": 0.8566, + "step": 1586 + }, + { + "epoch": 0.31, + "learning_rate": 1.627728246172499e-05, + "loss": 0.8895, + "step": 1587 + }, + { + "epoch": 0.31, + "learning_rate": 1.6272428060855316e-05, + "loss": 0.8158, + "step": 1588 + }, + { + "epoch": 0.31, + "learning_rate": 1.626757122191265e-05, + "loss": 0.8273, + "step": 1589 + }, + { + "epoch": 0.31, + "learning_rate": 1.6262711946784835e-05, + "loss": 0.7935, + "step": 1590 + }, + { + "epoch": 0.31, + "learning_rate": 1.6257850237360647e-05, + "loss": 0.8395, + "step": 1591 + }, + { + "epoch": 0.31, + "learning_rate": 1.625298609552982e-05, + "loss": 0.8705, + "step": 1592 + }, + { + "epoch": 0.31, + "learning_rate": 1.6248119523183032e-05, + "loss": 0.8016, + "step": 1593 + }, + { + "epoch": 0.31, + "learning_rate": 1.6243250522211903e-05, + "loss": 0.805, + "step": 1594 + }, + { + "epoch": 0.31, + "learning_rate": 1.6238379094509e-05, + "loss": 0.8285, + "step": 1595 + }, + { + "epoch": 0.31, + "learning_rate": 1.623350524196783e-05, + "loss": 0.8699, + "step": 1596 + }, + { + "epoch": 0.31, + "learning_rate": 1.6228628966482844e-05, + "loss": 0.8717, + "step": 1597 + }, + { + "epoch": 0.31, + "learning_rate": 1.6223750269949433e-05, + "loss": 0.8302, + "step": 1598 + }, + { + "epoch": 0.31, + "learning_rate": 1.6218869154263934e-05, + "loss": 0.8422, + "step": 1599 + }, + { + "epoch": 0.31, + "learning_rate": 1.6213985621323624e-05, + "loss": 0.8615, + "step": 1600 + }, + { + "epoch": 0.31, + "learning_rate": 1.6209099673026706e-05, + "loss": 0.8357, + "step": 1601 + }, + { + "epoch": 0.31, + "learning_rate": 1.620421131127235e-05, + "loss": 0.7996, + "step": 1602 + }, + { + "epoch": 0.31, + "learning_rate": 1.6199320537960627e-05, + "loss": 0.7845, + "step": 1603 + }, + { + "epoch": 0.31, + "learning_rate": 1.6194427354992578e-05, + "loss": 0.8044, + "step": 1604 + }, + { + "epoch": 0.31, + "learning_rate": 1.6189531764270167e-05, + "loss": 0.864, + "step": 1605 + }, + { + "epoch": 0.31, + "learning_rate": 1.6184633767696292e-05, + "loss": 0.7957, + "step": 1606 + }, + { + "epoch": 0.31, + "learning_rate": 1.617973336717479e-05, + "loss": 0.8188, + "step": 1607 + }, + { + "epoch": 0.31, + "learning_rate": 1.6174830564610426e-05, + "loss": 0.8218, + "step": 1608 + }, + { + "epoch": 0.31, + "learning_rate": 1.6169925361908912e-05, + "loss": 0.9085, + "step": 1609 + }, + { + "epoch": 0.31, + "learning_rate": 1.6165017760976878e-05, + "loss": 0.8224, + "step": 1610 + }, + { + "epoch": 0.31, + "learning_rate": 1.61601077637219e-05, + "loss": 0.8329, + "step": 1611 + }, + { + "epoch": 0.31, + "learning_rate": 1.6155195372052473e-05, + "loss": 0.8712, + "step": 1612 + }, + { + "epoch": 0.31, + "learning_rate": 1.615028058787803e-05, + "loss": 0.8563, + "step": 1613 + }, + { + "epoch": 0.31, + "learning_rate": 1.6145363413108927e-05, + "loss": 0.8338, + "step": 1614 + }, + { + "epoch": 0.31, + "learning_rate": 1.6140443849656466e-05, + "loss": 0.8401, + "step": 1615 + }, + { + "epoch": 0.31, + "learning_rate": 1.6135521899432854e-05, + "loss": 0.8838, + "step": 1616 + }, + { + "epoch": 0.31, + "learning_rate": 1.6130597564351245e-05, + "loss": 0.802, + "step": 1617 + }, + { + "epoch": 0.31, + "learning_rate": 1.6125670846325707e-05, + "loss": 0.8218, + "step": 1618 + }, + { + "epoch": 0.31, + "learning_rate": 1.612074174727125e-05, + "loss": 0.849, + "step": 1619 + }, + { + "epoch": 0.31, + "learning_rate": 1.6115810269103783e-05, + "loss": 0.8457, + "step": 1620 + }, + { + "epoch": 0.31, + "learning_rate": 1.6110876413740168e-05, + "loss": 0.8197, + "step": 1621 + }, + { + "epoch": 0.31, + "learning_rate": 1.6105940183098176e-05, + "loss": 0.8825, + "step": 1622 + }, + { + "epoch": 0.31, + "learning_rate": 1.6101001579096504e-05, + "loss": 0.8639, + "step": 1623 + }, + { + "epoch": 0.31, + "learning_rate": 1.6096060603654775e-05, + "loss": 1.6711, + "step": 1624 + }, + { + "epoch": 0.31, + "learning_rate": 1.6091117258693524e-05, + "loss": 1.7162, + "step": 1625 + }, + { + "epoch": 0.31, + "learning_rate": 1.6086171546134216e-05, + "loss": 0.8373, + "step": 1626 + }, + { + "epoch": 0.31, + "learning_rate": 1.6081223467899236e-05, + "loss": 0.8117, + "step": 1627 + }, + { + "epoch": 0.31, + "learning_rate": 1.6076273025911886e-05, + "loss": 0.8525, + "step": 1628 + }, + { + "epoch": 0.31, + "learning_rate": 1.6071320222096387e-05, + "loss": 0.7917, + "step": 1629 + }, + { + "epoch": 0.31, + "learning_rate": 1.6066365058377877e-05, + "loss": 0.8782, + "step": 1630 + }, + { + "epoch": 0.31, + "learning_rate": 1.606140753668241e-05, + "loss": 0.8134, + "step": 1631 + }, + { + "epoch": 0.31, + "learning_rate": 1.605644765893697e-05, + "loss": 1.6413, + "step": 1632 + }, + { + "epoch": 0.31, + "learning_rate": 1.6051485427069434e-05, + "loss": 0.8495, + "step": 1633 + }, + { + "epoch": 0.31, + "learning_rate": 1.604652084300861e-05, + "loss": 0.7985, + "step": 1634 + }, + { + "epoch": 0.31, + "learning_rate": 1.6041553908684214e-05, + "loss": 0.8142, + "step": 1635 + }, + { + "epoch": 0.31, + "learning_rate": 1.603658462602688e-05, + "loss": 0.8213, + "step": 1636 + }, + { + "epoch": 0.32, + "learning_rate": 1.6031612996968157e-05, + "loss": 0.8295, + "step": 1637 + }, + { + "epoch": 0.32, + "learning_rate": 1.602663902344049e-05, + "loss": 0.7917, + "step": 1638 + }, + { + "epoch": 0.32, + "learning_rate": 1.602166270737726e-05, + "loss": 0.8858, + "step": 1639 + }, + { + "epoch": 0.32, + "learning_rate": 1.6016684050712735e-05, + "loss": 0.8878, + "step": 1640 + }, + { + "epoch": 0.32, + "learning_rate": 1.6011703055382107e-05, + "loss": 0.7884, + "step": 1641 + }, + { + "epoch": 0.32, + "learning_rate": 1.6006719723321477e-05, + "loss": 0.783, + "step": 1642 + }, + { + "epoch": 0.32, + "learning_rate": 1.6001734056467844e-05, + "loss": 0.8655, + "step": 1643 + }, + { + "epoch": 0.32, + "learning_rate": 1.5996746056759123e-05, + "loss": 0.7917, + "step": 1644 + }, + { + "epoch": 0.32, + "learning_rate": 1.5991755726134134e-05, + "loss": 0.8301, + "step": 1645 + }, + { + "epoch": 0.32, + "learning_rate": 1.5986763066532608e-05, + "loss": 1.6918, + "step": 1646 + }, + { + "epoch": 0.32, + "learning_rate": 1.598176807989517e-05, + "loss": 0.8099, + "step": 1647 + }, + { + "epoch": 0.32, + "learning_rate": 1.5976770768163352e-05, + "loss": 0.8558, + "step": 1648 + }, + { + "epoch": 0.32, + "learning_rate": 1.59717711332796e-05, + "loss": 0.7908, + "step": 1649 + }, + { + "epoch": 0.32, + "learning_rate": 1.5966769177187254e-05, + "loss": 0.787, + "step": 1650 + }, + { + "epoch": 0.32, + "learning_rate": 1.5961764901830563e-05, + "loss": 0.8302, + "step": 1651 + }, + { + "epoch": 0.32, + "learning_rate": 1.5956758309154664e-05, + "loss": 0.853, + "step": 1652 + }, + { + "epoch": 0.32, + "learning_rate": 1.595174940110561e-05, + "loss": 0.885, + "step": 1653 + }, + { + "epoch": 0.32, + "learning_rate": 1.594673817963035e-05, + "loss": 0.84, + "step": 1654 + }, + { + "epoch": 0.32, + "learning_rate": 1.5941724646676725e-05, + "loss": 0.8177, + "step": 1655 + }, + { + "epoch": 0.32, + "learning_rate": 1.5936708804193478e-05, + "loss": 0.844, + "step": 1656 + }, + { + "epoch": 0.32, + "learning_rate": 1.5931690654130255e-05, + "loss": 0.8786, + "step": 1657 + }, + { + "epoch": 0.32, + "learning_rate": 1.5926670198437596e-05, + "loss": 0.8393, + "step": 1658 + }, + { + "epoch": 0.32, + "learning_rate": 1.5921647439066933e-05, + "loss": 0.8444, + "step": 1659 + }, + { + "epoch": 0.32, + "learning_rate": 1.59166223779706e-05, + "loss": 0.8338, + "step": 1660 + }, + { + "epoch": 0.32, + "learning_rate": 1.5911595017101817e-05, + "loss": 0.7944, + "step": 1661 + }, + { + "epoch": 0.32, + "learning_rate": 1.590656535841471e-05, + "loss": 0.8133, + "step": 1662 + }, + { + "epoch": 0.32, + "learning_rate": 1.5901533403864286e-05, + "loss": 0.8527, + "step": 1663 + }, + { + "epoch": 0.32, + "learning_rate": 1.5896499155406453e-05, + "loss": 0.8175, + "step": 1664 + }, + { + "epoch": 0.32, + "learning_rate": 1.589146261499801e-05, + "loss": 0.8081, + "step": 1665 + }, + { + "epoch": 0.32, + "learning_rate": 1.5886423784596635e-05, + "loss": 0.851, + "step": 1666 + }, + { + "epoch": 0.32, + "learning_rate": 1.5881382666160917e-05, + "loss": 0.8288, + "step": 1667 + }, + { + "epoch": 0.32, + "learning_rate": 1.5876339261650313e-05, + "loss": 1.6439, + "step": 1668 + }, + { + "epoch": 0.32, + "learning_rate": 1.5871293573025188e-05, + "loss": 0.8485, + "step": 1669 + }, + { + "epoch": 0.32, + "learning_rate": 1.5866245602246775e-05, + "loss": 0.8494, + "step": 1670 + }, + { + "epoch": 0.32, + "learning_rate": 1.586119535127721e-05, + "loss": 0.8036, + "step": 1671 + }, + { + "epoch": 0.32, + "learning_rate": 1.585614282207951e-05, + "loss": 1.6353, + "step": 1672 + }, + { + "epoch": 0.32, + "learning_rate": 1.5851088016617575e-05, + "loss": 0.8154, + "step": 1673 + }, + { + "epoch": 0.32, + "learning_rate": 1.5846030936856193e-05, + "loss": 0.8676, + "step": 1674 + }, + { + "epoch": 0.32, + "learning_rate": 1.5840971584761037e-05, + "loss": 0.8256, + "step": 1675 + }, + { + "epoch": 0.32, + "learning_rate": 1.5835909962298654e-05, + "loss": 0.8608, + "step": 1676 + }, + { + "epoch": 0.32, + "learning_rate": 1.5830846071436492e-05, + "loss": 0.8425, + "step": 1677 + }, + { + "epoch": 0.32, + "learning_rate": 1.582577991414286e-05, + "loss": 0.8412, + "step": 1678 + }, + { + "epoch": 0.32, + "learning_rate": 1.5820711492386963e-05, + "loss": 0.9138, + "step": 1679 + }, + { + "epoch": 0.32, + "learning_rate": 1.5815640808138876e-05, + "loss": 0.7383, + "step": 1680 + }, + { + "epoch": 0.32, + "learning_rate": 1.581056786336956e-05, + "loss": 0.7589, + "step": 1681 + }, + { + "epoch": 0.32, + "learning_rate": 1.5805492660050852e-05, + "loss": 0.7716, + "step": 1682 + }, + { + "epoch": 0.32, + "learning_rate": 1.580041520015547e-05, + "loss": 0.8291, + "step": 1683 + }, + { + "epoch": 0.32, + "learning_rate": 1.5795335485657003e-05, + "loss": 0.8508, + "step": 1684 + }, + { + "epoch": 0.32, + "learning_rate": 1.5790253518529923e-05, + "loss": 0.8638, + "step": 1685 + }, + { + "epoch": 0.32, + "learning_rate": 1.5785169300749576e-05, + "loss": 0.7749, + "step": 1686 + }, + { + "epoch": 0.32, + "learning_rate": 1.578008283429217e-05, + "loss": 0.8065, + "step": 1687 + }, + { + "epoch": 0.32, + "learning_rate": 1.5774994121134816e-05, + "loss": 0.7763, + "step": 1688 + }, + { + "epoch": 0.33, + "learning_rate": 1.5769903163255468e-05, + "loss": 0.8204, + "step": 1689 + }, + { + "epoch": 0.33, + "learning_rate": 1.576480996263297e-05, + "loss": 0.8114, + "step": 1690 + }, + { + "epoch": 0.33, + "learning_rate": 1.5759714521247036e-05, + "loss": 1.5978, + "step": 1691 + }, + { + "epoch": 0.33, + "learning_rate": 1.575461684107824e-05, + "loss": 0.8252, + "step": 1692 + }, + { + "epoch": 0.33, + "learning_rate": 1.574951692410804e-05, + "loss": 0.8237, + "step": 1693 + }, + { + "epoch": 0.33, + "learning_rate": 1.5744414772318756e-05, + "loss": 0.7976, + "step": 1694 + }, + { + "epoch": 0.33, + "learning_rate": 1.5739310387693578e-05, + "loss": 0.8221, + "step": 1695 + }, + { + "epoch": 0.33, + "learning_rate": 1.5734203772216564e-05, + "loss": 0.851, + "step": 1696 + }, + { + "epoch": 0.33, + "learning_rate": 1.5729094927872642e-05, + "loss": 0.864, + "step": 1697 + }, + { + "epoch": 0.33, + "learning_rate": 1.5723983856647595e-05, + "loss": 0.8408, + "step": 1698 + }, + { + "epoch": 0.33, + "learning_rate": 1.5718870560528096e-05, + "loss": 0.8395, + "step": 1699 + }, + { + "epoch": 0.33, + "learning_rate": 1.5713755041501652e-05, + "loss": 0.8535, + "step": 1700 + }, + { + "epoch": 0.33, + "learning_rate": 1.5708637301556657e-05, + "loss": 0.8563, + "step": 1701 + }, + { + "epoch": 0.33, + "learning_rate": 1.5703517342682357e-05, + "loss": 0.833, + "step": 1702 + }, + { + "epoch": 0.33, + "learning_rate": 1.5698395166868867e-05, + "loss": 0.8983, + "step": 1703 + }, + { + "epoch": 0.33, + "learning_rate": 1.5693270776107157e-05, + "loss": 0.746, + "step": 1704 + }, + { + "epoch": 0.33, + "learning_rate": 1.5688144172389067e-05, + "loss": 0.8429, + "step": 1705 + }, + { + "epoch": 0.33, + "learning_rate": 1.5683015357707282e-05, + "loss": 0.7763, + "step": 1706 + }, + { + "epoch": 0.33, + "learning_rate": 1.567788433405537e-05, + "loss": 0.8275, + "step": 1707 + }, + { + "epoch": 0.33, + "learning_rate": 1.5672751103427733e-05, + "loss": 0.8128, + "step": 1708 + }, + { + "epoch": 0.33, + "learning_rate": 1.566761566781964e-05, + "loss": 0.8845, + "step": 1709 + }, + { + "epoch": 0.33, + "learning_rate": 1.5662478029227225e-05, + "loss": 0.8889, + "step": 1710 + }, + { + "epoch": 0.33, + "learning_rate": 1.5657338189647472e-05, + "loss": 0.8327, + "step": 1711 + }, + { + "epoch": 0.33, + "learning_rate": 1.5652196151078218e-05, + "loss": 0.854, + "step": 1712 + }, + { + "epoch": 0.33, + "learning_rate": 1.5647051915518154e-05, + "loss": 0.8242, + "step": 1713 + }, + { + "epoch": 0.33, + "learning_rate": 1.5641905484966834e-05, + "loss": 0.8747, + "step": 1714 + }, + { + "epoch": 0.33, + "learning_rate": 1.5636756861424656e-05, + "loss": 0.8797, + "step": 1715 + }, + { + "epoch": 0.33, + "learning_rate": 1.5631606046892877e-05, + "loss": 1.6012, + "step": 1716 + }, + { + "epoch": 0.33, + "learning_rate": 1.5626453043373598e-05, + "loss": 0.8517, + "step": 1717 + }, + { + "epoch": 0.33, + "learning_rate": 1.5621297852869778e-05, + "loss": 0.8197, + "step": 1718 + }, + { + "epoch": 0.33, + "learning_rate": 1.561614047738522e-05, + "loss": 0.825, + "step": 1719 + }, + { + "epoch": 0.33, + "learning_rate": 1.5610980918924586e-05, + "loss": 0.8355, + "step": 1720 + }, + { + "epoch": 0.33, + "learning_rate": 1.5605819179493374e-05, + "loss": 0.8437, + "step": 1721 + }, + { + "epoch": 0.33, + "learning_rate": 1.5600655261097938e-05, + "loss": 0.7772, + "step": 1722 + }, + { + "epoch": 0.33, + "learning_rate": 1.5595489165745476e-05, + "loss": 0.8435, + "step": 1723 + }, + { + "epoch": 0.33, + "learning_rate": 1.5590320895444035e-05, + "loss": 0.7808, + "step": 1724 + }, + { + "epoch": 0.33, + "learning_rate": 1.5585150452202502e-05, + "loss": 0.8486, + "step": 1725 + }, + { + "epoch": 0.33, + "learning_rate": 1.5579977838030617e-05, + "loss": 0.8476, + "step": 1726 + }, + { + "epoch": 0.33, + "learning_rate": 1.557480305493895e-05, + "loss": 0.8439, + "step": 1727 + }, + { + "epoch": 0.33, + "learning_rate": 1.5569626104938934e-05, + "loss": 0.8229, + "step": 1728 + }, + { + "epoch": 0.33, + "learning_rate": 1.556444699004283e-05, + "loss": 0.8184, + "step": 1729 + }, + { + "epoch": 0.33, + "learning_rate": 1.5559265712263737e-05, + "loss": 0.82, + "step": 1730 + }, + { + "epoch": 0.33, + "learning_rate": 1.5554082273615608e-05, + "loss": 0.8273, + "step": 1731 + }, + { + "epoch": 0.33, + "learning_rate": 1.5548896676113223e-05, + "loss": 0.87, + "step": 1732 + }, + { + "epoch": 0.33, + "learning_rate": 1.5543708921772217e-05, + "loss": 0.7973, + "step": 1733 + }, + { + "epoch": 0.33, + "learning_rate": 1.5538519012609043e-05, + "loss": 0.8263, + "step": 1734 + }, + { + "epoch": 0.33, + "learning_rate": 1.553332695064101e-05, + "loss": 0.8861, + "step": 1735 + }, + { + "epoch": 0.33, + "learning_rate": 1.5528132737886252e-05, + "loss": 0.8313, + "step": 1736 + }, + { + "epoch": 0.33, + "learning_rate": 1.5522936376363747e-05, + "loss": 0.8094, + "step": 1737 + }, + { + "epoch": 0.33, + "learning_rate": 1.55177378680933e-05, + "loss": 0.8757, + "step": 1738 + }, + { + "epoch": 0.33, + "learning_rate": 1.551253721509556e-05, + "loss": 0.7988, + "step": 1739 + }, + { + "epoch": 0.33, + "learning_rate": 1.5507334419392e-05, + "loss": 0.7982, + "step": 1740 + }, + { + "epoch": 0.34, + "learning_rate": 1.5502129483004927e-05, + "loss": 0.8332, + "step": 1741 + }, + { + "epoch": 0.34, + "learning_rate": 1.5496922407957492e-05, + "loss": 0.8338, + "step": 1742 + }, + { + "epoch": 0.34, + "learning_rate": 1.549171319627366e-05, + "loss": 0.8083, + "step": 1743 + }, + { + "epoch": 0.34, + "learning_rate": 1.5486501849978244e-05, + "loss": 0.8386, + "step": 1744 + }, + { + "epoch": 0.34, + "learning_rate": 1.548128837109687e-05, + "loss": 0.8316, + "step": 1745 + }, + { + "epoch": 0.34, + "learning_rate": 1.547607276165601e-05, + "loss": 0.7864, + "step": 1746 + }, + { + "epoch": 0.34, + "learning_rate": 1.547085502368294e-05, + "loss": 0.8184, + "step": 1747 + }, + { + "epoch": 0.34, + "learning_rate": 1.5465635159205798e-05, + "loss": 1.5694, + "step": 1748 + }, + { + "epoch": 0.34, + "learning_rate": 1.546041317025351e-05, + "loss": 0.8193, + "step": 1749 + }, + { + "epoch": 0.34, + "learning_rate": 1.5455189058855858e-05, + "loss": 0.8109, + "step": 1750 + }, + { + "epoch": 0.34, + "learning_rate": 1.5449962827043433e-05, + "loss": 0.8041, + "step": 1751 + }, + { + "epoch": 0.34, + "learning_rate": 1.5444734476847658e-05, + "loss": 0.8263, + "step": 1752 + }, + { + "epoch": 0.34, + "learning_rate": 1.5439504010300776e-05, + "loss": 0.8267, + "step": 1753 + }, + { + "epoch": 0.34, + "learning_rate": 1.543427142943585e-05, + "loss": 1.6475, + "step": 1754 + }, + { + "epoch": 0.34, + "learning_rate": 1.5429036736286767e-05, + "loss": 0.8478, + "step": 1755 + }, + { + "epoch": 0.34, + "learning_rate": 1.542379993288824e-05, + "loss": 0.8272, + "step": 1756 + }, + { + "epoch": 0.34, + "learning_rate": 1.5418561021275792e-05, + "loss": 0.8087, + "step": 1757 + }, + { + "epoch": 0.34, + "learning_rate": 1.541332000348578e-05, + "loss": 0.8896, + "step": 1758 + }, + { + "epoch": 0.34, + "learning_rate": 1.5408076881555364e-05, + "loss": 0.847, + "step": 1759 + }, + { + "epoch": 0.34, + "learning_rate": 1.540283165752253e-05, + "loss": 0.8583, + "step": 1760 + }, + { + "epoch": 0.34, + "learning_rate": 1.5397584333426083e-05, + "loss": 0.8147, + "step": 1761 + }, + { + "epoch": 0.34, + "learning_rate": 1.539233491130564e-05, + "loss": 0.8321, + "step": 1762 + }, + { + "epoch": 0.34, + "learning_rate": 1.5387083393201633e-05, + "loss": 0.8511, + "step": 1763 + }, + { + "epoch": 0.34, + "learning_rate": 1.5381829781155307e-05, + "loss": 0.8575, + "step": 1764 + }, + { + "epoch": 0.34, + "learning_rate": 1.5376574077208737e-05, + "loss": 0.7854, + "step": 1765 + }, + { + "epoch": 0.34, + "learning_rate": 1.5371316283404786e-05, + "loss": 0.8679, + "step": 1766 + }, + { + "epoch": 0.34, + "learning_rate": 1.536605640178715e-05, + "loss": 0.8858, + "step": 1767 + }, + { + "epoch": 0.34, + "learning_rate": 1.5360794434400322e-05, + "loss": 0.8047, + "step": 1768 + }, + { + "epoch": 0.34, + "learning_rate": 1.5355530383289616e-05, + "loss": 0.796, + "step": 1769 + }, + { + "epoch": 0.34, + "learning_rate": 1.5350264250501154e-05, + "loss": 0.8237, + "step": 1770 + }, + { + "epoch": 0.34, + "learning_rate": 1.534499603808186e-05, + "loss": 0.8459, + "step": 1771 + }, + { + "epoch": 0.34, + "learning_rate": 1.533972574807947e-05, + "loss": 1.5925, + "step": 1772 + }, + { + "epoch": 0.34, + "learning_rate": 1.533445338254254e-05, + "loss": 0.8181, + "step": 1773 + }, + { + "epoch": 0.34, + "learning_rate": 1.5329178943520407e-05, + "loss": 1.4691, + "step": 1774 + }, + { + "epoch": 0.34, + "learning_rate": 1.5323902433063246e-05, + "loss": 0.8129, + "step": 1775 + }, + { + "epoch": 0.34, + "learning_rate": 1.5318623853222006e-05, + "loss": 0.81, + "step": 1776 + }, + { + "epoch": 0.34, + "learning_rate": 1.5313343206048458e-05, + "loss": 0.8448, + "step": 1777 + }, + { + "epoch": 0.34, + "learning_rate": 1.5308060493595173e-05, + "loss": 0.8518, + "step": 1778 + }, + { + "epoch": 0.34, + "learning_rate": 1.5302775717915528e-05, + "loss": 0.859, + "step": 1779 + }, + { + "epoch": 0.34, + "learning_rate": 1.5297488881063696e-05, + "loss": 0.758, + "step": 1780 + }, + { + "epoch": 0.34, + "learning_rate": 1.5292199985094652e-05, + "loss": 0.8031, + "step": 1781 + }, + { + "epoch": 0.34, + "learning_rate": 1.5286909032064174e-05, + "loss": 0.807, + "step": 1782 + }, + { + "epoch": 0.34, + "learning_rate": 1.5281616024028844e-05, + "loss": 0.832, + "step": 1783 + }, + { + "epoch": 0.34, + "learning_rate": 1.527632096304603e-05, + "loss": 0.8136, + "step": 1784 + }, + { + "epoch": 0.34, + "learning_rate": 1.5271023851173908e-05, + "loss": 0.828, + "step": 1785 + }, + { + "epoch": 0.34, + "learning_rate": 1.5265724690471454e-05, + "loss": 1.6493, + "step": 1786 + }, + { + "epoch": 0.34, + "learning_rate": 1.5260423482998427e-05, + "loss": 0.8882, + "step": 1787 + }, + { + "epoch": 0.34, + "learning_rate": 1.5255120230815394e-05, + "loss": 0.8552, + "step": 1788 + }, + { + "epoch": 0.34, + "learning_rate": 1.5249814935983713e-05, + "loss": 0.8342, + "step": 1789 + }, + { + "epoch": 0.34, + "learning_rate": 1.5244507600565532e-05, + "loss": 1.6562, + "step": 1790 + }, + { + "epoch": 0.34, + "learning_rate": 1.5239198226623796e-05, + "loss": 0.8741, + "step": 1791 + }, + { + "epoch": 0.34, + "learning_rate": 1.5233886816222247e-05, + "loss": 0.73, + "step": 1792 + }, + { + "epoch": 0.35, + "learning_rate": 1.522857337142541e-05, + "loss": 0.8176, + "step": 1793 + }, + { + "epoch": 0.35, + "learning_rate": 1.5223257894298602e-05, + "loss": 0.8138, + "step": 1794 + }, + { + "epoch": 0.35, + "learning_rate": 1.5217940386907933e-05, + "loss": 0.8376, + "step": 1795 + }, + { + "epoch": 0.35, + "learning_rate": 1.5212620851320305e-05, + "loss": 0.8724, + "step": 1796 + }, + { + "epoch": 0.35, + "learning_rate": 1.52072992896034e-05, + "loss": 0.8471, + "step": 1797 + }, + { + "epoch": 0.35, + "learning_rate": 1.5201975703825698e-05, + "loss": 0.8481, + "step": 1798 + }, + { + "epoch": 0.35, + "learning_rate": 1.5196650096056451e-05, + "loss": 0.7695, + "step": 1799 + }, + { + "epoch": 0.35, + "learning_rate": 1.5191322468365716e-05, + "loss": 0.8064, + "step": 1800 + }, + { + "epoch": 0.35, + "learning_rate": 1.5185992822824318e-05, + "loss": 0.8679, + "step": 1801 + }, + { + "epoch": 0.35, + "learning_rate": 1.5180661161503877e-05, + "loss": 0.7404, + "step": 1802 + }, + { + "epoch": 0.35, + "learning_rate": 1.5175327486476792e-05, + "loss": 0.8415, + "step": 1803 + }, + { + "epoch": 0.35, + "learning_rate": 1.5169991799816247e-05, + "loss": 1.6459, + "step": 1804 + }, + { + "epoch": 0.35, + "learning_rate": 1.5164654103596204e-05, + "loss": 0.8807, + "step": 1805 + }, + { + "epoch": 0.35, + "learning_rate": 1.5159314399891406e-05, + "loss": 0.8816, + "step": 1806 + }, + { + "epoch": 0.35, + "learning_rate": 1.5153972690777386e-05, + "loss": 0.8265, + "step": 1807 + }, + { + "epoch": 0.35, + "learning_rate": 1.5148628978330444e-05, + "loss": 0.8393, + "step": 1808 + }, + { + "epoch": 0.35, + "learning_rate": 1.514328326462767e-05, + "loss": 0.8426, + "step": 1809 + }, + { + "epoch": 0.35, + "learning_rate": 1.513793555174692e-05, + "loss": 0.828, + "step": 1810 + }, + { + "epoch": 0.35, + "learning_rate": 1.5132585841766835e-05, + "loss": 0.7768, + "step": 1811 + }, + { + "epoch": 0.35, + "learning_rate": 1.5127234136766832e-05, + "loss": 0.8207, + "step": 1812 + }, + { + "epoch": 0.35, + "learning_rate": 1.5121880438827101e-05, + "loss": 0.8221, + "step": 1813 + }, + { + "epoch": 0.35, + "learning_rate": 1.5116524750028607e-05, + "loss": 0.821, + "step": 1814 + }, + { + "epoch": 0.35, + "learning_rate": 1.5111167072453091e-05, + "loss": 0.7764, + "step": 1815 + }, + { + "epoch": 0.35, + "learning_rate": 1.5105807408183059e-05, + "loss": 1.5924, + "step": 1816 + }, + { + "epoch": 0.35, + "learning_rate": 1.5100445759301805e-05, + "loss": 0.8031, + "step": 1817 + }, + { + "epoch": 0.35, + "learning_rate": 1.5095082127893377e-05, + "loss": 0.8367, + "step": 1818 + }, + { + "epoch": 0.35, + "learning_rate": 1.508971651604261e-05, + "loss": 0.8099, + "step": 1819 + }, + { + "epoch": 0.35, + "learning_rate": 1.508434892583509e-05, + "loss": 0.8778, + "step": 1820 + }, + { + "epoch": 0.35, + "learning_rate": 1.5078979359357194e-05, + "loss": 0.8771, + "step": 1821 + }, + { + "epoch": 0.35, + "learning_rate": 1.5073607818696043e-05, + "loss": 1.7129, + "step": 1822 + }, + { + "epoch": 0.35, + "learning_rate": 1.5068234305939546e-05, + "loss": 0.8056, + "step": 1823 + }, + { + "epoch": 0.35, + "learning_rate": 1.5062858823176374e-05, + "loss": 0.8486, + "step": 1824 + }, + { + "epoch": 0.35, + "learning_rate": 1.5057481372495948e-05, + "loss": 0.7933, + "step": 1825 + }, + { + "epoch": 0.35, + "learning_rate": 1.5052101955988478e-05, + "loss": 0.7819, + "step": 1826 + }, + { + "epoch": 0.35, + "learning_rate": 1.5046720575744917e-05, + "loss": 1.5546, + "step": 1827 + }, + { + "epoch": 0.35, + "learning_rate": 1.5041337233856998e-05, + "loss": 0.8569, + "step": 1828 + }, + { + "epoch": 0.35, + "learning_rate": 1.5035951932417205e-05, + "loss": 1.4716, + "step": 1829 + }, + { + "epoch": 0.35, + "learning_rate": 1.503056467351879e-05, + "loss": 0.8125, + "step": 1830 + }, + { + "epoch": 0.35, + "learning_rate": 1.5025175459255761e-05, + "loss": 0.8321, + "step": 1831 + }, + { + "epoch": 0.35, + "learning_rate": 1.5019784291722888e-05, + "loss": 0.7877, + "step": 1832 + }, + { + "epoch": 0.35, + "learning_rate": 1.50143911730157e-05, + "loss": 0.8137, + "step": 1833 + }, + { + "epoch": 0.35, + "learning_rate": 1.5008996105230493e-05, + "loss": 0.8091, + "step": 1834 + }, + { + "epoch": 0.35, + "learning_rate": 1.5003599090464307e-05, + "loss": 0.8049, + "step": 1835 + }, + { + "epoch": 0.35, + "learning_rate": 1.4998200130814941e-05, + "loss": 0.8711, + "step": 1836 + }, + { + "epoch": 0.35, + "learning_rate": 1.4992799228380959e-05, + "loss": 0.833, + "step": 1837 + }, + { + "epoch": 0.35, + "learning_rate": 1.4987396385261676e-05, + "loss": 0.7466, + "step": 1838 + }, + { + "epoch": 0.35, + "learning_rate": 1.4981991603557155e-05, + "loss": 0.8551, + "step": 1839 + }, + { + "epoch": 0.35, + "learning_rate": 1.4976584885368221e-05, + "loss": 0.767, + "step": 1840 + }, + { + "epoch": 0.35, + "learning_rate": 1.4971176232796447e-05, + "loss": 0.7866, + "step": 1841 + }, + { + "epoch": 0.35, + "learning_rate": 1.4965765647944161e-05, + "loss": 0.8463, + "step": 1842 + }, + { + "epoch": 0.35, + "learning_rate": 1.4960353132914436e-05, + "loss": 0.8995, + "step": 1843 + }, + { + "epoch": 0.35, + "learning_rate": 1.4954938689811105e-05, + "loss": 0.8723, + "step": 1844 + }, + { + "epoch": 0.36, + "learning_rate": 1.494952232073874e-05, + "loss": 0.8527, + "step": 1845 + }, + { + "epoch": 0.36, + "learning_rate": 1.4944104027802668e-05, + "loss": 0.7739, + "step": 1846 + }, + { + "epoch": 0.36, + "learning_rate": 1.4938683813108968e-05, + "loss": 0.8038, + "step": 1847 + }, + { + "epoch": 0.36, + "learning_rate": 1.493326167876445e-05, + "loss": 0.8898, + "step": 1848 + }, + { + "epoch": 0.36, + "learning_rate": 1.492783762687669e-05, + "loss": 0.8127, + "step": 1849 + }, + { + "epoch": 0.36, + "learning_rate": 1.4922411659553993e-05, + "loss": 0.8014, + "step": 1850 + }, + { + "epoch": 0.36, + "learning_rate": 1.4916983778905418e-05, + "loss": 0.8183, + "step": 1851 + }, + { + "epoch": 0.36, + "learning_rate": 1.4911553987040767e-05, + "loss": 0.8254, + "step": 1852 + }, + { + "epoch": 0.36, + "learning_rate": 1.4906122286070582e-05, + "loss": 0.8353, + "step": 1853 + }, + { + "epoch": 0.36, + "learning_rate": 1.4900688678106146e-05, + "loss": 0.8231, + "step": 1854 + }, + { + "epoch": 0.36, + "learning_rate": 1.4895253165259487e-05, + "loss": 0.8217, + "step": 1855 + }, + { + "epoch": 0.36, + "learning_rate": 1.4889815749643371e-05, + "loss": 0.7719, + "step": 1856 + }, + { + "epoch": 0.36, + "learning_rate": 1.4884376433371304e-05, + "loss": 0.7798, + "step": 1857 + }, + { + "epoch": 0.36, + "learning_rate": 1.4878935218557531e-05, + "loss": 0.8071, + "step": 1858 + }, + { + "epoch": 0.36, + "learning_rate": 1.4873492107317039e-05, + "loss": 0.8403, + "step": 1859 + }, + { + "epoch": 0.36, + "learning_rate": 1.4868047101765541e-05, + "loss": 0.8202, + "step": 1860 + }, + { + "epoch": 0.36, + "learning_rate": 1.4862600204019497e-05, + "loss": 0.8582, + "step": 1861 + }, + { + "epoch": 0.36, + "learning_rate": 1.4857151416196103e-05, + "loss": 0.813, + "step": 1862 + }, + { + "epoch": 0.36, + "learning_rate": 1.485170074041328e-05, + "loss": 0.8285, + "step": 1863 + }, + { + "epoch": 0.36, + "learning_rate": 1.484624817878969e-05, + "loss": 0.7269, + "step": 1864 + }, + { + "epoch": 0.36, + "learning_rate": 1.4840793733444727e-05, + "loss": 0.8196, + "step": 1865 + }, + { + "epoch": 0.36, + "learning_rate": 1.4835337406498516e-05, + "loss": 0.8893, + "step": 1866 + }, + { + "epoch": 0.36, + "learning_rate": 1.4829879200071916e-05, + "loss": 0.8496, + "step": 1867 + }, + { + "epoch": 0.36, + "learning_rate": 1.4824419116286514e-05, + "loss": 1.6035, + "step": 1868 + }, + { + "epoch": 0.36, + "learning_rate": 1.4818957157264624e-05, + "loss": 0.7866, + "step": 1869 + }, + { + "epoch": 0.36, + "learning_rate": 1.4813493325129296e-05, + "loss": 1.4976, + "step": 1870 + }, + { + "epoch": 0.36, + "learning_rate": 1.48080276220043e-05, + "loss": 0.8122, + "step": 1871 + }, + { + "epoch": 0.36, + "learning_rate": 1.4802560050014145e-05, + "loss": 0.7893, + "step": 1872 + }, + { + "epoch": 0.36, + "learning_rate": 1.4797090611284053e-05, + "loss": 0.8726, + "step": 1873 + }, + { + "epoch": 0.36, + "learning_rate": 1.479161930793998e-05, + "loss": 0.8398, + "step": 1874 + }, + { + "epoch": 0.36, + "learning_rate": 1.4786146142108601e-05, + "loss": 0.8703, + "step": 1875 + }, + { + "epoch": 0.36, + "learning_rate": 1.4780671115917324e-05, + "loss": 0.7602, + "step": 1876 + }, + { + "epoch": 0.36, + "learning_rate": 1.477519423149427e-05, + "loss": 1.5956, + "step": 1877 + }, + { + "epoch": 0.36, + "learning_rate": 1.4769715490968289e-05, + "loss": 0.8035, + "step": 1878 + }, + { + "epoch": 0.36, + "learning_rate": 1.4764234896468946e-05, + "loss": 0.8652, + "step": 1879 + }, + { + "epoch": 0.36, + "learning_rate": 1.4758752450126536e-05, + "loss": 0.8354, + "step": 1880 + }, + { + "epoch": 0.36, + "learning_rate": 1.4753268154072067e-05, + "loss": 0.7582, + "step": 1881 + }, + { + "epoch": 0.36, + "learning_rate": 1.4747782010437264e-05, + "loss": 0.8843, + "step": 1882 + }, + { + "epoch": 0.36, + "learning_rate": 1.4742294021354578e-05, + "loss": 0.8662, + "step": 1883 + }, + { + "epoch": 0.36, + "learning_rate": 1.4736804188957174e-05, + "loss": 0.8013, + "step": 1884 + }, + { + "epoch": 0.36, + "learning_rate": 1.473131251537893e-05, + "loss": 0.8872, + "step": 1885 + }, + { + "epoch": 0.36, + "learning_rate": 1.472581900275444e-05, + "loss": 0.8489, + "step": 1886 + }, + { + "epoch": 0.36, + "learning_rate": 1.4720323653219017e-05, + "loss": 0.7683, + "step": 1887 + }, + { + "epoch": 0.36, + "learning_rate": 1.471482646890869e-05, + "loss": 0.8206, + "step": 1888 + }, + { + "epoch": 0.36, + "learning_rate": 1.4709327451960191e-05, + "loss": 0.8173, + "step": 1889 + }, + { + "epoch": 0.36, + "learning_rate": 1.4703826604510978e-05, + "loss": 0.8034, + "step": 1890 + }, + { + "epoch": 0.36, + "learning_rate": 1.4698323928699203e-05, + "loss": 0.7785, + "step": 1891 + }, + { + "epoch": 0.36, + "learning_rate": 1.4692819426663744e-05, + "loss": 0.8248, + "step": 1892 + }, + { + "epoch": 0.36, + "learning_rate": 1.4687313100544188e-05, + "loss": 0.8237, + "step": 1893 + }, + { + "epoch": 0.36, + "learning_rate": 1.4681804952480817e-05, + "loss": 0.7935, + "step": 1894 + }, + { + "epoch": 0.36, + "learning_rate": 1.4676294984614641e-05, + "loss": 0.7987, + "step": 1895 + }, + { + "epoch": 0.36, + "learning_rate": 1.467078319908736e-05, + "loss": 0.8014, + "step": 1896 + }, + { + "epoch": 0.37, + "learning_rate": 1.466526959804139e-05, + "loss": 0.831, + "step": 1897 + }, + { + "epoch": 0.37, + "learning_rate": 1.4659754183619847e-05, + "loss": 0.8585, + "step": 1898 + }, + { + "epoch": 0.37, + "learning_rate": 1.4654236957966558e-05, + "loss": 0.8191, + "step": 1899 + }, + { + "epoch": 0.37, + "learning_rate": 1.4648717923226057e-05, + "loss": 0.8552, + "step": 1900 + }, + { + "epoch": 0.37, + "learning_rate": 1.4643197081543566e-05, + "loss": 0.8626, + "step": 1901 + }, + { + "epoch": 0.37, + "learning_rate": 1.4637674435065024e-05, + "loss": 0.74, + "step": 1902 + }, + { + "epoch": 0.37, + "learning_rate": 1.4632149985937063e-05, + "loss": 0.8355, + "step": 1903 + }, + { + "epoch": 0.37, + "learning_rate": 1.462662373630702e-05, + "loss": 0.8614, + "step": 1904 + }, + { + "epoch": 0.37, + "learning_rate": 1.4621095688322935e-05, + "loss": 0.8329, + "step": 1905 + }, + { + "epoch": 0.37, + "learning_rate": 1.4615565844133539e-05, + "loss": 0.7703, + "step": 1906 + }, + { + "epoch": 0.37, + "learning_rate": 1.4610034205888263e-05, + "loss": 0.7793, + "step": 1907 + }, + { + "epoch": 0.37, + "learning_rate": 1.4604500775737241e-05, + "loss": 0.817, + "step": 1908 + }, + { + "epoch": 0.37, + "learning_rate": 1.4598965555831297e-05, + "loss": 0.8367, + "step": 1909 + }, + { + "epoch": 0.37, + "learning_rate": 1.4593428548321957e-05, + "loss": 0.9066, + "step": 1910 + }, + { + "epoch": 0.37, + "learning_rate": 1.4587889755361437e-05, + "loss": 1.7026, + "step": 1911 + }, + { + "epoch": 0.37, + "learning_rate": 1.4582349179102643e-05, + "loss": 0.812, + "step": 1912 + }, + { + "epoch": 0.37, + "learning_rate": 1.4576806821699188e-05, + "loss": 0.813, + "step": 1913 + }, + { + "epoch": 0.37, + "learning_rate": 1.4571262685305365e-05, + "loss": 0.8543, + "step": 1914 + }, + { + "epoch": 0.37, + "learning_rate": 1.4565716772076161e-05, + "loss": 0.7935, + "step": 1915 + }, + { + "epoch": 0.37, + "learning_rate": 1.4560169084167259e-05, + "loss": 1.5397, + "step": 1916 + }, + { + "epoch": 0.37, + "learning_rate": 1.4554619623735023e-05, + "loss": 0.8571, + "step": 1917 + }, + { + "epoch": 0.37, + "learning_rate": 1.4549068392936514e-05, + "loss": 0.8299, + "step": 1918 + }, + { + "epoch": 0.37, + "learning_rate": 1.4543515393929472e-05, + "loss": 0.8604, + "step": 1919 + }, + { + "epoch": 0.37, + "learning_rate": 1.4537960628872338e-05, + "loss": 0.8108, + "step": 1920 + }, + { + "epoch": 0.37, + "learning_rate": 1.453240409992423e-05, + "loss": 0.7789, + "step": 1921 + }, + { + "epoch": 0.37, + "learning_rate": 1.4526845809244952e-05, + "loss": 0.7876, + "step": 1922 + }, + { + "epoch": 0.37, + "learning_rate": 1.4521285758994994e-05, + "loss": 0.7993, + "step": 1923 + }, + { + "epoch": 0.37, + "learning_rate": 1.4515723951335527e-05, + "loss": 0.8486, + "step": 1924 + }, + { + "epoch": 0.37, + "learning_rate": 1.4510160388428414e-05, + "loss": 0.824, + "step": 1925 + }, + { + "epoch": 0.37, + "learning_rate": 1.4504595072436192e-05, + "loss": 1.6338, + "step": 1926 + }, + { + "epoch": 0.37, + "learning_rate": 1.449902800552208e-05, + "loss": 0.8537, + "step": 1927 + }, + { + "epoch": 0.37, + "learning_rate": 1.4493459189849976e-05, + "loss": 0.8373, + "step": 1928 + }, + { + "epoch": 0.37, + "learning_rate": 1.448788862758447e-05, + "loss": 0.8667, + "step": 1929 + }, + { + "epoch": 0.37, + "learning_rate": 1.4482316320890815e-05, + "loss": 0.8325, + "step": 1930 + }, + { + "epoch": 0.37, + "learning_rate": 1.4476742271934954e-05, + "loss": 0.7851, + "step": 1931 + }, + { + "epoch": 0.37, + "learning_rate": 1.44711664828835e-05, + "loss": 0.7906, + "step": 1932 + }, + { + "epoch": 0.37, + "learning_rate": 1.4465588955903745e-05, + "loss": 0.8536, + "step": 1933 + }, + { + "epoch": 0.37, + "learning_rate": 1.4460009693163651e-05, + "loss": 0.775, + "step": 1934 + }, + { + "epoch": 0.37, + "learning_rate": 1.4454428696831868e-05, + "loss": 0.8306, + "step": 1935 + }, + { + "epoch": 0.37, + "learning_rate": 1.4448845969077706e-05, + "loss": 0.8112, + "step": 1936 + }, + { + "epoch": 0.37, + "learning_rate": 1.4443261512071155e-05, + "loss": 0.8217, + "step": 1937 + }, + { + "epoch": 0.37, + "learning_rate": 1.443767532798288e-05, + "loss": 0.7701, + "step": 1938 + }, + { + "epoch": 0.37, + "learning_rate": 1.4432087418984207e-05, + "loss": 1.4883, + "step": 1939 + }, + { + "epoch": 0.37, + "learning_rate": 1.4426497787247143e-05, + "loss": 0.7719, + "step": 1940 + }, + { + "epoch": 0.37, + "learning_rate": 1.4420906434944355e-05, + "loss": 0.8353, + "step": 1941 + }, + { + "epoch": 0.37, + "learning_rate": 1.4415313364249188e-05, + "loss": 0.8249, + "step": 1942 + }, + { + "epoch": 0.37, + "learning_rate": 1.4409718577335654e-05, + "loss": 0.8051, + "step": 1943 + }, + { + "epoch": 0.37, + "learning_rate": 1.4404122076378425e-05, + "loss": 0.8345, + "step": 1944 + }, + { + "epoch": 0.37, + "learning_rate": 1.439852386355284e-05, + "loss": 0.8472, + "step": 1945 + }, + { + "epoch": 0.37, + "learning_rate": 1.439292394103491e-05, + "loss": 0.8487, + "step": 1946 + }, + { + "epoch": 0.37, + "learning_rate": 1.4387322311001308e-05, + "loss": 0.7806, + "step": 1947 + }, + { + "epoch": 0.37, + "learning_rate": 1.4381718975629373e-05, + "loss": 0.8233, + "step": 1948 + }, + { + "epoch": 0.38, + "learning_rate": 1.4376113937097098e-05, + "loss": 0.8293, + "step": 1949 + }, + { + "epoch": 0.38, + "learning_rate": 1.4370507197583145e-05, + "loss": 0.843, + "step": 1950 + }, + { + "epoch": 0.38, + "learning_rate": 1.4364898759266837e-05, + "loss": 1.5072, + "step": 1951 + }, + { + "epoch": 0.38, + "learning_rate": 1.4359288624328158e-05, + "loss": 0.8861, + "step": 1952 + }, + { + "epoch": 0.38, + "learning_rate": 1.4353676794947747e-05, + "loss": 0.8289, + "step": 1953 + }, + { + "epoch": 0.38, + "learning_rate": 1.4348063273306905e-05, + "loss": 0.8005, + "step": 1954 + }, + { + "epoch": 0.38, + "learning_rate": 1.4342448061587587e-05, + "loss": 0.8366, + "step": 1955 + }, + { + "epoch": 0.38, + "learning_rate": 1.4336831161972418e-05, + "loss": 0.8077, + "step": 1956 + }, + { + "epoch": 0.38, + "learning_rate": 1.4331212576644657e-05, + "loss": 0.8273, + "step": 1957 + }, + { + "epoch": 0.38, + "learning_rate": 1.432559230778824e-05, + "loss": 0.8331, + "step": 1958 + }, + { + "epoch": 0.38, + "learning_rate": 1.4319970357587742e-05, + "loss": 0.795, + "step": 1959 + }, + { + "epoch": 0.38, + "learning_rate": 1.43143467282284e-05, + "loss": 1.5681, + "step": 1960 + }, + { + "epoch": 0.38, + "learning_rate": 1.43087214218961e-05, + "loss": 0.8219, + "step": 1961 + }, + { + "epoch": 0.38, + "learning_rate": 1.430309444077738e-05, + "loss": 0.8305, + "step": 1962 + }, + { + "epoch": 0.38, + "learning_rate": 1.4297465787059427e-05, + "loss": 0.762, + "step": 1963 + }, + { + "epoch": 0.38, + "learning_rate": 1.429183546293009e-05, + "loss": 0.8358, + "step": 1964 + }, + { + "epoch": 0.38, + "learning_rate": 1.4286203470577853e-05, + "loss": 0.8652, + "step": 1965 + }, + { + "epoch": 0.38, + "learning_rate": 1.4280569812191852e-05, + "loss": 0.8174, + "step": 1966 + }, + { + "epoch": 0.38, + "learning_rate": 1.427493448996187e-05, + "loss": 0.8241, + "step": 1967 + }, + { + "epoch": 0.38, + "learning_rate": 1.4269297506078348e-05, + "loss": 0.872, + "step": 1968 + }, + { + "epoch": 0.38, + "learning_rate": 1.426365886273236e-05, + "loss": 1.5384, + "step": 1969 + }, + { + "epoch": 0.38, + "learning_rate": 1.4258018562115623e-05, + "loss": 0.8711, + "step": 1970 + }, + { + "epoch": 0.38, + "learning_rate": 1.425237660642051e-05, + "loss": 0.8128, + "step": 1971 + }, + { + "epoch": 0.38, + "learning_rate": 1.424673299784003e-05, + "loss": 0.8254, + "step": 1972 + }, + { + "epoch": 0.38, + "learning_rate": 1.4241087738567837e-05, + "loss": 0.8231, + "step": 1973 + }, + { + "epoch": 0.38, + "learning_rate": 1.423544083079822e-05, + "loss": 0.8292, + "step": 1974 + }, + { + "epoch": 0.38, + "learning_rate": 1.4229792276726122e-05, + "loss": 0.7113, + "step": 1975 + }, + { + "epoch": 0.38, + "learning_rate": 1.4224142078547112e-05, + "loss": 0.8272, + "step": 1976 + }, + { + "epoch": 0.38, + "learning_rate": 1.4218490238457407e-05, + "loss": 0.8636, + "step": 1977 + }, + { + "epoch": 0.38, + "learning_rate": 1.4212836758653862e-05, + "loss": 0.787, + "step": 1978 + }, + { + "epoch": 0.38, + "learning_rate": 1.4207181641333962e-05, + "loss": 0.8249, + "step": 1979 + }, + { + "epoch": 0.38, + "learning_rate": 1.4201524888695835e-05, + "loss": 0.8117, + "step": 1980 + }, + { + "epoch": 0.38, + "learning_rate": 1.4195866502938245e-05, + "loss": 0.8545, + "step": 1981 + }, + { + "epoch": 0.38, + "learning_rate": 1.4190206486260585e-05, + "loss": 0.8354, + "step": 1982 + }, + { + "epoch": 0.38, + "learning_rate": 1.4184544840862888e-05, + "loss": 0.8486, + "step": 1983 + }, + { + "epoch": 0.38, + "learning_rate": 1.4178881568945816e-05, + "loss": 0.83, + "step": 1984 + }, + { + "epoch": 0.38, + "learning_rate": 1.4173216672710665e-05, + "loss": 0.7718, + "step": 1985 + }, + { + "epoch": 0.38, + "learning_rate": 1.4167550154359365e-05, + "loss": 0.8457, + "step": 1986 + }, + { + "epoch": 0.38, + "learning_rate": 1.4161882016094475e-05, + "loss": 0.7612, + "step": 1987 + }, + { + "epoch": 0.38, + "learning_rate": 1.4156212260119176e-05, + "loss": 0.8438, + "step": 1988 + }, + { + "epoch": 0.38, + "learning_rate": 1.4150540888637287e-05, + "loss": 0.8576, + "step": 1989 + }, + { + "epoch": 0.38, + "learning_rate": 1.4144867903853254e-05, + "loss": 0.8016, + "step": 1990 + }, + { + "epoch": 0.38, + "learning_rate": 1.4139193307972148e-05, + "loss": 0.7674, + "step": 1991 + }, + { + "epoch": 0.38, + "learning_rate": 1.4133517103199666e-05, + "loss": 0.8558, + "step": 1992 + }, + { + "epoch": 0.38, + "learning_rate": 1.4127839291742129e-05, + "loss": 0.8396, + "step": 1993 + }, + { + "epoch": 0.38, + "learning_rate": 1.412215987580649e-05, + "loss": 0.8536, + "step": 1994 + }, + { + "epoch": 0.38, + "learning_rate": 1.4116478857600311e-05, + "loss": 1.4713, + "step": 1995 + }, + { + "epoch": 0.38, + "learning_rate": 1.4110796239331791e-05, + "loss": 0.8204, + "step": 1996 + }, + { + "epoch": 0.38, + "learning_rate": 1.410511202320975e-05, + "loss": 0.8432, + "step": 1997 + }, + { + "epoch": 0.38, + "learning_rate": 1.4099426211443619e-05, + "loss": 0.8468, + "step": 1998 + }, + { + "epoch": 0.38, + "learning_rate": 1.4093738806243458e-05, + "loss": 0.8294, + "step": 1999 + }, + { + "epoch": 0.38, + "learning_rate": 1.4088049809819939e-05, + "loss": 0.7814, + "step": 2000 + }, + { + "epoch": 0.39, + "learning_rate": 1.4082359224384361e-05, + "loss": 1.4731, + "step": 2001 + }, + { + "epoch": 0.39, + "learning_rate": 1.4076667052148635e-05, + "loss": 0.8233, + "step": 2002 + }, + { + "epoch": 0.39, + "learning_rate": 1.4070973295325294e-05, + "loss": 0.8542, + "step": 2003 + }, + { + "epoch": 0.39, + "learning_rate": 1.4065277956127478e-05, + "loss": 0.792, + "step": 2004 + }, + { + "epoch": 0.39, + "learning_rate": 1.405958103676895e-05, + "loss": 0.8438, + "step": 2005 + }, + { + "epoch": 0.39, + "learning_rate": 1.4053882539464083e-05, + "loss": 0.842, + "step": 2006 + }, + { + "epoch": 0.39, + "learning_rate": 1.404818246642787e-05, + "loss": 0.7613, + "step": 2007 + }, + { + "epoch": 0.39, + "learning_rate": 1.4042480819875907e-05, + "loss": 0.8467, + "step": 2008 + }, + { + "epoch": 0.39, + "learning_rate": 1.4036777602024405e-05, + "loss": 0.783, + "step": 2009 + }, + { + "epoch": 0.39, + "learning_rate": 1.4031072815090188e-05, + "loss": 0.8016, + "step": 2010 + }, + { + "epoch": 0.39, + "learning_rate": 1.402536646129069e-05, + "loss": 1.3952, + "step": 2011 + }, + { + "epoch": 0.39, + "learning_rate": 1.4019658542843952e-05, + "loss": 0.806, + "step": 2012 + }, + { + "epoch": 0.39, + "learning_rate": 1.4013949061968626e-05, + "loss": 0.8161, + "step": 2013 + }, + { + "epoch": 0.39, + "learning_rate": 1.4008238020883965e-05, + "loss": 0.8789, + "step": 2014 + }, + { + "epoch": 0.39, + "learning_rate": 1.4002525421809831e-05, + "loss": 0.8288, + "step": 2015 + }, + { + "epoch": 0.39, + "learning_rate": 1.3996811266966704e-05, + "loss": 0.8349, + "step": 2016 + }, + { + "epoch": 0.39, + "learning_rate": 1.3991095558575645e-05, + "loss": 0.8191, + "step": 2017 + }, + { + "epoch": 0.39, + "learning_rate": 1.3985378298858341e-05, + "loss": 0.7958, + "step": 2018 + }, + { + "epoch": 0.39, + "learning_rate": 1.3979659490037065e-05, + "loss": 0.8051, + "step": 2019 + }, + { + "epoch": 0.39, + "learning_rate": 1.397393913433471e-05, + "loss": 0.8177, + "step": 2020 + }, + { + "epoch": 0.39, + "learning_rate": 1.396821723397475e-05, + "loss": 0.8265, + "step": 2021 + }, + { + "epoch": 0.39, + "learning_rate": 1.3962493791181275e-05, + "loss": 0.8376, + "step": 2022 + }, + { + "epoch": 0.39, + "learning_rate": 1.395676880817897e-05, + "loss": 0.8216, + "step": 2023 + }, + { + "epoch": 0.39, + "learning_rate": 1.3951042287193116e-05, + "loss": 0.8566, + "step": 2024 + }, + { + "epoch": 0.39, + "learning_rate": 1.3945314230449594e-05, + "loss": 0.8183, + "step": 2025 + }, + { + "epoch": 0.39, + "learning_rate": 1.393958464017488e-05, + "loss": 0.7981, + "step": 2026 + }, + { + "epoch": 0.39, + "learning_rate": 1.3933853518596048e-05, + "loss": 0.8454, + "step": 2027 + }, + { + "epoch": 0.39, + "learning_rate": 1.392812086794077e-05, + "loss": 0.8355, + "step": 2028 + }, + { + "epoch": 0.39, + "learning_rate": 1.3922386690437307e-05, + "loss": 0.8407, + "step": 2029 + }, + { + "epoch": 0.39, + "learning_rate": 1.3916650988314516e-05, + "loss": 0.7655, + "step": 2030 + }, + { + "epoch": 0.39, + "learning_rate": 1.3910913763801843e-05, + "loss": 0.8622, + "step": 2031 + }, + { + "epoch": 0.39, + "learning_rate": 1.3905175019129338e-05, + "loss": 1.5037, + "step": 2032 + }, + { + "epoch": 0.39, + "learning_rate": 1.3899434756527623e-05, + "loss": 0.8237, + "step": 2033 + }, + { + "epoch": 0.39, + "learning_rate": 1.3893692978227924e-05, + "loss": 0.8214, + "step": 2034 + }, + { + "epoch": 0.39, + "learning_rate": 1.3887949686462055e-05, + "loss": 0.8267, + "step": 2035 + }, + { + "epoch": 0.39, + "learning_rate": 1.388220488346241e-05, + "loss": 1.4523, + "step": 2036 + }, + { + "epoch": 0.39, + "learning_rate": 1.387645857146198e-05, + "loss": 0.8219, + "step": 2037 + }, + { + "epoch": 0.39, + "learning_rate": 1.3870710752694334e-05, + "loss": 0.8004, + "step": 2038 + }, + { + "epoch": 0.39, + "learning_rate": 1.3864961429393632e-05, + "loss": 0.8027, + "step": 2039 + }, + { + "epoch": 0.39, + "learning_rate": 1.3859210603794626e-05, + "loss": 0.8222, + "step": 2040 + }, + { + "epoch": 0.39, + "learning_rate": 1.3853458278132637e-05, + "loss": 0.8066, + "step": 2041 + }, + { + "epoch": 0.39, + "learning_rate": 1.3847704454643571e-05, + "loss": 0.8311, + "step": 2042 + }, + { + "epoch": 0.39, + "learning_rate": 1.3841949135563928e-05, + "loss": 0.8129, + "step": 2043 + }, + { + "epoch": 0.39, + "learning_rate": 1.3836192323130782e-05, + "loss": 0.8017, + "step": 2044 + }, + { + "epoch": 0.39, + "learning_rate": 1.3830434019581786e-05, + "loss": 0.7915, + "step": 2045 + }, + { + "epoch": 0.39, + "learning_rate": 1.3824674227155175e-05, + "loss": 0.8273, + "step": 2046 + }, + { + "epoch": 0.39, + "learning_rate": 1.381891294808976e-05, + "loss": 0.7652, + "step": 2047 + }, + { + "epoch": 0.39, + "learning_rate": 1.3813150184624936e-05, + "loss": 0.8004, + "step": 2048 + }, + { + "epoch": 0.39, + "learning_rate": 1.3807385939000668e-05, + "loss": 0.8169, + "step": 2049 + }, + { + "epoch": 0.39, + "learning_rate": 1.38016202134575e-05, + "loss": 0.8429, + "step": 2050 + }, + { + "epoch": 0.39, + "learning_rate": 1.3795853010236555e-05, + "loss": 0.8712, + "step": 2051 + }, + { + "epoch": 0.39, + "learning_rate": 1.379008433157952e-05, + "loss": 0.7793, + "step": 2052 + }, + { + "epoch": 0.4, + "learning_rate": 1.3784314179728668e-05, + "loss": 0.8289, + "step": 2053 + }, + { + "epoch": 0.4, + "learning_rate": 1.377854255692684e-05, + "loss": 0.8071, + "step": 2054 + }, + { + "epoch": 0.4, + "learning_rate": 1.377276946541744e-05, + "loss": 0.8841, + "step": 2055 + }, + { + "epoch": 0.4, + "learning_rate": 1.376699490744446e-05, + "loss": 0.8563, + "step": 2056 + }, + { + "epoch": 0.4, + "learning_rate": 1.3761218885252443e-05, + "loss": 0.81, + "step": 2057 + }, + { + "epoch": 0.4, + "learning_rate": 1.3755441401086517e-05, + "loss": 0.7953, + "step": 2058 + }, + { + "epoch": 0.4, + "learning_rate": 1.374966245719237e-05, + "loss": 0.8403, + "step": 2059 + }, + { + "epoch": 0.4, + "learning_rate": 1.3743882055816257e-05, + "loss": 0.821, + "step": 2060 + }, + { + "epoch": 0.4, + "learning_rate": 1.3738100199205007e-05, + "loss": 0.8011, + "step": 2061 + }, + { + "epoch": 0.4, + "learning_rate": 1.3732316889606005e-05, + "loss": 0.8251, + "step": 2062 + }, + { + "epoch": 0.4, + "learning_rate": 1.3726532129267206e-05, + "loss": 0.8257, + "step": 2063 + }, + { + "epoch": 0.4, + "learning_rate": 1.3720745920437128e-05, + "loss": 0.884, + "step": 2064 + }, + { + "epoch": 0.4, + "learning_rate": 1.3714958265364855e-05, + "loss": 0.8138, + "step": 2065 + }, + { + "epoch": 0.4, + "learning_rate": 1.3709169166300028e-05, + "loss": 0.8531, + "step": 2066 + }, + { + "epoch": 0.4, + "learning_rate": 1.3703378625492852e-05, + "loss": 0.8633, + "step": 2067 + }, + { + "epoch": 0.4, + "learning_rate": 1.369758664519409e-05, + "loss": 0.8609, + "step": 2068 + }, + { + "epoch": 0.4, + "learning_rate": 1.3691793227655066e-05, + "loss": 0.8702, + "step": 2069 + }, + { + "epoch": 0.4, + "learning_rate": 1.3685998375127669e-05, + "loss": 0.8105, + "step": 2070 + }, + { + "epoch": 0.4, + "learning_rate": 1.3680202089864331e-05, + "loss": 0.8124, + "step": 2071 + }, + { + "epoch": 0.4, + "learning_rate": 1.367440437411806e-05, + "loss": 0.8124, + "step": 2072 + }, + { + "epoch": 0.4, + "learning_rate": 1.3668605230142403e-05, + "loss": 0.8047, + "step": 2073 + }, + { + "epoch": 0.4, + "learning_rate": 1.3662804660191469e-05, + "loss": 0.7949, + "step": 2074 + }, + { + "epoch": 0.4, + "learning_rate": 1.3657002666519925e-05, + "loss": 0.7802, + "step": 2075 + }, + { + "epoch": 0.4, + "learning_rate": 1.3651199251382983e-05, + "loss": 0.755, + "step": 2076 + }, + { + "epoch": 0.4, + "learning_rate": 1.3645394417036414e-05, + "loss": 0.858, + "step": 2077 + }, + { + "epoch": 0.4, + "learning_rate": 1.3639588165736544e-05, + "loss": 0.8697, + "step": 2078 + }, + { + "epoch": 0.4, + "learning_rate": 1.3633780499740237e-05, + "loss": 0.8493, + "step": 2079 + }, + { + "epoch": 0.4, + "learning_rate": 1.3627971421304916e-05, + "loss": 0.823, + "step": 2080 + }, + { + "epoch": 0.4, + "learning_rate": 1.3622160932688553e-05, + "loss": 0.7997, + "step": 2081 + }, + { + "epoch": 0.4, + "learning_rate": 1.3616349036149668e-05, + "loss": 0.8064, + "step": 2082 + }, + { + "epoch": 0.4, + "learning_rate": 1.3610535733947325e-05, + "loss": 0.8588, + "step": 2083 + }, + { + "epoch": 0.4, + "learning_rate": 1.3604721028341137e-05, + "loss": 0.8451, + "step": 2084 + }, + { + "epoch": 0.4, + "learning_rate": 1.3598904921591261e-05, + "loss": 0.8, + "step": 2085 + }, + { + "epoch": 0.4, + "learning_rate": 1.3593087415958397e-05, + "loss": 0.7998, + "step": 2086 + }, + { + "epoch": 0.4, + "learning_rate": 1.3587268513703795e-05, + "loss": 0.8446, + "step": 2087 + }, + { + "epoch": 0.4, + "learning_rate": 1.3581448217089243e-05, + "loss": 0.7675, + "step": 2088 + }, + { + "epoch": 0.4, + "learning_rate": 1.3575626528377073e-05, + "loss": 1.4518, + "step": 2089 + }, + { + "epoch": 0.4, + "learning_rate": 1.3569803449830152e-05, + "loss": 0.8245, + "step": 2090 + }, + { + "epoch": 0.4, + "learning_rate": 1.3563978983711899e-05, + "loss": 0.817, + "step": 2091 + }, + { + "epoch": 0.4, + "learning_rate": 1.355815313228626e-05, + "loss": 0.8268, + "step": 2092 + }, + { + "epoch": 0.4, + "learning_rate": 1.3552325897817728e-05, + "loss": 0.8245, + "step": 2093 + }, + { + "epoch": 0.4, + "learning_rate": 1.3546497282571331e-05, + "loss": 0.7846, + "step": 2094 + }, + { + "epoch": 0.4, + "learning_rate": 1.3540667288812633e-05, + "loss": 0.7669, + "step": 2095 + }, + { + "epoch": 0.4, + "learning_rate": 1.3534835918807731e-05, + "loss": 0.7768, + "step": 2096 + }, + { + "epoch": 0.4, + "learning_rate": 1.3529003174823265e-05, + "loss": 0.8183, + "step": 2097 + }, + { + "epoch": 0.4, + "learning_rate": 1.35231690591264e-05, + "loss": 0.8425, + "step": 2098 + }, + { + "epoch": 0.4, + "learning_rate": 1.3517333573984842e-05, + "loss": 0.8123, + "step": 2099 + }, + { + "epoch": 0.4, + "learning_rate": 1.3511496721666823e-05, + "loss": 0.7654, + "step": 2100 + }, + { + "epoch": 0.4, + "learning_rate": 1.350565850444111e-05, + "loss": 0.8453, + "step": 2101 + }, + { + "epoch": 0.4, + "learning_rate": 1.3499818924577e-05, + "loss": 0.7931, + "step": 2102 + }, + { + "epoch": 0.4, + "learning_rate": 1.3493977984344317e-05, + "loss": 0.8105, + "step": 2103 + }, + { + "epoch": 0.41, + "learning_rate": 1.348813568601342e-05, + "loss": 0.8463, + "step": 2104 + }, + { + "epoch": 0.41, + "learning_rate": 1.348229203185519e-05, + "loss": 0.8329, + "step": 2105 + }, + { + "epoch": 0.41, + "learning_rate": 1.3476447024141038e-05, + "loss": 0.8123, + "step": 2106 + }, + { + "epoch": 0.41, + "learning_rate": 1.3470600665142894e-05, + "loss": 0.8507, + "step": 2107 + }, + { + "epoch": 0.41, + "learning_rate": 1.3464752957133226e-05, + "loss": 0.8071, + "step": 2108 + }, + { + "epoch": 0.41, + "learning_rate": 1.3458903902385018e-05, + "loss": 0.778, + "step": 2109 + }, + { + "epoch": 0.41, + "learning_rate": 1.3453053503171782e-05, + "loss": 0.8046, + "step": 2110 + }, + { + "epoch": 0.41, + "learning_rate": 1.3447201761767543e-05, + "loss": 0.8273, + "step": 2111 + }, + { + "epoch": 0.41, + "learning_rate": 1.344134868044686e-05, + "loss": 0.7741, + "step": 2112 + }, + { + "epoch": 0.41, + "learning_rate": 1.3435494261484804e-05, + "loss": 0.8587, + "step": 2113 + }, + { + "epoch": 0.41, + "learning_rate": 1.342963850715697e-05, + "loss": 0.8456, + "step": 2114 + }, + { + "epoch": 0.41, + "learning_rate": 1.3423781419739472e-05, + "loss": 0.8138, + "step": 2115 + }, + { + "epoch": 0.41, + "learning_rate": 1.341792300150894e-05, + "loss": 0.8785, + "step": 2116 + }, + { + "epoch": 0.41, + "learning_rate": 1.3412063254742527e-05, + "loss": 0.8028, + "step": 2117 + }, + { + "epoch": 0.41, + "learning_rate": 1.340620218171789e-05, + "loss": 0.8446, + "step": 2118 + }, + { + "epoch": 0.41, + "learning_rate": 1.340033978471322e-05, + "loss": 0.7998, + "step": 2119 + }, + { + "epoch": 0.41, + "learning_rate": 1.3394476066007202e-05, + "loss": 0.8054, + "step": 2120 + }, + { + "epoch": 0.41, + "learning_rate": 1.3388611027879052e-05, + "loss": 0.7546, + "step": 2121 + }, + { + "epoch": 0.41, + "learning_rate": 1.3382744672608489e-05, + "loss": 0.8334, + "step": 2122 + }, + { + "epoch": 0.41, + "learning_rate": 1.3376877002475746e-05, + "loss": 0.8111, + "step": 2123 + }, + { + "epoch": 0.41, + "learning_rate": 1.3371008019761568e-05, + "loss": 0.8494, + "step": 2124 + }, + { + "epoch": 0.41, + "learning_rate": 1.3365137726747213e-05, + "loss": 0.8299, + "step": 2125 + }, + { + "epoch": 0.41, + "learning_rate": 1.3359266125714443e-05, + "loss": 0.8418, + "step": 2126 + }, + { + "epoch": 0.41, + "learning_rate": 1.3353393218945532e-05, + "loss": 0.8157, + "step": 2127 + }, + { + "epoch": 0.41, + "learning_rate": 1.3347519008723258e-05, + "loss": 1.6095, + "step": 2128 + }, + { + "epoch": 0.41, + "learning_rate": 1.3341643497330911e-05, + "loss": 0.8543, + "step": 2129 + }, + { + "epoch": 0.41, + "learning_rate": 1.333576668705228e-05, + "loss": 0.8448, + "step": 2130 + }, + { + "epoch": 0.41, + "learning_rate": 1.3329888580171666e-05, + "loss": 0.8678, + "step": 2131 + }, + { + "epoch": 0.41, + "learning_rate": 1.3324009178973872e-05, + "loss": 0.7885, + "step": 2132 + }, + { + "epoch": 0.41, + "learning_rate": 1.3318128485744197e-05, + "loss": 0.8342, + "step": 2133 + }, + { + "epoch": 0.41, + "learning_rate": 1.3312246502768453e-05, + "loss": 0.8349, + "step": 2134 + }, + { + "epoch": 0.41, + "learning_rate": 1.3306363232332944e-05, + "loss": 0.8206, + "step": 2135 + }, + { + "epoch": 0.41, + "learning_rate": 1.3300478676724482e-05, + "loss": 0.7821, + "step": 2136 + }, + { + "epoch": 0.41, + "learning_rate": 1.3294592838230375e-05, + "loss": 0.7722, + "step": 2137 + }, + { + "epoch": 0.41, + "learning_rate": 1.3288705719138429e-05, + "loss": 0.7724, + "step": 2138 + }, + { + "epoch": 0.41, + "learning_rate": 1.3282817321736946e-05, + "loss": 0.8028, + "step": 2139 + }, + { + "epoch": 0.41, + "learning_rate": 1.3276927648314732e-05, + "loss": 0.7467, + "step": 2140 + }, + { + "epoch": 0.41, + "learning_rate": 1.3271036701161082e-05, + "loss": 1.5157, + "step": 2141 + }, + { + "epoch": 0.41, + "learning_rate": 1.326514448256579e-05, + "loss": 0.7712, + "step": 2142 + }, + { + "epoch": 0.41, + "learning_rate": 1.3259250994819141e-05, + "loss": 0.8354, + "step": 2143 + }, + { + "epoch": 0.41, + "learning_rate": 1.3253356240211917e-05, + "loss": 0.7842, + "step": 2144 + }, + { + "epoch": 0.41, + "learning_rate": 1.324746022103539e-05, + "loss": 0.8298, + "step": 2145 + }, + { + "epoch": 0.41, + "learning_rate": 1.324156293958132e-05, + "loss": 0.8105, + "step": 2146 + }, + { + "epoch": 0.41, + "learning_rate": 1.3235664398141968e-05, + "loss": 0.8203, + "step": 2147 + }, + { + "epoch": 0.41, + "learning_rate": 1.3229764599010077e-05, + "loss": 0.7636, + "step": 2148 + }, + { + "epoch": 0.41, + "learning_rate": 1.3223863544478875e-05, + "loss": 0.8246, + "step": 2149 + }, + { + "epoch": 0.41, + "learning_rate": 1.3217961236842089e-05, + "loss": 0.9116, + "step": 2150 + }, + { + "epoch": 0.41, + "learning_rate": 1.3212057678393926e-05, + "loss": 0.7909, + "step": 2151 + }, + { + "epoch": 0.41, + "learning_rate": 1.320615287142908e-05, + "loss": 0.8605, + "step": 2152 + }, + { + "epoch": 0.41, + "learning_rate": 1.3200246818242733e-05, + "loss": 0.8387, + "step": 2153 + }, + { + "epoch": 0.41, + "learning_rate": 1.3194339521130544e-05, + "loss": 0.8246, + "step": 2154 + }, + { + "epoch": 0.41, + "learning_rate": 1.3188430982388664e-05, + "loss": 0.8535, + "step": 2155 + }, + { + "epoch": 0.42, + "learning_rate": 1.3182521204313726e-05, + "loss": 0.8546, + "step": 2156 + }, + { + "epoch": 0.42, + "learning_rate": 1.3176610189202836e-05, + "loss": 0.8126, + "step": 2157 + }, + { + "epoch": 0.42, + "learning_rate": 1.3170697939353593e-05, + "loss": 0.7746, + "step": 2158 + }, + { + "epoch": 0.42, + "learning_rate": 1.3164784457064067e-05, + "loss": 0.8113, + "step": 2159 + }, + { + "epoch": 0.42, + "learning_rate": 1.3158869744632807e-05, + "loss": 1.5595, + "step": 2160 + }, + { + "epoch": 0.42, + "learning_rate": 1.315295380435885e-05, + "loss": 0.7639, + "step": 2161 + }, + { + "epoch": 0.42, + "learning_rate": 1.3147036638541698e-05, + "loss": 0.8094, + "step": 2162 + }, + { + "epoch": 0.42, + "learning_rate": 1.3141118249481335e-05, + "loss": 0.8076, + "step": 2163 + }, + { + "epoch": 0.42, + "learning_rate": 1.3135198639478222e-05, + "loss": 0.7325, + "step": 2164 + }, + { + "epoch": 0.42, + "learning_rate": 1.3129277810833292e-05, + "loss": 0.7562, + "step": 2165 + }, + { + "epoch": 0.42, + "learning_rate": 1.3123355765847952e-05, + "loss": 0.8102, + "step": 2166 + }, + { + "epoch": 0.42, + "learning_rate": 1.3117432506824083e-05, + "loss": 0.7741, + "step": 2167 + }, + { + "epoch": 0.42, + "learning_rate": 1.3111508036064037e-05, + "loss": 0.8393, + "step": 2168 + }, + { + "epoch": 0.42, + "learning_rate": 1.3105582355870636e-05, + "loss": 0.8461, + "step": 2169 + }, + { + "epoch": 0.42, + "learning_rate": 1.3099655468547174e-05, + "loss": 0.8486, + "step": 2170 + }, + { + "epoch": 0.42, + "learning_rate": 1.3093727376397413e-05, + "loss": 0.7992, + "step": 2171 + }, + { + "epoch": 0.42, + "learning_rate": 1.3087798081725587e-05, + "loss": 1.5695, + "step": 2172 + }, + { + "epoch": 0.42, + "learning_rate": 1.3081867586836388e-05, + "loss": 0.7966, + "step": 2173 + }, + { + "epoch": 0.42, + "learning_rate": 1.3075935894034984e-05, + "loss": 0.8765, + "step": 2174 + }, + { + "epoch": 0.42, + "learning_rate": 1.3070003005627008e-05, + "loss": 0.7865, + "step": 2175 + }, + { + "epoch": 0.42, + "learning_rate": 1.3064068923918551e-05, + "loss": 1.4331, + "step": 2176 + }, + { + "epoch": 0.42, + "learning_rate": 1.3058133651216172e-05, + "loss": 0.7614, + "step": 2177 + }, + { + "epoch": 0.42, + "learning_rate": 1.3052197189826892e-05, + "loss": 0.7823, + "step": 2178 + }, + { + "epoch": 0.42, + "learning_rate": 1.3046259542058198e-05, + "loss": 0.8641, + "step": 2179 + }, + { + "epoch": 0.42, + "learning_rate": 1.3040320710218035e-05, + "loss": 0.8162, + "step": 2180 + }, + { + "epoch": 0.42, + "learning_rate": 1.3034380696614806e-05, + "loss": 1.3658, + "step": 2181 + }, + { + "epoch": 0.42, + "learning_rate": 1.3028439503557376e-05, + "loss": 0.8345, + "step": 2182 + }, + { + "epoch": 0.42, + "learning_rate": 1.3022497133355066e-05, + "loss": 0.7922, + "step": 2183 + }, + { + "epoch": 0.42, + "learning_rate": 1.3016553588317662e-05, + "loss": 1.4329, + "step": 2184 + }, + { + "epoch": 0.42, + "learning_rate": 1.3010608870755395e-05, + "loss": 0.8166, + "step": 2185 + }, + { + "epoch": 0.42, + "learning_rate": 1.3004662982978964e-05, + "loss": 0.7827, + "step": 2186 + }, + { + "epoch": 0.42, + "learning_rate": 1.2998715927299513e-05, + "loss": 0.8293, + "step": 2187 + }, + { + "epoch": 0.42, + "learning_rate": 1.2992767706028641e-05, + "loss": 0.8503, + "step": 2188 + }, + { + "epoch": 0.42, + "learning_rate": 1.298681832147841e-05, + "loss": 0.7854, + "step": 2189 + }, + { + "epoch": 0.42, + "learning_rate": 1.2980867775961324e-05, + "loss": 0.8536, + "step": 2190 + }, + { + "epoch": 0.42, + "learning_rate": 1.2974916071790337e-05, + "loss": 1.3462, + "step": 2191 + }, + { + "epoch": 0.42, + "learning_rate": 1.2968963211278865e-05, + "loss": 0.8058, + "step": 2192 + }, + { + "epoch": 0.42, + "learning_rate": 1.2963009196740762e-05, + "loss": 0.798, + "step": 2193 + }, + { + "epoch": 0.42, + "learning_rate": 1.2957054030490332e-05, + "loss": 0.8304, + "step": 2194 + }, + { + "epoch": 0.42, + "learning_rate": 1.2951097714842331e-05, + "loss": 0.7906, + "step": 2195 + }, + { + "epoch": 0.42, + "learning_rate": 1.2945140252111967e-05, + "loss": 1.4169, + "step": 2196 + }, + { + "epoch": 0.42, + "learning_rate": 1.293918164461488e-05, + "loss": 0.7907, + "step": 2197 + }, + { + "epoch": 0.42, + "learning_rate": 1.293322189466716e-05, + "loss": 0.8019, + "step": 2198 + }, + { + "epoch": 0.42, + "learning_rate": 1.2927261004585347e-05, + "loss": 1.3729, + "step": 2199 + }, + { + "epoch": 0.42, + "learning_rate": 1.2921298976686421e-05, + "loss": 0.8585, + "step": 2200 + }, + { + "epoch": 0.42, + "learning_rate": 1.2915335813287802e-05, + "loss": 0.8877, + "step": 2201 + }, + { + "epoch": 0.42, + "learning_rate": 1.2909371516707355e-05, + "loss": 1.3763, + "step": 2202 + }, + { + "epoch": 0.42, + "learning_rate": 1.2903406089263375e-05, + "loss": 0.8311, + "step": 2203 + }, + { + "epoch": 0.42, + "learning_rate": 1.2897439533274615e-05, + "loss": 0.7956, + "step": 2204 + }, + { + "epoch": 0.42, + "learning_rate": 1.2891471851060251e-05, + "loss": 0.8031, + "step": 2205 + }, + { + "epoch": 0.42, + "learning_rate": 1.2885503044939903e-05, + "loss": 0.8064, + "step": 2206 + }, + { + "epoch": 0.42, + "learning_rate": 1.2879533117233628e-05, + "loss": 0.7661, + "step": 2207 + }, + { + "epoch": 0.43, + "learning_rate": 1.2873562070261918e-05, + "loss": 0.8124, + "step": 2208 + }, + { + "epoch": 0.43, + "learning_rate": 1.28675899063457e-05, + "loss": 0.8199, + "step": 2209 + }, + { + "epoch": 0.43, + "learning_rate": 1.2861616627806334e-05, + "loss": 0.8269, + "step": 2210 + }, + { + "epoch": 0.43, + "learning_rate": 1.2855642236965615e-05, + "loss": 0.8122, + "step": 2211 + }, + { + "epoch": 0.43, + "learning_rate": 1.2849666736145774e-05, + "loss": 0.8029, + "step": 2212 + }, + { + "epoch": 0.43, + "learning_rate": 1.284369012766946e-05, + "loss": 0.8263, + "step": 2213 + }, + { + "epoch": 0.43, + "learning_rate": 1.2837712413859773e-05, + "loss": 0.8007, + "step": 2214 + }, + { + "epoch": 0.43, + "learning_rate": 1.2831733597040224e-05, + "loss": 0.8125, + "step": 2215 + }, + { + "epoch": 0.43, + "learning_rate": 1.2825753679534762e-05, + "loss": 0.8223, + "step": 2216 + }, + { + "epoch": 0.43, + "learning_rate": 1.2819772663667762e-05, + "loss": 0.79, + "step": 2217 + }, + { + "epoch": 0.43, + "learning_rate": 1.281379055176403e-05, + "loss": 0.867, + "step": 2218 + }, + { + "epoch": 0.43, + "learning_rate": 1.2807807346148786e-05, + "loss": 1.4071, + "step": 2219 + }, + { + "epoch": 0.43, + "learning_rate": 1.2801823049147689e-05, + "loss": 0.8119, + "step": 2220 + }, + { + "epoch": 0.43, + "learning_rate": 1.2795837663086812e-05, + "loss": 0.8368, + "step": 2221 + }, + { + "epoch": 0.43, + "learning_rate": 1.2789851190292664e-05, + "loss": 0.8273, + "step": 2222 + }, + { + "epoch": 0.43, + "learning_rate": 1.2783863633092159e-05, + "loss": 0.8272, + "step": 2223 + }, + { + "epoch": 0.43, + "learning_rate": 1.2777874993812646e-05, + "loss": 0.8475, + "step": 2224 + }, + { + "epoch": 0.43, + "learning_rate": 1.277188527478189e-05, + "loss": 0.762, + "step": 2225 + }, + { + "epoch": 0.43, + "learning_rate": 1.2765894478328073e-05, + "loss": 0.8076, + "step": 2226 + }, + { + "epoch": 0.43, + "learning_rate": 1.2759902606779804e-05, + "loss": 0.7958, + "step": 2227 + }, + { + "epoch": 0.43, + "learning_rate": 1.2753909662466099e-05, + "loss": 0.8331, + "step": 2228 + }, + { + "epoch": 0.43, + "learning_rate": 1.2747915647716403e-05, + "loss": 0.8075, + "step": 2229 + }, + { + "epoch": 0.43, + "learning_rate": 1.2741920564860562e-05, + "loss": 0.8216, + "step": 2230 + }, + { + "epoch": 0.43, + "learning_rate": 1.2735924416228853e-05, + "loss": 1.4252, + "step": 2231 + }, + { + "epoch": 0.43, + "learning_rate": 1.2729927204151958e-05, + "loss": 0.8264, + "step": 2232 + }, + { + "epoch": 0.43, + "learning_rate": 1.2723928930960972e-05, + "loss": 0.8397, + "step": 2233 + }, + { + "epoch": 0.43, + "learning_rate": 1.2717929598987406e-05, + "loss": 0.7639, + "step": 2234 + }, + { + "epoch": 0.43, + "learning_rate": 1.2711929210563187e-05, + "loss": 0.8296, + "step": 2235 + }, + { + "epoch": 0.43, + "learning_rate": 1.2705927768020638e-05, + "loss": 0.791, + "step": 2236 + }, + { + "epoch": 0.43, + "learning_rate": 1.2699925273692507e-05, + "loss": 0.7577, + "step": 2237 + }, + { + "epoch": 0.43, + "learning_rate": 1.269392172991194e-05, + "loss": 0.8188, + "step": 2238 + }, + { + "epoch": 0.43, + "learning_rate": 1.26879171390125e-05, + "loss": 0.7987, + "step": 2239 + }, + { + "epoch": 0.43, + "learning_rate": 1.2681911503328153e-05, + "loss": 0.7623, + "step": 2240 + }, + { + "epoch": 0.43, + "learning_rate": 1.2675904825193264e-05, + "loss": 0.8523, + "step": 2241 + }, + { + "epoch": 0.43, + "learning_rate": 1.2669897106942615e-05, + "loss": 0.8383, + "step": 2242 + }, + { + "epoch": 0.43, + "learning_rate": 1.2663888350911389e-05, + "loss": 0.8324, + "step": 2243 + }, + { + "epoch": 0.43, + "learning_rate": 1.2657878559435166e-05, + "loss": 0.855, + "step": 2244 + }, + { + "epoch": 0.43, + "learning_rate": 1.2651867734849935e-05, + "loss": 0.8265, + "step": 2245 + }, + { + "epoch": 0.43, + "learning_rate": 1.2645855879492084e-05, + "loss": 0.8886, + "step": 2246 + }, + { + "epoch": 0.43, + "learning_rate": 1.2639842995698402e-05, + "loss": 0.8413, + "step": 2247 + }, + { + "epoch": 0.43, + "learning_rate": 1.263382908580608e-05, + "loss": 0.8602, + "step": 2248 + }, + { + "epoch": 0.43, + "learning_rate": 1.2627814152152702e-05, + "loss": 0.8541, + "step": 2249 + }, + { + "epoch": 0.43, + "learning_rate": 1.2621798197076259e-05, + "loss": 0.836, + "step": 2250 + }, + { + "epoch": 0.43, + "learning_rate": 1.261578122291513e-05, + "loss": 0.8026, + "step": 2251 + }, + { + "epoch": 0.43, + "learning_rate": 1.2609763232008092e-05, + "loss": 0.8664, + "step": 2252 + }, + { + "epoch": 0.43, + "learning_rate": 1.2603744226694322e-05, + "loss": 0.8095, + "step": 2253 + }, + { + "epoch": 0.43, + "learning_rate": 1.2597724209313392e-05, + "loss": 0.774, + "step": 2254 + }, + { + "epoch": 0.43, + "learning_rate": 1.2591703182205257e-05, + "loss": 0.868, + "step": 2255 + }, + { + "epoch": 0.43, + "learning_rate": 1.2585681147710276e-05, + "loss": 0.7662, + "step": 2256 + }, + { + "epoch": 0.43, + "learning_rate": 1.257965810816919e-05, + "loss": 0.8033, + "step": 2257 + }, + { + "epoch": 0.43, + "learning_rate": 1.257363406592314e-05, + "loss": 0.7772, + "step": 2258 + }, + { + "epoch": 0.43, + "learning_rate": 1.2567609023313648e-05, + "loss": 0.7474, + "step": 2259 + }, + { + "epoch": 0.44, + "learning_rate": 1.2561582982682634e-05, + "loss": 0.8176, + "step": 2260 + }, + { + "epoch": 0.44, + "learning_rate": 1.25555559463724e-05, + "loss": 0.7517, + "step": 2261 + }, + { + "epoch": 0.44, + "learning_rate": 1.2549527916725632e-05, + "loss": 0.7591, + "step": 2262 + }, + { + "epoch": 0.44, + "learning_rate": 1.2543498896085409e-05, + "loss": 0.7999, + "step": 2263 + }, + { + "epoch": 0.44, + "learning_rate": 1.253746888679519e-05, + "loss": 0.7495, + "step": 2264 + }, + { + "epoch": 0.44, + "learning_rate": 1.2531437891198825e-05, + "loss": 0.8399, + "step": 2265 + }, + { + "epoch": 0.44, + "learning_rate": 1.2525405911640542e-05, + "loss": 0.7863, + "step": 2266 + }, + { + "epoch": 0.44, + "learning_rate": 1.251937295046495e-05, + "loss": 0.8071, + "step": 2267 + }, + { + "epoch": 0.44, + "learning_rate": 1.251333901001704e-05, + "loss": 0.8048, + "step": 2268 + }, + { + "epoch": 0.44, + "learning_rate": 1.2507304092642191e-05, + "loss": 1.4082, + "step": 2269 + }, + { + "epoch": 0.44, + "learning_rate": 1.2501268200686153e-05, + "loss": 0.8152, + "step": 2270 + }, + { + "epoch": 0.44, + "learning_rate": 1.249523133649506e-05, + "loss": 0.829, + "step": 2271 + }, + { + "epoch": 0.44, + "learning_rate": 1.248919350241542e-05, + "loss": 0.8693, + "step": 2272 + }, + { + "epoch": 0.44, + "learning_rate": 1.2483154700794122e-05, + "loss": 0.8201, + "step": 2273 + }, + { + "epoch": 0.44, + "learning_rate": 1.2477114933978429e-05, + "loss": 0.8002, + "step": 2274 + }, + { + "epoch": 0.44, + "learning_rate": 1.2471074204315975e-05, + "loss": 0.81, + "step": 2275 + }, + { + "epoch": 0.44, + "learning_rate": 1.2465032514154778e-05, + "loss": 0.7809, + "step": 2276 + }, + { + "epoch": 0.44, + "learning_rate": 1.2458989865843223e-05, + "loss": 0.8241, + "step": 2277 + }, + { + "epoch": 0.44, + "learning_rate": 1.2452946261730069e-05, + "loss": 0.812, + "step": 2278 + }, + { + "epoch": 0.44, + "learning_rate": 1.2446901704164441e-05, + "loss": 0.8027, + "step": 2279 + }, + { + "epoch": 0.44, + "learning_rate": 1.244085619549584e-05, + "loss": 0.8353, + "step": 2280 + }, + { + "epoch": 0.44, + "learning_rate": 1.2434809738074144e-05, + "loss": 0.8479, + "step": 2281 + }, + { + "epoch": 0.44, + "learning_rate": 1.2428762334249584e-05, + "loss": 0.8409, + "step": 2282 + }, + { + "epoch": 0.44, + "learning_rate": 1.2422713986372772e-05, + "loss": 1.4932, + "step": 2283 + }, + { + "epoch": 0.44, + "learning_rate": 1.2416664696794675e-05, + "loss": 0.8269, + "step": 2284 + }, + { + "epoch": 0.44, + "learning_rate": 1.241061446786664e-05, + "loss": 0.787, + "step": 2285 + }, + { + "epoch": 0.44, + "learning_rate": 1.2404563301940366e-05, + "loss": 0.8458, + "step": 2286 + }, + { + "epoch": 0.44, + "learning_rate": 1.239851120136793e-05, + "loss": 0.7956, + "step": 2287 + }, + { + "epoch": 0.44, + "learning_rate": 1.2392458168501755e-05, + "loss": 0.8396, + "step": 2288 + }, + { + "epoch": 0.44, + "learning_rate": 1.238640420569464e-05, + "loss": 0.8343, + "step": 2289 + }, + { + "epoch": 0.44, + "learning_rate": 1.2380349315299744e-05, + "loss": 0.8175, + "step": 2290 + }, + { + "epoch": 0.44, + "learning_rate": 1.237429349967058e-05, + "loss": 0.828, + "step": 2291 + }, + { + "epoch": 0.44, + "learning_rate": 1.2368236761161023e-05, + "loss": 0.8628, + "step": 2292 + }, + { + "epoch": 0.44, + "learning_rate": 1.2362179102125315e-05, + "loss": 0.8096, + "step": 2293 + }, + { + "epoch": 0.44, + "learning_rate": 1.2356120524918045e-05, + "loss": 0.7894, + "step": 2294 + }, + { + "epoch": 0.44, + "learning_rate": 1.2350061031894159e-05, + "loss": 0.8139, + "step": 2295 + }, + { + "epoch": 0.44, + "learning_rate": 1.2344000625408964e-05, + "loss": 0.8311, + "step": 2296 + }, + { + "epoch": 0.44, + "learning_rate": 1.2337939307818127e-05, + "loss": 0.7878, + "step": 2297 + }, + { + "epoch": 0.44, + "learning_rate": 1.2331877081477661e-05, + "loss": 0.8472, + "step": 2298 + }, + { + "epoch": 0.44, + "learning_rate": 1.232581394874393e-05, + "loss": 0.8502, + "step": 2299 + }, + { + "epoch": 0.44, + "learning_rate": 1.2319749911973658e-05, + "loss": 0.8055, + "step": 2300 + }, + { + "epoch": 0.44, + "learning_rate": 1.2313684973523914e-05, + "loss": 0.8065, + "step": 2301 + }, + { + "epoch": 0.44, + "learning_rate": 1.2307619135752123e-05, + "loss": 0.8161, + "step": 2302 + }, + { + "epoch": 0.44, + "learning_rate": 1.2301552401016058e-05, + "loss": 0.7736, + "step": 2303 + }, + { + "epoch": 0.44, + "learning_rate": 1.2295484771673838e-05, + "loss": 0.778, + "step": 2304 + }, + { + "epoch": 0.44, + "learning_rate": 1.228941625008393e-05, + "loss": 0.8154, + "step": 2305 + }, + { + "epoch": 0.44, + "learning_rate": 1.2283346838605148e-05, + "loss": 0.8406, + "step": 2306 + }, + { + "epoch": 0.44, + "learning_rate": 1.227727653959666e-05, + "loss": 0.7576, + "step": 2307 + }, + { + "epoch": 0.44, + "learning_rate": 1.2271205355417966e-05, + "loss": 0.7654, + "step": 2308 + }, + { + "epoch": 0.44, + "learning_rate": 1.2265133288428919e-05, + "loss": 0.8159, + "step": 2309 + }, + { + "epoch": 0.44, + "learning_rate": 1.225906034098971e-05, + "loss": 0.8119, + "step": 2310 + }, + { + "epoch": 0.44, + "learning_rate": 1.2252986515460878e-05, + "loss": 0.8275, + "step": 2311 + }, + { + "epoch": 0.45, + "learning_rate": 1.2246911814203295e-05, + "loss": 0.8664, + "step": 2312 + }, + { + "epoch": 0.45, + "learning_rate": 1.224083623957818e-05, + "loss": 0.7816, + "step": 2313 + }, + { + "epoch": 0.45, + "learning_rate": 1.2234759793947092e-05, + "loss": 0.8186, + "step": 2314 + }, + { + "epoch": 0.45, + "learning_rate": 1.2228682479671927e-05, + "loss": 0.7581, + "step": 2315 + }, + { + "epoch": 0.45, + "learning_rate": 1.2222604299114911e-05, + "loss": 0.7987, + "step": 2316 + }, + { + "epoch": 0.45, + "learning_rate": 1.2216525254638618e-05, + "loss": 0.8287, + "step": 2317 + }, + { + "epoch": 0.45, + "learning_rate": 1.2210445348605954e-05, + "loss": 0.8238, + "step": 2318 + }, + { + "epoch": 0.45, + "learning_rate": 1.2204364583380164e-05, + "loss": 0.8154, + "step": 2319 + }, + { + "epoch": 0.45, + "learning_rate": 1.219828296132481e-05, + "loss": 0.8225, + "step": 2320 + }, + { + "epoch": 0.45, + "learning_rate": 1.2192200484803812e-05, + "loss": 0.7518, + "step": 2321 + }, + { + "epoch": 0.45, + "learning_rate": 1.2186117156181401e-05, + "loss": 0.8165, + "step": 2322 + }, + { + "epoch": 0.45, + "learning_rate": 1.2180032977822149e-05, + "loss": 0.8216, + "step": 2323 + }, + { + "epoch": 0.45, + "learning_rate": 1.2173947952090961e-05, + "loss": 0.8351, + "step": 2324 + }, + { + "epoch": 0.45, + "learning_rate": 1.2167862081353063e-05, + "loss": 0.8333, + "step": 2325 + }, + { + "epoch": 0.45, + "learning_rate": 1.2161775367974019e-05, + "loss": 0.8646, + "step": 2326 + }, + { + "epoch": 0.45, + "learning_rate": 1.2155687814319705e-05, + "loss": 0.7792, + "step": 2327 + }, + { + "epoch": 0.45, + "learning_rate": 1.2149599422756347e-05, + "loss": 0.8777, + "step": 2328 + }, + { + "epoch": 0.45, + "learning_rate": 1.2143510195650473e-05, + "loss": 0.8441, + "step": 2329 + }, + { + "epoch": 0.45, + "learning_rate": 1.2137420135368951e-05, + "loss": 0.8, + "step": 2330 + }, + { + "epoch": 0.45, + "learning_rate": 1.2131329244278969e-05, + "loss": 0.8349, + "step": 2331 + }, + { + "epoch": 0.45, + "learning_rate": 1.2125237524748037e-05, + "loss": 0.8006, + "step": 2332 + }, + { + "epoch": 0.45, + "learning_rate": 1.2119144979143984e-05, + "loss": 0.8532, + "step": 2333 + }, + { + "epoch": 0.45, + "learning_rate": 1.2113051609834966e-05, + "loss": 1.5857, + "step": 2334 + }, + { + "epoch": 0.45, + "learning_rate": 1.2106957419189453e-05, + "loss": 0.8363, + "step": 2335 + }, + { + "epoch": 0.45, + "learning_rate": 1.2100862409576243e-05, + "loss": 0.7795, + "step": 2336 + }, + { + "epoch": 0.45, + "learning_rate": 1.2094766583364445e-05, + "loss": 0.8689, + "step": 2337 + }, + { + "epoch": 0.45, + "learning_rate": 1.2088669942923486e-05, + "loss": 0.7989, + "step": 2338 + }, + { + "epoch": 0.45, + "learning_rate": 1.2082572490623113e-05, + "loss": 0.8502, + "step": 2339 + }, + { + "epoch": 0.45, + "learning_rate": 1.2076474228833383e-05, + "loss": 0.7805, + "step": 2340 + }, + { + "epoch": 0.45, + "learning_rate": 1.2070375159924674e-05, + "loss": 0.787, + "step": 2341 + }, + { + "epoch": 0.45, + "learning_rate": 1.2064275286267675e-05, + "loss": 0.811, + "step": 2342 + }, + { + "epoch": 0.45, + "learning_rate": 1.2058174610233384e-05, + "loss": 0.7782, + "step": 2343 + }, + { + "epoch": 0.45, + "learning_rate": 1.2052073134193118e-05, + "loss": 0.8083, + "step": 2344 + }, + { + "epoch": 0.45, + "learning_rate": 1.2045970860518504e-05, + "loss": 0.793, + "step": 2345 + }, + { + "epoch": 0.45, + "learning_rate": 1.203986779158147e-05, + "loss": 0.8163, + "step": 2346 + }, + { + "epoch": 0.45, + "learning_rate": 1.2033763929754265e-05, + "loss": 0.7506, + "step": 2347 + }, + { + "epoch": 0.45, + "learning_rate": 1.2027659277409436e-05, + "loss": 0.7951, + "step": 2348 + }, + { + "epoch": 0.45, + "learning_rate": 1.2021553836919848e-05, + "loss": 1.5493, + "step": 2349 + }, + { + "epoch": 0.45, + "learning_rate": 1.2015447610658661e-05, + "loss": 0.8187, + "step": 2350 + }, + { + "epoch": 0.45, + "learning_rate": 1.200934060099935e-05, + "loss": 0.8126, + "step": 2351 + }, + { + "epoch": 0.45, + "learning_rate": 1.2003232810315688e-05, + "loss": 0.8474, + "step": 2352 + }, + { + "epoch": 0.45, + "learning_rate": 1.1997124240981754e-05, + "loss": 0.8095, + "step": 2353 + }, + { + "epoch": 0.45, + "learning_rate": 1.199101489537193e-05, + "loss": 0.8213, + "step": 2354 + }, + { + "epoch": 0.45, + "learning_rate": 1.1984904775860897e-05, + "loss": 0.8405, + "step": 2355 + }, + { + "epoch": 0.45, + "learning_rate": 1.1978793884823643e-05, + "loss": 1.4552, + "step": 2356 + }, + { + "epoch": 0.45, + "learning_rate": 1.1972682224635454e-05, + "loss": 0.7795, + "step": 2357 + }, + { + "epoch": 0.45, + "learning_rate": 1.196656979767191e-05, + "loss": 0.8382, + "step": 2358 + }, + { + "epoch": 0.45, + "learning_rate": 1.1960456606308887e-05, + "loss": 0.8542, + "step": 2359 + }, + { + "epoch": 0.45, + "learning_rate": 1.195434265292257e-05, + "loss": 0.8119, + "step": 2360 + }, + { + "epoch": 0.45, + "learning_rate": 1.194822793988943e-05, + "loss": 0.8208, + "step": 2361 + }, + { + "epoch": 0.45, + "learning_rate": 1.1942112469586241e-05, + "loss": 1.4211, + "step": 2362 + }, + { + "epoch": 0.45, + "learning_rate": 1.1935996244390064e-05, + "loss": 0.8531, + "step": 2363 + }, + { + "epoch": 0.46, + "learning_rate": 1.1929879266678256e-05, + "loss": 0.7558, + "step": 2364 + }, + { + "epoch": 0.46, + "learning_rate": 1.1923761538828465e-05, + "loss": 0.8345, + "step": 2365 + }, + { + "epoch": 0.46, + "learning_rate": 1.1917643063218638e-05, + "loss": 1.3651, + "step": 2366 + }, + { + "epoch": 0.46, + "learning_rate": 1.1911523842227002e-05, + "loss": 0.8019, + "step": 2367 + }, + { + "epoch": 0.46, + "learning_rate": 1.190540387823208e-05, + "loss": 0.7863, + "step": 2368 + }, + { + "epoch": 0.46, + "learning_rate": 1.1899283173612686e-05, + "loss": 0.8035, + "step": 2369 + }, + { + "epoch": 0.46, + "learning_rate": 1.1893161730747917e-05, + "loss": 0.7937, + "step": 2370 + }, + { + "epoch": 0.46, + "learning_rate": 1.1887039552017157e-05, + "loss": 0.8266, + "step": 2371 + }, + { + "epoch": 0.46, + "learning_rate": 1.1880916639800076e-05, + "loss": 0.8127, + "step": 2372 + }, + { + "epoch": 0.46, + "learning_rate": 1.1874792996476634e-05, + "loss": 1.3498, + "step": 2373 + }, + { + "epoch": 0.46, + "learning_rate": 1.186866862442707e-05, + "loss": 0.8405, + "step": 2374 + }, + { + "epoch": 0.46, + "learning_rate": 1.1862543526031914e-05, + "loss": 0.72, + "step": 2375 + }, + { + "epoch": 0.46, + "learning_rate": 1.1856417703671962e-05, + "loss": 0.8073, + "step": 2376 + }, + { + "epoch": 0.46, + "learning_rate": 1.1850291159728307e-05, + "loss": 0.8296, + "step": 2377 + }, + { + "epoch": 0.46, + "learning_rate": 1.1844163896582321e-05, + "loss": 0.7904, + "step": 2378 + }, + { + "epoch": 0.46, + "learning_rate": 1.1838035916615645e-05, + "loss": 0.8316, + "step": 2379 + }, + { + "epoch": 0.46, + "learning_rate": 1.1831907222210212e-05, + "loss": 0.7923, + "step": 2380 + }, + { + "epoch": 0.46, + "learning_rate": 1.182577781574822e-05, + "loss": 0.8617, + "step": 2381 + }, + { + "epoch": 0.46, + "learning_rate": 1.1819647699612153e-05, + "loss": 0.7661, + "step": 2382 + }, + { + "epoch": 0.46, + "learning_rate": 1.181351687618477e-05, + "loss": 0.8285, + "step": 2383 + }, + { + "epoch": 0.46, + "learning_rate": 1.1807385347849098e-05, + "loss": 0.8331, + "step": 2384 + }, + { + "epoch": 0.46, + "learning_rate": 1.1801253116988447e-05, + "loss": 0.8112, + "step": 2385 + }, + { + "epoch": 0.46, + "learning_rate": 1.179512018598639e-05, + "loss": 0.7849, + "step": 2386 + }, + { + "epoch": 0.46, + "learning_rate": 1.1788986557226788e-05, + "loss": 0.8304, + "step": 2387 + }, + { + "epoch": 0.46, + "learning_rate": 1.1782852233093754e-05, + "loss": 0.8272, + "step": 2388 + }, + { + "epoch": 0.46, + "learning_rate": 1.177671721597168e-05, + "loss": 0.7969, + "step": 2389 + }, + { + "epoch": 0.46, + "learning_rate": 1.1770581508245235e-05, + "loss": 0.7804, + "step": 2390 + }, + { + "epoch": 0.46, + "learning_rate": 1.1764445112299347e-05, + "loss": 0.7757, + "step": 2391 + }, + { + "epoch": 0.46, + "learning_rate": 1.1758308030519208e-05, + "loss": 1.3863, + "step": 2392 + }, + { + "epoch": 0.46, + "learning_rate": 1.1752170265290287e-05, + "loss": 0.8083, + "step": 2393 + }, + { + "epoch": 0.46, + "learning_rate": 1.1746031818998314e-05, + "loss": 0.7964, + "step": 2394 + }, + { + "epoch": 0.46, + "learning_rate": 1.1739892694029285e-05, + "loss": 0.8189, + "step": 2395 + }, + { + "epoch": 0.46, + "learning_rate": 1.1733752892769457e-05, + "loss": 0.844, + "step": 2396 + }, + { + "epoch": 0.46, + "learning_rate": 1.1727612417605348e-05, + "loss": 0.7763, + "step": 2397 + }, + { + "epoch": 0.46, + "learning_rate": 1.1721471270923746e-05, + "loss": 1.3661, + "step": 2398 + }, + { + "epoch": 0.46, + "learning_rate": 1.171532945511169e-05, + "loss": 1.3483, + "step": 2399 + }, + { + "epoch": 0.46, + "learning_rate": 1.1709186972556494e-05, + "loss": 0.8528, + "step": 2400 + }, + { + "epoch": 0.46, + "learning_rate": 1.1703043825645715e-05, + "loss": 0.8288, + "step": 2401 + }, + { + "epoch": 0.46, + "learning_rate": 1.1696900016767173e-05, + "loss": 0.8654, + "step": 2402 + }, + { + "epoch": 0.46, + "learning_rate": 1.169075554830895e-05, + "loss": 0.8181, + "step": 2403 + }, + { + "epoch": 0.46, + "learning_rate": 1.1684610422659382e-05, + "loss": 0.8018, + "step": 2404 + }, + { + "epoch": 0.46, + "learning_rate": 1.1678464642207057e-05, + "loss": 0.7686, + "step": 2405 + }, + { + "epoch": 0.46, + "learning_rate": 1.1672318209340824e-05, + "loss": 0.8024, + "step": 2406 + }, + { + "epoch": 0.46, + "learning_rate": 1.1666171126449779e-05, + "loss": 0.8473, + "step": 2407 + }, + { + "epoch": 0.46, + "learning_rate": 1.1660023395923279e-05, + "loss": 0.7687, + "step": 2408 + }, + { + "epoch": 0.46, + "learning_rate": 1.165387502015092e-05, + "loss": 0.843, + "step": 2409 + }, + { + "epoch": 0.46, + "learning_rate": 1.1647726001522562e-05, + "loss": 0.8503, + "step": 2410 + }, + { + "epoch": 0.46, + "learning_rate": 1.1641576342428305e-05, + "loss": 0.8179, + "step": 2411 + }, + { + "epoch": 0.46, + "learning_rate": 1.1635426045258508e-05, + "loss": 0.8424, + "step": 2412 + }, + { + "epoch": 0.46, + "learning_rate": 1.1629275112403766e-05, + "loss": 0.8023, + "step": 2413 + }, + { + "epoch": 0.46, + "learning_rate": 1.1623123546254931e-05, + "loss": 0.8562, + "step": 2414 + }, + { + "epoch": 0.46, + "learning_rate": 1.1616971349203091e-05, + "loss": 0.7001, + "step": 2415 + }, + { + "epoch": 0.47, + "learning_rate": 1.1610818523639598e-05, + "loss": 0.7984, + "step": 2416 + }, + { + "epoch": 0.47, + "learning_rate": 1.1604665071956023e-05, + "loss": 0.8417, + "step": 2417 + }, + { + "epoch": 0.47, + "learning_rate": 1.1598510996544201e-05, + "loss": 0.8332, + "step": 2418 + }, + { + "epoch": 0.47, + "learning_rate": 1.1592356299796198e-05, + "loss": 0.7805, + "step": 2419 + }, + { + "epoch": 0.47, + "learning_rate": 1.1586200984104323e-05, + "loss": 0.7974, + "step": 2420 + }, + { + "epoch": 0.47, + "learning_rate": 1.1580045051861138e-05, + "loss": 0.7853, + "step": 2421 + }, + { + "epoch": 0.47, + "learning_rate": 1.1573888505459423e-05, + "loss": 0.8308, + "step": 2422 + }, + { + "epoch": 0.47, + "learning_rate": 1.1567731347292217e-05, + "loss": 0.8602, + "step": 2423 + }, + { + "epoch": 0.47, + "learning_rate": 1.156157357975278e-05, + "loss": 0.8004, + "step": 2424 + }, + { + "epoch": 0.47, + "learning_rate": 1.1555415205234623e-05, + "loss": 0.8161, + "step": 2425 + }, + { + "epoch": 0.47, + "learning_rate": 1.1549256226131482e-05, + "loss": 0.8056, + "step": 2426 + }, + { + "epoch": 0.47, + "learning_rate": 1.1543096644837335e-05, + "loss": 0.8042, + "step": 2427 + }, + { + "epoch": 0.47, + "learning_rate": 1.1536936463746395e-05, + "loss": 0.8271, + "step": 2428 + }, + { + "epoch": 0.47, + "learning_rate": 1.1530775685253101e-05, + "loss": 0.8295, + "step": 2429 + }, + { + "epoch": 0.47, + "learning_rate": 1.1524614311752128e-05, + "loss": 0.7569, + "step": 2430 + }, + { + "epoch": 0.47, + "learning_rate": 1.1518452345638383e-05, + "loss": 0.8464, + "step": 2431 + }, + { + "epoch": 0.47, + "learning_rate": 1.1512289789307003e-05, + "loss": 0.8437, + "step": 2432 + }, + { + "epoch": 0.47, + "learning_rate": 1.1506126645153355e-05, + "loss": 0.8194, + "step": 2433 + }, + { + "epoch": 0.47, + "learning_rate": 1.1499962915573035e-05, + "loss": 0.772, + "step": 2434 + }, + { + "epoch": 0.47, + "learning_rate": 1.1493798602961862e-05, + "loss": 0.7859, + "step": 2435 + }, + { + "epoch": 0.47, + "learning_rate": 1.1487633709715884e-05, + "loss": 0.801, + "step": 2436 + }, + { + "epoch": 0.47, + "learning_rate": 1.1481468238231378e-05, + "loss": 0.8083, + "step": 2437 + }, + { + "epoch": 0.47, + "learning_rate": 1.1475302190904847e-05, + "loss": 0.7512, + "step": 2438 + }, + { + "epoch": 0.47, + "learning_rate": 1.146913557013301e-05, + "loss": 0.7876, + "step": 2439 + }, + { + "epoch": 0.47, + "learning_rate": 1.1462968378312808e-05, + "loss": 0.816, + "step": 2440 + }, + { + "epoch": 0.47, + "learning_rate": 1.1456800617841417e-05, + "loss": 0.7904, + "step": 2441 + }, + { + "epoch": 0.47, + "learning_rate": 1.1450632291116226e-05, + "loss": 0.7401, + "step": 2442 + }, + { + "epoch": 0.47, + "learning_rate": 1.1444463400534837e-05, + "loss": 0.8093, + "step": 2443 + }, + { + "epoch": 0.47, + "learning_rate": 1.1438293948495086e-05, + "loss": 0.7766, + "step": 2444 + }, + { + "epoch": 0.47, + "learning_rate": 1.1432123937395015e-05, + "loss": 0.6873, + "step": 2445 + }, + { + "epoch": 0.47, + "learning_rate": 1.142595336963289e-05, + "loss": 0.7735, + "step": 2446 + }, + { + "epoch": 0.47, + "learning_rate": 1.141978224760719e-05, + "loss": 0.7314, + "step": 2447 + }, + { + "epoch": 0.47, + "learning_rate": 1.1413610573716607e-05, + "loss": 0.8259, + "step": 2448 + }, + { + "epoch": 0.47, + "learning_rate": 1.140743835036006e-05, + "loss": 0.7565, + "step": 2449 + }, + { + "epoch": 0.47, + "learning_rate": 1.1401265579936669e-05, + "loss": 0.8235, + "step": 2450 + }, + { + "epoch": 0.47, + "learning_rate": 1.1395092264845764e-05, + "loss": 1.3823, + "step": 2451 + }, + { + "epoch": 0.47, + "learning_rate": 1.13889184074869e-05, + "loss": 0.7666, + "step": 2452 + }, + { + "epoch": 0.47, + "learning_rate": 1.1382744010259835e-05, + "loss": 0.8227, + "step": 2453 + }, + { + "epoch": 0.47, + "learning_rate": 1.1376569075564537e-05, + "loss": 0.8207, + "step": 2454 + }, + { + "epoch": 0.47, + "learning_rate": 1.1370393605801184e-05, + "loss": 0.8312, + "step": 2455 + }, + { + "epoch": 0.47, + "learning_rate": 1.136421760337016e-05, + "loss": 0.8081, + "step": 2456 + }, + { + "epoch": 0.47, + "learning_rate": 1.135804107067206e-05, + "loss": 0.8029, + "step": 2457 + }, + { + "epoch": 0.47, + "learning_rate": 1.1351864010107678e-05, + "loss": 0.88, + "step": 2458 + }, + { + "epoch": 0.47, + "learning_rate": 1.1345686424078027e-05, + "loss": 0.8238, + "step": 2459 + }, + { + "epoch": 0.47, + "learning_rate": 1.1339508314984306e-05, + "loss": 0.8231, + "step": 2460 + }, + { + "epoch": 0.47, + "learning_rate": 1.1333329685227934e-05, + "loss": 0.763, + "step": 2461 + }, + { + "epoch": 0.47, + "learning_rate": 1.1327150537210517e-05, + "loss": 0.8346, + "step": 2462 + }, + { + "epoch": 0.47, + "learning_rate": 1.1320970873333876e-05, + "loss": 0.8342, + "step": 2463 + }, + { + "epoch": 0.47, + "learning_rate": 1.1314790696000023e-05, + "loss": 0.8044, + "step": 2464 + }, + { + "epoch": 0.47, + "learning_rate": 1.1308610007611178e-05, + "loss": 0.8126, + "step": 2465 + }, + { + "epoch": 0.47, + "learning_rate": 1.1302428810569755e-05, + "loss": 0.8002, + "step": 2466 + }, + { + "epoch": 0.47, + "learning_rate": 1.1296247107278362e-05, + "loss": 0.8228, + "step": 2467 + }, + { + "epoch": 0.48, + "learning_rate": 1.1290064900139808e-05, + "loss": 0.8533, + "step": 2468 + }, + { + "epoch": 0.48, + "learning_rate": 1.1283882191557099e-05, + "loss": 0.7716, + "step": 2469 + }, + { + "epoch": 0.48, + "learning_rate": 1.1277698983933431e-05, + "loss": 0.8439, + "step": 2470 + }, + { + "epoch": 0.48, + "learning_rate": 1.1271515279672205e-05, + "loss": 0.8005, + "step": 2471 + }, + { + "epoch": 0.48, + "learning_rate": 1.1265331081177002e-05, + "loss": 0.8298, + "step": 2472 + }, + { + "epoch": 0.48, + "learning_rate": 1.1259146390851598e-05, + "loss": 0.8076, + "step": 2473 + }, + { + "epoch": 0.48, + "learning_rate": 1.1252961211099966e-05, + "loss": 0.8009, + "step": 2474 + }, + { + "epoch": 0.48, + "learning_rate": 1.1246775544326268e-05, + "loss": 0.8164, + "step": 2475 + }, + { + "epoch": 0.48, + "learning_rate": 1.1240589392934849e-05, + "loss": 0.8065, + "step": 2476 + }, + { + "epoch": 0.48, + "learning_rate": 1.123440275933025e-05, + "loss": 0.8344, + "step": 2477 + }, + { + "epoch": 0.48, + "learning_rate": 1.122821564591719e-05, + "loss": 0.768, + "step": 2478 + }, + { + "epoch": 0.48, + "learning_rate": 1.1222028055100584e-05, + "loss": 0.8849, + "step": 2479 + }, + { + "epoch": 0.48, + "learning_rate": 1.1215839989285536e-05, + "loss": 0.8047, + "step": 2480 + }, + { + "epoch": 0.48, + "learning_rate": 1.1209651450877315e-05, + "loss": 0.7738, + "step": 2481 + }, + { + "epoch": 0.48, + "learning_rate": 1.1203462442281394e-05, + "loss": 0.7968, + "step": 2482 + }, + { + "epoch": 0.48, + "learning_rate": 1.119727296590342e-05, + "loss": 0.7821, + "step": 2483 + }, + { + "epoch": 0.48, + "learning_rate": 1.1191083024149225e-05, + "loss": 0.7917, + "step": 2484 + }, + { + "epoch": 0.48, + "learning_rate": 1.1184892619424815e-05, + "loss": 0.817, + "step": 2485 + }, + { + "epoch": 0.48, + "learning_rate": 1.117870175413638e-05, + "loss": 0.8327, + "step": 2486 + }, + { + "epoch": 0.48, + "learning_rate": 1.1172510430690298e-05, + "loss": 0.8247, + "step": 2487 + }, + { + "epoch": 0.48, + "learning_rate": 1.116631865149311e-05, + "loss": 0.7822, + "step": 2488 + }, + { + "epoch": 0.48, + "learning_rate": 1.1160126418951542e-05, + "loss": 0.783, + "step": 2489 + }, + { + "epoch": 0.48, + "learning_rate": 1.1153933735472498e-05, + "loss": 0.8412, + "step": 2490 + }, + { + "epoch": 0.48, + "learning_rate": 1.1147740603463051e-05, + "loss": 0.7695, + "step": 2491 + }, + { + "epoch": 0.48, + "learning_rate": 1.1141547025330454e-05, + "loss": 0.78, + "step": 2492 + }, + { + "epoch": 0.48, + "learning_rate": 1.1135353003482132e-05, + "loss": 0.801, + "step": 2493 + }, + { + "epoch": 0.48, + "learning_rate": 1.112915854032568e-05, + "loss": 0.8129, + "step": 2494 + }, + { + "epoch": 0.48, + "learning_rate": 1.1122963638268864e-05, + "loss": 0.7529, + "step": 2495 + }, + { + "epoch": 0.48, + "learning_rate": 1.1116768299719628e-05, + "loss": 0.8157, + "step": 2496 + }, + { + "epoch": 0.48, + "learning_rate": 1.1110572527086079e-05, + "loss": 0.781, + "step": 2497 + }, + { + "epoch": 0.48, + "learning_rate": 1.1104376322776493e-05, + "loss": 0.7924, + "step": 2498 + }, + { + "epoch": 0.48, + "learning_rate": 1.1098179689199316e-05, + "loss": 0.7902, + "step": 2499 + }, + { + "epoch": 0.48, + "learning_rate": 1.1091982628763155e-05, + "loss": 0.8619, + "step": 2500 + }, + { + "epoch": 0.48, + "learning_rate": 1.10857851438768e-05, + "loss": 0.7954, + "step": 2501 + }, + { + "epoch": 0.48, + "learning_rate": 1.107958723694918e-05, + "loss": 0.7698, + "step": 2502 + }, + { + "epoch": 0.48, + "learning_rate": 1.1073388910389411e-05, + "loss": 0.7949, + "step": 2503 + }, + { + "epoch": 0.48, + "learning_rate": 1.1067190166606758e-05, + "loss": 0.7733, + "step": 2504 + }, + { + "epoch": 0.48, + "learning_rate": 1.1060991008010658e-05, + "loss": 0.7923, + "step": 2505 + }, + { + "epoch": 0.48, + "learning_rate": 1.10547914370107e-05, + "loss": 0.7978, + "step": 2506 + }, + { + "epoch": 0.48, + "learning_rate": 1.1048591456016638e-05, + "loss": 0.8287, + "step": 2507 + }, + { + "epoch": 0.48, + "learning_rate": 1.1042391067438385e-05, + "loss": 0.8159, + "step": 2508 + }, + { + "epoch": 0.48, + "learning_rate": 1.1036190273686019e-05, + "loss": 0.8437, + "step": 2509 + }, + { + "epoch": 0.48, + "learning_rate": 1.1029989077169761e-05, + "loss": 0.8031, + "step": 2510 + }, + { + "epoch": 0.48, + "learning_rate": 1.1023787480299996e-05, + "loss": 0.8409, + "step": 2511 + }, + { + "epoch": 0.48, + "learning_rate": 1.101758548548727e-05, + "loss": 0.8082, + "step": 2512 + }, + { + "epoch": 0.48, + "learning_rate": 1.1011383095142279e-05, + "loss": 0.831, + "step": 2513 + }, + { + "epoch": 0.48, + "learning_rate": 1.1005180311675869e-05, + "loss": 0.8049, + "step": 2514 + }, + { + "epoch": 0.48, + "learning_rate": 1.0998977137499044e-05, + "loss": 0.7548, + "step": 2515 + }, + { + "epoch": 0.48, + "learning_rate": 1.0992773575022962e-05, + "loss": 0.7563, + "step": 2516 + }, + { + "epoch": 0.48, + "learning_rate": 1.0986569626658918e-05, + "loss": 0.7963, + "step": 2517 + }, + { + "epoch": 0.48, + "learning_rate": 1.0980365294818377e-05, + "loss": 1.479, + "step": 2518 + }, + { + "epoch": 0.48, + "learning_rate": 1.097416058191294e-05, + "loss": 0.8155, + "step": 2519 + }, + { + "epoch": 0.49, + "learning_rate": 1.096795549035436e-05, + "loss": 0.8546, + "step": 2520 + }, + { + "epoch": 0.49, + "learning_rate": 1.0961750022554533e-05, + "loss": 0.7771, + "step": 2521 + }, + { + "epoch": 0.49, + "learning_rate": 1.095554418092551e-05, + "loss": 0.8379, + "step": 2522 + }, + { + "epoch": 0.49, + "learning_rate": 1.0949337967879478e-05, + "loss": 0.8849, + "step": 2523 + }, + { + "epoch": 0.49, + "learning_rate": 1.0943131385828773e-05, + "loss": 0.7753, + "step": 2524 + }, + { + "epoch": 0.49, + "learning_rate": 1.0936924437185879e-05, + "loss": 0.8314, + "step": 2525 + }, + { + "epoch": 0.49, + "learning_rate": 1.093071712436341e-05, + "loss": 0.7968, + "step": 2526 + }, + { + "epoch": 0.49, + "learning_rate": 1.092450944977413e-05, + "loss": 0.7854, + "step": 2527 + }, + { + "epoch": 0.49, + "learning_rate": 1.0918301415830945e-05, + "loss": 0.8069, + "step": 2528 + }, + { + "epoch": 0.49, + "learning_rate": 1.09120930249469e-05, + "loss": 0.8283, + "step": 2529 + }, + { + "epoch": 0.49, + "learning_rate": 1.0905884279535174e-05, + "loss": 1.4572, + "step": 2530 + }, + { + "epoch": 0.49, + "learning_rate": 1.0899675182009086e-05, + "loss": 0.7944, + "step": 2531 + }, + { + "epoch": 0.49, + "learning_rate": 1.0893465734782094e-05, + "loss": 0.8359, + "step": 2532 + }, + { + "epoch": 0.49, + "learning_rate": 1.0887255940267792e-05, + "loss": 0.8327, + "step": 2533 + }, + { + "epoch": 0.49, + "learning_rate": 1.0881045800879904e-05, + "loss": 0.8221, + "step": 2534 + }, + { + "epoch": 0.49, + "learning_rate": 1.0874835319032295e-05, + "loss": 0.7967, + "step": 2535 + }, + { + "epoch": 0.49, + "learning_rate": 1.086862449713896e-05, + "loss": 0.7771, + "step": 2536 + }, + { + "epoch": 0.49, + "learning_rate": 1.0862413337614021e-05, + "loss": 0.7781, + "step": 2537 + }, + { + "epoch": 0.49, + "learning_rate": 1.0856201842871741e-05, + "loss": 0.811, + "step": 2538 + }, + { + "epoch": 0.49, + "learning_rate": 1.0849990015326508e-05, + "loss": 1.3475, + "step": 2539 + }, + { + "epoch": 0.49, + "learning_rate": 1.0843777857392836e-05, + "loss": 0.8179, + "step": 2540 + }, + { + "epoch": 0.49, + "learning_rate": 1.0837565371485375e-05, + "loss": 0.8175, + "step": 2541 + }, + { + "epoch": 0.49, + "learning_rate": 1.0831352560018897e-05, + "loss": 1.4904, + "step": 2542 + }, + { + "epoch": 0.49, + "learning_rate": 1.0825139425408304e-05, + "loss": 0.8488, + "step": 2543 + }, + { + "epoch": 0.49, + "learning_rate": 1.0818925970068617e-05, + "loss": 0.8, + "step": 2544 + }, + { + "epoch": 0.49, + "learning_rate": 1.0812712196414989e-05, + "loss": 0.8336, + "step": 2545 + }, + { + "epoch": 0.49, + "learning_rate": 1.08064981068627e-05, + "loss": 0.8003, + "step": 2546 + }, + { + "epoch": 0.49, + "learning_rate": 1.080028370382714e-05, + "loss": 0.7873, + "step": 2547 + }, + { + "epoch": 0.49, + "learning_rate": 1.079406898972383e-05, + "loss": 0.8068, + "step": 2548 + }, + { + "epoch": 0.49, + "learning_rate": 1.0787853966968408e-05, + "loss": 0.7887, + "step": 2549 + }, + { + "epoch": 0.49, + "learning_rate": 1.0781638637976636e-05, + "loss": 0.7707, + "step": 2550 + }, + { + "epoch": 0.49, + "learning_rate": 1.0775423005164394e-05, + "loss": 0.7942, + "step": 2551 + }, + { + "epoch": 0.49, + "learning_rate": 1.0769207070947675e-05, + "loss": 0.7946, + "step": 2552 + }, + { + "epoch": 0.49, + "learning_rate": 1.0762990837742598e-05, + "loss": 0.8177, + "step": 2553 + }, + { + "epoch": 0.49, + "learning_rate": 1.0756774307965385e-05, + "loss": 0.8143, + "step": 2554 + }, + { + "epoch": 0.49, + "learning_rate": 1.075055748403239e-05, + "loss": 0.8135, + "step": 2555 + }, + { + "epoch": 0.49, + "learning_rate": 1.0744340368360069e-05, + "loss": 0.8248, + "step": 2556 + }, + { + "epoch": 0.49, + "learning_rate": 1.0738122963364996e-05, + "loss": 0.7779, + "step": 2557 + }, + { + "epoch": 0.49, + "learning_rate": 1.0731905271463858e-05, + "loss": 0.8235, + "step": 2558 + }, + { + "epoch": 0.49, + "learning_rate": 1.0725687295073449e-05, + "loss": 1.3706, + "step": 2559 + }, + { + "epoch": 0.49, + "learning_rate": 1.071946903661068e-05, + "loss": 0.7585, + "step": 2560 + }, + { + "epoch": 0.49, + "learning_rate": 1.0713250498492565e-05, + "loss": 0.8093, + "step": 2561 + }, + { + "epoch": 0.49, + "learning_rate": 1.0707031683136232e-05, + "loss": 0.7831, + "step": 2562 + }, + { + "epoch": 0.49, + "learning_rate": 1.0700812592958918e-05, + "loss": 0.7987, + "step": 2563 + }, + { + "epoch": 0.49, + "learning_rate": 1.0694593230377959e-05, + "loss": 0.7956, + "step": 2564 + }, + { + "epoch": 0.49, + "learning_rate": 1.0688373597810801e-05, + "loss": 0.7642, + "step": 2565 + }, + { + "epoch": 0.49, + "learning_rate": 1.0682153697675e-05, + "loss": 0.8168, + "step": 2566 + }, + { + "epoch": 0.49, + "learning_rate": 1.067593353238821e-05, + "loss": 0.7948, + "step": 2567 + }, + { + "epoch": 0.49, + "learning_rate": 1.0669713104368189e-05, + "loss": 0.7808, + "step": 2568 + }, + { + "epoch": 0.49, + "learning_rate": 1.0663492416032799e-05, + "loss": 0.819, + "step": 2569 + }, + { + "epoch": 0.49, + "learning_rate": 1.0657271469799998e-05, + "loss": 0.7869, + "step": 2570 + }, + { + "epoch": 0.49, + "learning_rate": 1.0651050268087853e-05, + "loss": 0.733, + "step": 2571 + }, + { + "epoch": 0.5, + "learning_rate": 1.064482881331452e-05, + "loss": 0.8114, + "step": 2572 + }, + { + "epoch": 0.5, + "learning_rate": 1.0638607107898266e-05, + "loss": 0.7261, + "step": 2573 + }, + { + "epoch": 0.5, + "learning_rate": 1.0632385154257445e-05, + "loss": 0.8392, + "step": 2574 + }, + { + "epoch": 0.5, + "learning_rate": 1.0626162954810508e-05, + "loss": 0.7418, + "step": 2575 + }, + { + "epoch": 0.5, + "learning_rate": 1.0619940511976006e-05, + "loss": 0.8591, + "step": 2576 + }, + { + "epoch": 0.5, + "learning_rate": 1.0613717828172584e-05, + "loss": 0.8045, + "step": 2577 + }, + { + "epoch": 0.5, + "learning_rate": 1.060749490581898e-05, + "loss": 0.7388, + "step": 2578 + }, + { + "epoch": 0.5, + "learning_rate": 1.0601271747334025e-05, + "loss": 0.7336, + "step": 2579 + }, + { + "epoch": 0.5, + "learning_rate": 1.0595048355136634e-05, + "loss": 1.3689, + "step": 2580 + }, + { + "epoch": 0.5, + "learning_rate": 1.058882473164583e-05, + "loss": 0.8408, + "step": 2581 + }, + { + "epoch": 0.5, + "learning_rate": 1.0582600879280709e-05, + "loss": 0.8795, + "step": 2582 + }, + { + "epoch": 0.5, + "learning_rate": 1.0576376800460464e-05, + "loss": 0.7892, + "step": 2583 + }, + { + "epoch": 0.5, + "learning_rate": 1.0570152497604378e-05, + "loss": 0.7991, + "step": 2584 + }, + { + "epoch": 0.5, + "learning_rate": 1.0563927973131816e-05, + "loss": 0.8263, + "step": 2585 + }, + { + "epoch": 0.5, + "learning_rate": 1.0557703229462229e-05, + "loss": 0.7934, + "step": 2586 + }, + { + "epoch": 0.5, + "learning_rate": 1.0551478269015154e-05, + "loss": 0.8438, + "step": 2587 + }, + { + "epoch": 0.5, + "learning_rate": 1.054525309421022e-05, + "loss": 0.8051, + "step": 2588 + }, + { + "epoch": 0.5, + "learning_rate": 1.0539027707467126e-05, + "loss": 1.3724, + "step": 2589 + }, + { + "epoch": 0.5, + "learning_rate": 1.0532802111205667e-05, + "loss": 0.8084, + "step": 2590 + }, + { + "epoch": 0.5, + "learning_rate": 1.0526576307845706e-05, + "loss": 0.8064, + "step": 2591 + }, + { + "epoch": 0.5, + "learning_rate": 1.0520350299807196e-05, + "loss": 0.8103, + "step": 2592 + }, + { + "epoch": 0.5, + "learning_rate": 1.0514124089510167e-05, + "loss": 0.8188, + "step": 2593 + }, + { + "epoch": 0.5, + "learning_rate": 1.0507897679374729e-05, + "loss": 0.8822, + "step": 2594 + }, + { + "epoch": 0.5, + "learning_rate": 1.0501671071821064e-05, + "loss": 0.7909, + "step": 2595 + }, + { + "epoch": 0.5, + "learning_rate": 1.0495444269269434e-05, + "loss": 0.8185, + "step": 2596 + }, + { + "epoch": 0.5, + "learning_rate": 1.0489217274140185e-05, + "loss": 0.7584, + "step": 2597 + }, + { + "epoch": 0.5, + "learning_rate": 1.0482990088853721e-05, + "loss": 0.8072, + "step": 2598 + }, + { + "epoch": 0.5, + "learning_rate": 1.0476762715830538e-05, + "loss": 0.8226, + "step": 2599 + }, + { + "epoch": 0.5, + "learning_rate": 1.0470535157491189e-05, + "loss": 0.803, + "step": 2600 + }, + { + "epoch": 0.5, + "learning_rate": 1.046430741625631e-05, + "loss": 0.7861, + "step": 2601 + }, + { + "epoch": 0.5, + "learning_rate": 1.0458079494546605e-05, + "loss": 0.8536, + "step": 2602 + }, + { + "epoch": 0.5, + "learning_rate": 1.0451851394782844e-05, + "loss": 0.794, + "step": 2603 + }, + { + "epoch": 0.5, + "learning_rate": 1.044562311938587e-05, + "loss": 0.8183, + "step": 2604 + }, + { + "epoch": 0.5, + "learning_rate": 1.0439394670776598e-05, + "loss": 0.7972, + "step": 2605 + }, + { + "epoch": 0.5, + "learning_rate": 1.0433166051376007e-05, + "loss": 0.8253, + "step": 2606 + }, + { + "epoch": 0.5, + "learning_rate": 1.0426937263605135e-05, + "loss": 0.8289, + "step": 2607 + }, + { + "epoch": 0.5, + "learning_rate": 1.0420708309885096e-05, + "loss": 0.7848, + "step": 2608 + }, + { + "epoch": 0.5, + "learning_rate": 1.0414479192637065e-05, + "loss": 0.7619, + "step": 2609 + }, + { + "epoch": 0.5, + "learning_rate": 1.040824991428228e-05, + "loss": 0.8076, + "step": 2610 + }, + { + "epoch": 0.5, + "learning_rate": 1.0402020477242043e-05, + "loss": 0.858, + "step": 2611 + }, + { + "epoch": 0.5, + "learning_rate": 1.0395790883937718e-05, + "loss": 0.753, + "step": 2612 + }, + { + "epoch": 0.5, + "learning_rate": 1.038956113679072e-05, + "loss": 0.8197, + "step": 2613 + }, + { + "epoch": 0.5, + "learning_rate": 1.0383331238222539e-05, + "loss": 0.7958, + "step": 2614 + }, + { + "epoch": 0.5, + "learning_rate": 1.0377101190654716e-05, + "loss": 0.8188, + "step": 2615 + }, + { + "epoch": 0.5, + "learning_rate": 1.0370870996508849e-05, + "loss": 0.8358, + "step": 2616 + }, + { + "epoch": 0.5, + "learning_rate": 1.03646406582066e-05, + "loss": 0.76, + "step": 2617 + }, + { + "epoch": 0.5, + "learning_rate": 1.0358410178169673e-05, + "loss": 0.8385, + "step": 2618 + }, + { + "epoch": 0.5, + "learning_rate": 1.0352179558819844e-05, + "loss": 0.7664, + "step": 2619 + }, + { + "epoch": 0.5, + "learning_rate": 1.0345948802578932e-05, + "loss": 0.8307, + "step": 2620 + }, + { + "epoch": 0.5, + "learning_rate": 1.0339717911868808e-05, + "loss": 0.8024, + "step": 2621 + }, + { + "epoch": 0.5, + "learning_rate": 1.0333486889111408e-05, + "loss": 0.8101, + "step": 2622 + }, + { + "epoch": 0.5, + "learning_rate": 1.0327255736728707e-05, + "loss": 0.7777, + "step": 2623 + }, + { + "epoch": 0.51, + "learning_rate": 1.0321024457142732e-05, + "loss": 0.795, + "step": 2624 + }, + { + "epoch": 0.51, + "learning_rate": 1.0314793052775563e-05, + "loss": 0.8482, + "step": 2625 + }, + { + "epoch": 0.51, + "learning_rate": 1.0308561526049327e-05, + "loss": 0.7572, + "step": 2626 + }, + { + "epoch": 0.51, + "learning_rate": 1.0302329879386203e-05, + "loss": 1.3093, + "step": 2627 + }, + { + "epoch": 0.51, + "learning_rate": 1.0296098115208408e-05, + "loss": 0.834, + "step": 2628 + }, + { + "epoch": 0.51, + "learning_rate": 1.0289866235938208e-05, + "loss": 0.8352, + "step": 2629 + }, + { + "epoch": 0.51, + "learning_rate": 1.0283634243997917e-05, + "loss": 0.8238, + "step": 2630 + }, + { + "epoch": 0.51, + "learning_rate": 1.0277402141809891e-05, + "loss": 0.8225, + "step": 2631 + }, + { + "epoch": 0.51, + "learning_rate": 1.027116993179653e-05, + "loss": 0.8036, + "step": 2632 + }, + { + "epoch": 0.51, + "learning_rate": 1.0264937616380274e-05, + "loss": 0.7977, + "step": 2633 + }, + { + "epoch": 0.51, + "learning_rate": 1.0258705197983598e-05, + "loss": 0.7948, + "step": 2634 + }, + { + "epoch": 0.51, + "learning_rate": 1.0252472679029028e-05, + "loss": 0.7632, + "step": 2635 + }, + { + "epoch": 0.51, + "learning_rate": 1.0246240061939128e-05, + "loss": 0.8038, + "step": 2636 + }, + { + "epoch": 0.51, + "learning_rate": 1.0240007349136489e-05, + "loss": 0.8068, + "step": 2637 + }, + { + "epoch": 0.51, + "learning_rate": 1.0233774543043753e-05, + "loss": 0.7927, + "step": 2638 + }, + { + "epoch": 0.51, + "learning_rate": 1.022754164608359e-05, + "loss": 1.3129, + "step": 2639 + }, + { + "epoch": 0.51, + "learning_rate": 1.0221308660678708e-05, + "loss": 0.8112, + "step": 2640 + }, + { + "epoch": 0.51, + "learning_rate": 1.0215075589251846e-05, + "loss": 0.8205, + "step": 2641 + }, + { + "epoch": 0.51, + "learning_rate": 1.020884243422578e-05, + "loss": 0.8345, + "step": 2642 + }, + { + "epoch": 0.51, + "learning_rate": 1.0202609198023324e-05, + "loss": 0.8114, + "step": 2643 + }, + { + "epoch": 0.51, + "learning_rate": 1.0196375883067309e-05, + "loss": 0.8227, + "step": 2644 + }, + { + "epoch": 0.51, + "learning_rate": 1.0190142491780608e-05, + "loss": 0.8405, + "step": 2645 + }, + { + "epoch": 0.51, + "learning_rate": 1.0183909026586118e-05, + "loss": 0.8283, + "step": 2646 + }, + { + "epoch": 0.51, + "learning_rate": 1.0177675489906773e-05, + "loss": 0.7871, + "step": 2647 + }, + { + "epoch": 0.51, + "learning_rate": 1.0171441884165524e-05, + "loss": 0.8091, + "step": 2648 + }, + { + "epoch": 0.51, + "learning_rate": 1.016520821178536e-05, + "loss": 0.7876, + "step": 2649 + }, + { + "epoch": 0.51, + "learning_rate": 1.015897447518928e-05, + "loss": 0.7895, + "step": 2650 + }, + { + "epoch": 0.51, + "learning_rate": 1.0152740676800326e-05, + "loss": 0.8351, + "step": 2651 + }, + { + "epoch": 0.51, + "learning_rate": 1.014650681904155e-05, + "loss": 0.8216, + "step": 2652 + }, + { + "epoch": 0.51, + "learning_rate": 1.014027290433604e-05, + "loss": 0.8282, + "step": 2653 + }, + { + "epoch": 0.51, + "learning_rate": 1.0134038935106892e-05, + "loss": 0.7689, + "step": 2654 + }, + { + "epoch": 0.51, + "learning_rate": 1.0127804913777235e-05, + "loss": 0.7819, + "step": 2655 + }, + { + "epoch": 0.51, + "learning_rate": 1.012157084277021e-05, + "loss": 0.8065, + "step": 2656 + }, + { + "epoch": 0.51, + "learning_rate": 1.0115336724508984e-05, + "loss": 0.8574, + "step": 2657 + }, + { + "epoch": 0.51, + "learning_rate": 1.0109102561416732e-05, + "loss": 0.7351, + "step": 2658 + }, + { + "epoch": 0.51, + "learning_rate": 1.0102868355916662e-05, + "loss": 0.7974, + "step": 2659 + }, + { + "epoch": 0.51, + "learning_rate": 1.0096634110431989e-05, + "loss": 0.7762, + "step": 2660 + }, + { + "epoch": 0.51, + "learning_rate": 1.0090399827385942e-05, + "loss": 0.7998, + "step": 2661 + }, + { + "epoch": 0.51, + "learning_rate": 1.0084165509201764e-05, + "loss": 0.8414, + "step": 2662 + }, + { + "epoch": 0.51, + "learning_rate": 1.0077931158302718e-05, + "loss": 0.8146, + "step": 2663 + }, + { + "epoch": 0.51, + "learning_rate": 1.0071696777112076e-05, + "loss": 0.8235, + "step": 2664 + }, + { + "epoch": 0.51, + "learning_rate": 1.0065462368053127e-05, + "loss": 0.823, + "step": 2665 + }, + { + "epoch": 0.51, + "learning_rate": 1.0059227933549163e-05, + "loss": 0.7725, + "step": 2666 + }, + { + "epoch": 0.51, + "learning_rate": 1.0052993476023485e-05, + "loss": 0.8385, + "step": 2667 + }, + { + "epoch": 0.51, + "learning_rate": 1.0046758997899409e-05, + "loss": 0.821, + "step": 2668 + }, + { + "epoch": 0.51, + "learning_rate": 1.0040524501600259e-05, + "loss": 0.7842, + "step": 2669 + }, + { + "epoch": 0.51, + "learning_rate": 1.0034289989549364e-05, + "loss": 0.8497, + "step": 2670 + }, + { + "epoch": 0.51, + "learning_rate": 1.002805546417006e-05, + "loss": 0.7666, + "step": 2671 + }, + { + "epoch": 0.51, + "learning_rate": 1.0021820927885684e-05, + "loss": 0.8077, + "step": 2672 + }, + { + "epoch": 0.51, + "learning_rate": 1.001558638311958e-05, + "loss": 0.8067, + "step": 2673 + }, + { + "epoch": 0.51, + "learning_rate": 1.0009351832295103e-05, + "loss": 0.8182, + "step": 2674 + }, + { + "epoch": 0.51, + "learning_rate": 1.0003117277835593e-05, + "loss": 0.8125, + "step": 2675 + }, + { + "epoch": 0.52, + "learning_rate": 9.99688272216441e-06, + "loss": 1.3756, + "step": 2676 + }, + { + "epoch": 0.52, + "learning_rate": 9.990648167704904e-06, + "loss": 0.8025, + "step": 2677 + }, + { + "epoch": 0.52, + "learning_rate": 9.984413616880422e-06, + "loss": 0.823, + "step": 2678 + }, + { + "epoch": 0.52, + "learning_rate": 9.97817907211432e-06, + "loss": 0.7877, + "step": 2679 + }, + { + "epoch": 0.52, + "learning_rate": 9.971944535829943e-06, + "loss": 1.3349, + "step": 2680 + }, + { + "epoch": 0.52, + "learning_rate": 9.965710010450637e-06, + "loss": 1.328, + "step": 2681 + }, + { + "epoch": 0.52, + "learning_rate": 9.959475498399743e-06, + "loss": 0.7768, + "step": 2682 + }, + { + "epoch": 0.52, + "learning_rate": 9.953241002100593e-06, + "loss": 0.8324, + "step": 2683 + }, + { + "epoch": 0.52, + "learning_rate": 9.94700652397652e-06, + "loss": 0.749, + "step": 2684 + }, + { + "epoch": 0.52, + "learning_rate": 9.940772066450842e-06, + "loss": 0.778, + "step": 2685 + }, + { + "epoch": 0.52, + "learning_rate": 9.934537631946875e-06, + "loss": 0.6959, + "step": 2686 + }, + { + "epoch": 0.52, + "learning_rate": 9.928303222887925e-06, + "loss": 0.7837, + "step": 2687 + }, + { + "epoch": 0.52, + "learning_rate": 9.922068841697284e-06, + "loss": 0.8089, + "step": 2688 + }, + { + "epoch": 0.52, + "learning_rate": 9.915834490798239e-06, + "loss": 1.3238, + "step": 2689 + }, + { + "epoch": 0.52, + "learning_rate": 9.909600172614062e-06, + "loss": 0.8041, + "step": 2690 + }, + { + "epoch": 0.52, + "learning_rate": 9.903365889568015e-06, + "loss": 0.7887, + "step": 2691 + }, + { + "epoch": 0.52, + "learning_rate": 9.897131644083338e-06, + "loss": 0.8017, + "step": 2692 + }, + { + "epoch": 0.52, + "learning_rate": 9.890897438583271e-06, + "loss": 0.8013, + "step": 2693 + }, + { + "epoch": 0.52, + "learning_rate": 9.884663275491023e-06, + "loss": 0.789, + "step": 2694 + }, + { + "epoch": 0.52, + "learning_rate": 9.878429157229792e-06, + "loss": 0.7431, + "step": 2695 + }, + { + "epoch": 0.52, + "learning_rate": 9.872195086222768e-06, + "loss": 0.7232, + "step": 2696 + }, + { + "epoch": 0.52, + "learning_rate": 9.86596106489311e-06, + "loss": 0.7764, + "step": 2697 + }, + { + "epoch": 0.52, + "learning_rate": 9.859727095663962e-06, + "loss": 0.8183, + "step": 2698 + }, + { + "epoch": 0.52, + "learning_rate": 9.853493180958449e-06, + "loss": 0.7589, + "step": 2699 + }, + { + "epoch": 0.52, + "learning_rate": 9.847259323199674e-06, + "loss": 0.7882, + "step": 2700 + }, + { + "epoch": 0.52, + "learning_rate": 9.841025524810724e-06, + "loss": 0.7997, + "step": 2701 + }, + { + "epoch": 0.52, + "learning_rate": 9.834791788214645e-06, + "loss": 0.7209, + "step": 2702 + }, + { + "epoch": 0.52, + "learning_rate": 9.828558115834477e-06, + "loss": 0.8503, + "step": 2703 + }, + { + "epoch": 0.52, + "learning_rate": 9.82232451009323e-06, + "loss": 0.7985, + "step": 2704 + }, + { + "epoch": 0.52, + "learning_rate": 9.816090973413885e-06, + "loss": 0.7912, + "step": 2705 + }, + { + "epoch": 0.52, + "learning_rate": 9.809857508219395e-06, + "loss": 0.8438, + "step": 2706 + }, + { + "epoch": 0.52, + "learning_rate": 9.803624116932695e-06, + "loss": 0.7951, + "step": 2707 + }, + { + "epoch": 0.52, + "learning_rate": 9.79739080197668e-06, + "loss": 0.8036, + "step": 2708 + }, + { + "epoch": 0.52, + "learning_rate": 9.79115756577422e-06, + "loss": 0.767, + "step": 2709 + }, + { + "epoch": 0.52, + "learning_rate": 9.784924410748159e-06, + "loss": 0.8279, + "step": 2710 + }, + { + "epoch": 0.52, + "learning_rate": 9.778691339321297e-06, + "loss": 0.7439, + "step": 2711 + }, + { + "epoch": 0.52, + "learning_rate": 9.772458353916413e-06, + "loss": 0.8204, + "step": 2712 + }, + { + "epoch": 0.52, + "learning_rate": 9.766225456956248e-06, + "loss": 0.8565, + "step": 2713 + }, + { + "epoch": 0.52, + "learning_rate": 9.759992650863513e-06, + "loss": 0.8241, + "step": 2714 + }, + { + "epoch": 0.52, + "learning_rate": 9.753759938060875e-06, + "loss": 0.8002, + "step": 2715 + }, + { + "epoch": 0.52, + "learning_rate": 9.747527320970974e-06, + "loss": 0.7275, + "step": 2716 + }, + { + "epoch": 0.52, + "learning_rate": 9.741294802016403e-06, + "loss": 0.8299, + "step": 2717 + }, + { + "epoch": 0.52, + "learning_rate": 9.735062383619731e-06, + "loss": 0.7883, + "step": 2718 + }, + { + "epoch": 0.52, + "learning_rate": 9.728830068203472e-06, + "loss": 0.8062, + "step": 2719 + }, + { + "epoch": 0.52, + "learning_rate": 9.722597858190112e-06, + "loss": 0.7878, + "step": 2720 + }, + { + "epoch": 0.52, + "learning_rate": 9.716365756002086e-06, + "loss": 0.7148, + "step": 2721 + }, + { + "epoch": 0.52, + "learning_rate": 9.710133764061795e-06, + "loss": 0.8883, + "step": 2722 + }, + { + "epoch": 0.52, + "learning_rate": 9.703901884791594e-06, + "loss": 0.8265, + "step": 2723 + }, + { + "epoch": 0.52, + "learning_rate": 9.6976701206138e-06, + "loss": 0.806, + "step": 2724 + }, + { + "epoch": 0.52, + "learning_rate": 9.691438473950674e-06, + "loss": 0.7874, + "step": 2725 + }, + { + "epoch": 0.52, + "learning_rate": 9.685206947224437e-06, + "loss": 0.7912, + "step": 2726 + }, + { + "epoch": 0.52, + "learning_rate": 9.678975542857275e-06, + "loss": 0.7579, + "step": 2727 + }, + { + "epoch": 0.53, + "learning_rate": 9.6727442632713e-06, + "loss": 0.7589, + "step": 2728 + }, + { + "epoch": 0.53, + "learning_rate": 9.666513110888595e-06, + "loss": 0.7848, + "step": 2729 + }, + { + "epoch": 0.53, + "learning_rate": 9.660282088131193e-06, + "loss": 0.8149, + "step": 2730 + }, + { + "epoch": 0.53, + "learning_rate": 9.654051197421073e-06, + "loss": 0.8901, + "step": 2731 + }, + { + "epoch": 0.53, + "learning_rate": 9.647820441180159e-06, + "loss": 0.7844, + "step": 2732 + }, + { + "epoch": 0.53, + "learning_rate": 9.641589821830326e-06, + "loss": 0.7956, + "step": 2733 + }, + { + "epoch": 0.53, + "learning_rate": 9.635359341793404e-06, + "loss": 0.7724, + "step": 2734 + }, + { + "epoch": 0.53, + "learning_rate": 9.629129003491153e-06, + "loss": 0.8569, + "step": 2735 + }, + { + "epoch": 0.53, + "learning_rate": 9.622898809345289e-06, + "loss": 0.8116, + "step": 2736 + }, + { + "epoch": 0.53, + "learning_rate": 9.616668761777465e-06, + "loss": 0.7914, + "step": 2737 + }, + { + "epoch": 0.53, + "learning_rate": 9.610438863209284e-06, + "loss": 0.8362, + "step": 2738 + }, + { + "epoch": 0.53, + "learning_rate": 9.604209116062286e-06, + "loss": 0.8204, + "step": 2739 + }, + { + "epoch": 0.53, + "learning_rate": 9.59797952275796e-06, + "loss": 0.8028, + "step": 2740 + }, + { + "epoch": 0.53, + "learning_rate": 9.59175008571772e-06, + "loss": 0.7854, + "step": 2741 + }, + { + "epoch": 0.53, + "learning_rate": 9.585520807362936e-06, + "loss": 0.8089, + "step": 2742 + }, + { + "epoch": 0.53, + "learning_rate": 9.579291690114903e-06, + "loss": 0.801, + "step": 2743 + }, + { + "epoch": 0.53, + "learning_rate": 9.573062736394868e-06, + "loss": 0.7886, + "step": 2744 + }, + { + "epoch": 0.53, + "learning_rate": 9.566833948623999e-06, + "loss": 0.8356, + "step": 2745 + }, + { + "epoch": 0.53, + "learning_rate": 9.560605329223406e-06, + "loss": 0.8171, + "step": 2746 + }, + { + "epoch": 0.53, + "learning_rate": 9.554376880614133e-06, + "loss": 0.7986, + "step": 2747 + }, + { + "epoch": 0.53, + "learning_rate": 9.54814860521716e-06, + "loss": 0.8701, + "step": 2748 + }, + { + "epoch": 0.53, + "learning_rate": 9.5419205054534e-06, + "loss": 0.8156, + "step": 2749 + }, + { + "epoch": 0.53, + "learning_rate": 9.535692583743691e-06, + "loss": 0.8201, + "step": 2750 + }, + { + "epoch": 0.53, + "learning_rate": 9.529464842508813e-06, + "loss": 0.7353, + "step": 2751 + }, + { + "epoch": 0.53, + "learning_rate": 9.523237284169469e-06, + "loss": 0.7944, + "step": 2752 + }, + { + "epoch": 0.53, + "learning_rate": 9.517009911146282e-06, + "loss": 0.8205, + "step": 2753 + }, + { + "epoch": 0.53, + "learning_rate": 9.51078272585982e-06, + "loss": 0.7705, + "step": 2754 + }, + { + "epoch": 0.53, + "learning_rate": 9.504555730730567e-06, + "loss": 1.3912, + "step": 2755 + }, + { + "epoch": 0.53, + "learning_rate": 9.49832892817894e-06, + "loss": 0.8136, + "step": 2756 + }, + { + "epoch": 0.53, + "learning_rate": 9.492102320625275e-06, + "loss": 0.8263, + "step": 2757 + }, + { + "epoch": 0.53, + "learning_rate": 9.485875910489835e-06, + "loss": 0.7837, + "step": 2758 + }, + { + "epoch": 0.53, + "learning_rate": 9.479649700192805e-06, + "loss": 0.8108, + "step": 2759 + }, + { + "epoch": 0.53, + "learning_rate": 9.473423692154299e-06, + "loss": 0.827, + "step": 2760 + }, + { + "epoch": 0.53, + "learning_rate": 9.467197888794338e-06, + "loss": 0.8268, + "step": 2761 + }, + { + "epoch": 0.53, + "learning_rate": 9.460972292532876e-06, + "loss": 0.7982, + "step": 2762 + }, + { + "epoch": 0.53, + "learning_rate": 9.454746905789785e-06, + "loss": 0.767, + "step": 2763 + }, + { + "epoch": 0.53, + "learning_rate": 9.448521730984848e-06, + "loss": 0.8283, + "step": 2764 + }, + { + "epoch": 0.53, + "learning_rate": 9.442296770537775e-06, + "loss": 0.7894, + "step": 2765 + }, + { + "epoch": 0.53, + "learning_rate": 9.436072026868186e-06, + "loss": 0.7279, + "step": 2766 + }, + { + "epoch": 0.53, + "learning_rate": 9.429847502395623e-06, + "loss": 0.7667, + "step": 2767 + }, + { + "epoch": 0.53, + "learning_rate": 9.423623199539536e-06, + "loss": 0.7563, + "step": 2768 + }, + { + "epoch": 0.53, + "learning_rate": 9.417399120719296e-06, + "loss": 0.7294, + "step": 2769 + }, + { + "epoch": 0.53, + "learning_rate": 9.411175268354174e-06, + "loss": 0.8583, + "step": 2770 + }, + { + "epoch": 0.53, + "learning_rate": 9.404951644863367e-06, + "loss": 0.8191, + "step": 2771 + }, + { + "epoch": 0.53, + "learning_rate": 9.398728252665978e-06, + "loss": 1.2408, + "step": 2772 + }, + { + "epoch": 0.53, + "learning_rate": 9.392505094181023e-06, + "loss": 0.8301, + "step": 2773 + }, + { + "epoch": 0.53, + "learning_rate": 9.386282171827417e-06, + "loss": 0.7375, + "step": 2774 + }, + { + "epoch": 0.53, + "learning_rate": 9.380059488023995e-06, + "loss": 0.7588, + "step": 2775 + }, + { + "epoch": 0.53, + "learning_rate": 9.373837045189494e-06, + "loss": 0.8237, + "step": 2776 + }, + { + "epoch": 0.53, + "learning_rate": 9.36761484574256e-06, + "loss": 0.8353, + "step": 2777 + }, + { + "epoch": 0.53, + "learning_rate": 9.361392892101735e-06, + "loss": 0.7639, + "step": 2778 + }, + { + "epoch": 0.53, + "learning_rate": 9.355171186685483e-06, + "loss": 0.7314, + "step": 2779 + }, + { + "epoch": 0.54, + "learning_rate": 9.34894973191215e-06, + "loss": 0.8213, + "step": 2780 + }, + { + "epoch": 0.54, + "learning_rate": 9.342728530200005e-06, + "loss": 0.8365, + "step": 2781 + }, + { + "epoch": 0.54, + "learning_rate": 9.336507583967204e-06, + "loss": 0.8282, + "step": 2782 + }, + { + "epoch": 0.54, + "learning_rate": 9.330286895631814e-06, + "loss": 0.7968, + "step": 2783 + }, + { + "epoch": 0.54, + "learning_rate": 9.324066467611792e-06, + "loss": 1.2637, + "step": 2784 + }, + { + "epoch": 0.54, + "learning_rate": 9.317846302325e-06, + "loss": 0.7585, + "step": 2785 + }, + { + "epoch": 0.54, + "learning_rate": 9.311626402189202e-06, + "loss": 0.7363, + "step": 2786 + }, + { + "epoch": 0.54, + "learning_rate": 9.305406769622046e-06, + "loss": 0.7812, + "step": 2787 + }, + { + "epoch": 0.54, + "learning_rate": 9.299187407041087e-06, + "loss": 0.8045, + "step": 2788 + }, + { + "epoch": 0.54, + "learning_rate": 9.29296831686377e-06, + "loss": 0.7645, + "step": 2789 + }, + { + "epoch": 0.54, + "learning_rate": 9.286749501507438e-06, + "loss": 0.8475, + "step": 2790 + }, + { + "epoch": 0.54, + "learning_rate": 9.280530963389324e-06, + "loss": 0.7968, + "step": 2791 + }, + { + "epoch": 0.54, + "learning_rate": 9.274312704926553e-06, + "loss": 0.8028, + "step": 2792 + }, + { + "epoch": 0.54, + "learning_rate": 9.268094728536144e-06, + "loss": 0.82, + "step": 2793 + }, + { + "epoch": 0.54, + "learning_rate": 9.261877036635007e-06, + "loss": 0.7725, + "step": 2794 + }, + { + "epoch": 0.54, + "learning_rate": 9.255659631639934e-06, + "loss": 0.8018, + "step": 2795 + }, + { + "epoch": 0.54, + "learning_rate": 9.249442515967614e-06, + "loss": 0.8472, + "step": 2796 + }, + { + "epoch": 0.54, + "learning_rate": 9.243225692034617e-06, + "loss": 0.752, + "step": 2797 + }, + { + "epoch": 0.54, + "learning_rate": 9.237009162257407e-06, + "loss": 0.7229, + "step": 2798 + }, + { + "epoch": 0.54, + "learning_rate": 9.230792929052326e-06, + "loss": 0.78, + "step": 2799 + }, + { + "epoch": 0.54, + "learning_rate": 9.22457699483561e-06, + "loss": 0.7959, + "step": 2800 + }, + { + "epoch": 0.54, + "learning_rate": 9.218361362023365e-06, + "loss": 0.7893, + "step": 2801 + }, + { + "epoch": 0.54, + "learning_rate": 9.212146033031593e-06, + "loss": 0.8494, + "step": 2802 + }, + { + "epoch": 0.54, + "learning_rate": 9.205931010276174e-06, + "loss": 0.8163, + "step": 2803 + }, + { + "epoch": 0.54, + "learning_rate": 9.199716296172864e-06, + "loss": 0.7644, + "step": 2804 + }, + { + "epoch": 0.54, + "learning_rate": 9.193501893137302e-06, + "loss": 1.2571, + "step": 2805 + }, + { + "epoch": 0.54, + "learning_rate": 9.187287803585013e-06, + "loss": 0.7978, + "step": 2806 + }, + { + "epoch": 0.54, + "learning_rate": 9.181074029931386e-06, + "loss": 0.7711, + "step": 2807 + }, + { + "epoch": 0.54, + "learning_rate": 9.1748605745917e-06, + "loss": 0.7961, + "step": 2808 + }, + { + "epoch": 0.54, + "learning_rate": 9.168647439981104e-06, + "loss": 0.7365, + "step": 2809 + }, + { + "epoch": 0.54, + "learning_rate": 9.162434628514627e-06, + "loss": 0.8205, + "step": 2810 + }, + { + "epoch": 0.54, + "learning_rate": 9.156222142607167e-06, + "loss": 0.7842, + "step": 2811 + }, + { + "epoch": 0.54, + "learning_rate": 9.150009984673497e-06, + "loss": 0.8216, + "step": 2812 + }, + { + "epoch": 0.54, + "learning_rate": 9.143798157128262e-06, + "loss": 0.8078, + "step": 2813 + }, + { + "epoch": 0.54, + "learning_rate": 9.13758666238598e-06, + "loss": 0.7648, + "step": 2814 + }, + { + "epoch": 0.54, + "learning_rate": 9.131375502861042e-06, + "loss": 0.7441, + "step": 2815 + }, + { + "epoch": 0.54, + "learning_rate": 9.125164680967706e-06, + "loss": 0.8086, + "step": 2816 + }, + { + "epoch": 0.54, + "learning_rate": 9.118954199120096e-06, + "loss": 0.7872, + "step": 2817 + }, + { + "epoch": 0.54, + "learning_rate": 9.11274405973221e-06, + "loss": 0.8249, + "step": 2818 + }, + { + "epoch": 0.54, + "learning_rate": 9.10653426521791e-06, + "loss": 0.7994, + "step": 2819 + }, + { + "epoch": 0.54, + "learning_rate": 9.100324817990917e-06, + "loss": 0.7911, + "step": 2820 + }, + { + "epoch": 0.54, + "learning_rate": 9.09411572046483e-06, + "loss": 0.7608, + "step": 2821 + }, + { + "epoch": 0.54, + "learning_rate": 9.087906975053105e-06, + "loss": 0.7814, + "step": 2822 + }, + { + "epoch": 0.54, + "learning_rate": 9.081698584169058e-06, + "loss": 0.8191, + "step": 2823 + }, + { + "epoch": 0.54, + "learning_rate": 9.075490550225873e-06, + "loss": 0.8544, + "step": 2824 + }, + { + "epoch": 0.54, + "learning_rate": 9.069282875636593e-06, + "loss": 0.8143, + "step": 2825 + }, + { + "epoch": 0.54, + "learning_rate": 9.063075562814125e-06, + "loss": 0.8062, + "step": 2826 + }, + { + "epoch": 0.54, + "learning_rate": 9.056868614171227e-06, + "loss": 0.7386, + "step": 2827 + }, + { + "epoch": 0.54, + "learning_rate": 9.050662032120527e-06, + "loss": 0.777, + "step": 2828 + }, + { + "epoch": 0.54, + "learning_rate": 9.044455819074493e-06, + "loss": 0.8095, + "step": 2829 + }, + { + "epoch": 0.54, + "learning_rate": 9.038249977445469e-06, + "loss": 1.2888, + "step": 2830 + }, + { + "epoch": 0.54, + "learning_rate": 9.032044509645643e-06, + "loss": 0.7722, + "step": 2831 + }, + { + "epoch": 0.55, + "learning_rate": 9.025839418087063e-06, + "loss": 0.7983, + "step": 2832 + }, + { + "epoch": 0.55, + "learning_rate": 9.019634705181624e-06, + "loss": 0.8176, + "step": 2833 + }, + { + "epoch": 0.55, + "learning_rate": 9.013430373341082e-06, + "loss": 0.772, + "step": 2834 + }, + { + "epoch": 0.55, + "learning_rate": 9.00722642497704e-06, + "loss": 0.8331, + "step": 2835 + }, + { + "epoch": 0.55, + "learning_rate": 9.001022862500959e-06, + "loss": 0.8053, + "step": 2836 + }, + { + "epoch": 0.55, + "learning_rate": 8.994819688324134e-06, + "loss": 0.8266, + "step": 2837 + }, + { + "epoch": 0.55, + "learning_rate": 8.988616904857726e-06, + "loss": 0.742, + "step": 2838 + }, + { + "epoch": 0.55, + "learning_rate": 8.982414514512732e-06, + "loss": 0.7606, + "step": 2839 + }, + { + "epoch": 0.55, + "learning_rate": 8.976212519700007e-06, + "loss": 0.794, + "step": 2840 + }, + { + "epoch": 0.55, + "learning_rate": 8.970010922830244e-06, + "loss": 0.7591, + "step": 2841 + }, + { + "epoch": 0.55, + "learning_rate": 8.963809726313983e-06, + "loss": 0.8041, + "step": 2842 + }, + { + "epoch": 0.55, + "learning_rate": 8.957608932561615e-06, + "loss": 0.799, + "step": 2843 + }, + { + "epoch": 0.55, + "learning_rate": 8.951408543983363e-06, + "loss": 0.8343, + "step": 2844 + }, + { + "epoch": 0.55, + "learning_rate": 8.945208562989306e-06, + "loss": 0.8112, + "step": 2845 + }, + { + "epoch": 0.55, + "learning_rate": 8.939008991989347e-06, + "loss": 0.7825, + "step": 2846 + }, + { + "epoch": 0.55, + "learning_rate": 8.932809833393245e-06, + "loss": 0.8778, + "step": 2847 + }, + { + "epoch": 0.55, + "learning_rate": 8.926611089610592e-06, + "loss": 0.8062, + "step": 2848 + }, + { + "epoch": 0.55, + "learning_rate": 8.920412763050823e-06, + "loss": 0.7708, + "step": 2849 + }, + { + "epoch": 0.55, + "learning_rate": 8.914214856123205e-06, + "loss": 1.3593, + "step": 2850 + }, + { + "epoch": 0.55, + "learning_rate": 8.908017371236843e-06, + "loss": 0.7897, + "step": 2851 + }, + { + "epoch": 0.55, + "learning_rate": 8.901820310800686e-06, + "loss": 0.8305, + "step": 2852 + }, + { + "epoch": 0.55, + "learning_rate": 8.895623677223512e-06, + "loss": 0.7865, + "step": 2853 + }, + { + "epoch": 0.55, + "learning_rate": 8.889427472913925e-06, + "loss": 0.7754, + "step": 2854 + }, + { + "epoch": 0.55, + "learning_rate": 8.883231700280376e-06, + "loss": 0.8067, + "step": 2855 + }, + { + "epoch": 0.55, + "learning_rate": 8.877036361731138e-06, + "loss": 0.85, + "step": 2856 + }, + { + "epoch": 0.55, + "learning_rate": 8.870841459674325e-06, + "loss": 0.7949, + "step": 2857 + }, + { + "epoch": 0.55, + "learning_rate": 8.864646996517871e-06, + "loss": 0.8646, + "step": 2858 + }, + { + "epoch": 0.55, + "learning_rate": 8.858452974669547e-06, + "loss": 0.7696, + "step": 2859 + }, + { + "epoch": 0.55, + "learning_rate": 8.85225939653695e-06, + "loss": 0.7748, + "step": 2860 + }, + { + "epoch": 0.55, + "learning_rate": 8.846066264527504e-06, + "loss": 0.7586, + "step": 2861 + }, + { + "epoch": 0.55, + "learning_rate": 8.839873581048462e-06, + "loss": 0.78, + "step": 2862 + }, + { + "epoch": 0.55, + "learning_rate": 8.833681348506894e-06, + "loss": 0.7954, + "step": 2863 + }, + { + "epoch": 0.55, + "learning_rate": 8.827489569309705e-06, + "loss": 0.7575, + "step": 2864 + }, + { + "epoch": 0.55, + "learning_rate": 8.821298245863621e-06, + "loss": 0.8047, + "step": 2865 + }, + { + "epoch": 0.55, + "learning_rate": 8.81510738057519e-06, + "loss": 0.8135, + "step": 2866 + }, + { + "epoch": 0.55, + "learning_rate": 8.808916975850778e-06, + "loss": 0.8078, + "step": 2867 + }, + { + "epoch": 0.55, + "learning_rate": 8.80272703409658e-06, + "loss": 0.7785, + "step": 2868 + }, + { + "epoch": 0.55, + "learning_rate": 8.796537557718608e-06, + "loss": 0.7388, + "step": 2869 + }, + { + "epoch": 0.55, + "learning_rate": 8.790348549122689e-06, + "loss": 0.7856, + "step": 2870 + }, + { + "epoch": 0.55, + "learning_rate": 8.78416001071447e-06, + "loss": 0.8094, + "step": 2871 + }, + { + "epoch": 0.55, + "learning_rate": 8.777971944899417e-06, + "loss": 0.754, + "step": 2872 + }, + { + "epoch": 0.55, + "learning_rate": 8.771784354082812e-06, + "loss": 0.797, + "step": 2873 + }, + { + "epoch": 0.55, + "learning_rate": 8.765597240669755e-06, + "loss": 0.7877, + "step": 2874 + }, + { + "epoch": 0.55, + "learning_rate": 8.759410607065154e-06, + "loss": 0.8112, + "step": 2875 + }, + { + "epoch": 0.55, + "learning_rate": 8.753224455673734e-06, + "loss": 0.839, + "step": 2876 + }, + { + "epoch": 0.55, + "learning_rate": 8.747038788900033e-06, + "loss": 0.7578, + "step": 2877 + }, + { + "epoch": 0.55, + "learning_rate": 8.740853609148402e-06, + "loss": 0.8096, + "step": 2878 + }, + { + "epoch": 0.55, + "learning_rate": 8.734668918823003e-06, + "loss": 0.7659, + "step": 2879 + }, + { + "epoch": 0.55, + "learning_rate": 8.728484720327797e-06, + "loss": 0.7669, + "step": 2880 + }, + { + "epoch": 0.55, + "learning_rate": 8.72230101606657e-06, + "loss": 0.772, + "step": 2881 + }, + { + "epoch": 0.55, + "learning_rate": 8.716117808442905e-06, + "loss": 0.7559, + "step": 2882 + }, + { + "epoch": 0.55, + "learning_rate": 8.709935099860194e-06, + "loss": 0.8116, + "step": 2883 + }, + { + "epoch": 0.56, + "learning_rate": 8.70375289272164e-06, + "loss": 0.7873, + "step": 2884 + }, + { + "epoch": 0.56, + "learning_rate": 8.697571189430247e-06, + "loss": 0.8337, + "step": 2885 + }, + { + "epoch": 0.56, + "learning_rate": 8.691389992388822e-06, + "loss": 0.8265, + "step": 2886 + }, + { + "epoch": 0.56, + "learning_rate": 8.68520930399998e-06, + "loss": 0.7904, + "step": 2887 + }, + { + "epoch": 0.56, + "learning_rate": 8.679029126666129e-06, + "loss": 0.7702, + "step": 2888 + }, + { + "epoch": 0.56, + "learning_rate": 8.672849462789487e-06, + "loss": 0.7531, + "step": 2889 + }, + { + "epoch": 0.56, + "learning_rate": 8.66667031477207e-06, + "loss": 0.8202, + "step": 2890 + }, + { + "epoch": 0.56, + "learning_rate": 8.660491685015697e-06, + "loss": 0.7714, + "step": 2891 + }, + { + "epoch": 0.56, + "learning_rate": 8.654313575921975e-06, + "loss": 0.8459, + "step": 2892 + }, + { + "epoch": 0.56, + "learning_rate": 8.648135989892322e-06, + "loss": 0.7553, + "step": 2893 + }, + { + "epoch": 0.56, + "learning_rate": 8.641958929327942e-06, + "loss": 0.8233, + "step": 2894 + }, + { + "epoch": 0.56, + "learning_rate": 8.635782396629844e-06, + "loss": 0.7823, + "step": 2895 + }, + { + "epoch": 0.56, + "learning_rate": 8.62960639419882e-06, + "loss": 0.7784, + "step": 2896 + }, + { + "epoch": 0.56, + "learning_rate": 8.623430924435465e-06, + "loss": 0.7511, + "step": 2897 + }, + { + "epoch": 0.56, + "learning_rate": 8.617255989740169e-06, + "loss": 0.7975, + "step": 2898 + }, + { + "epoch": 0.56, + "learning_rate": 8.611081592513103e-06, + "loss": 0.7601, + "step": 2899 + }, + { + "epoch": 0.56, + "learning_rate": 8.604907735154239e-06, + "loss": 0.8105, + "step": 2900 + }, + { + "epoch": 0.56, + "learning_rate": 8.598734420063335e-06, + "loss": 0.8206, + "step": 2901 + }, + { + "epoch": 0.56, + "learning_rate": 8.592561649639942e-06, + "loss": 0.8912, + "step": 2902 + }, + { + "epoch": 0.56, + "learning_rate": 8.586389426283393e-06, + "loss": 0.7742, + "step": 2903 + }, + { + "epoch": 0.56, + "learning_rate": 8.580217752392817e-06, + "loss": 0.7975, + "step": 2904 + }, + { + "epoch": 0.56, + "learning_rate": 8.574046630367114e-06, + "loss": 0.7939, + "step": 2905 + }, + { + "epoch": 0.56, + "learning_rate": 8.567876062604989e-06, + "loss": 0.7736, + "step": 2906 + }, + { + "epoch": 0.56, + "learning_rate": 8.561706051504917e-06, + "loss": 0.7582, + "step": 2907 + }, + { + "epoch": 0.56, + "learning_rate": 8.555536599465166e-06, + "loss": 0.7766, + "step": 2908 + }, + { + "epoch": 0.56, + "learning_rate": 8.549367708883777e-06, + "loss": 0.8044, + "step": 2909 + }, + { + "epoch": 0.56, + "learning_rate": 8.543199382158583e-06, + "loss": 0.7675, + "step": 2910 + }, + { + "epoch": 0.56, + "learning_rate": 8.53703162168719e-06, + "loss": 0.7563, + "step": 2911 + }, + { + "epoch": 0.56, + "learning_rate": 8.530864429866996e-06, + "loss": 1.3686, + "step": 2912 + }, + { + "epoch": 0.56, + "learning_rate": 8.524697809095156e-06, + "loss": 0.6935, + "step": 2913 + }, + { + "epoch": 0.56, + "learning_rate": 8.518531761768623e-06, + "loss": 0.7884, + "step": 2914 + }, + { + "epoch": 0.56, + "learning_rate": 8.512366290284119e-06, + "loss": 0.7486, + "step": 2915 + }, + { + "epoch": 0.56, + "learning_rate": 8.506201397038142e-06, + "loss": 0.7468, + "step": 2916 + }, + { + "epoch": 0.56, + "learning_rate": 8.500037084426968e-06, + "loss": 0.7433, + "step": 2917 + }, + { + "epoch": 0.56, + "learning_rate": 8.493873354846647e-06, + "loss": 0.8552, + "step": 2918 + }, + { + "epoch": 0.56, + "learning_rate": 8.487710210692999e-06, + "loss": 0.741, + "step": 2919 + }, + { + "epoch": 0.56, + "learning_rate": 8.481547654361619e-06, + "loss": 0.7786, + "step": 2920 + }, + { + "epoch": 0.56, + "learning_rate": 8.475385688247877e-06, + "loss": 0.7863, + "step": 2921 + }, + { + "epoch": 0.56, + "learning_rate": 8.469224314746904e-06, + "loss": 0.8006, + "step": 2922 + }, + { + "epoch": 0.56, + "learning_rate": 8.463063536253607e-06, + "loss": 0.794, + "step": 2923 + }, + { + "epoch": 0.56, + "learning_rate": 8.456903355162667e-06, + "loss": 0.7329, + "step": 2924 + }, + { + "epoch": 0.56, + "learning_rate": 8.450743773868521e-06, + "loss": 0.8645, + "step": 2925 + }, + { + "epoch": 0.56, + "learning_rate": 8.44458479476538e-06, + "loss": 1.4479, + "step": 2926 + }, + { + "epoch": 0.56, + "learning_rate": 8.438426420247221e-06, + "loss": 0.7929, + "step": 2927 + }, + { + "epoch": 0.56, + "learning_rate": 8.432268652707787e-06, + "loss": 0.8403, + "step": 2928 + }, + { + "epoch": 0.56, + "learning_rate": 8.426111494540578e-06, + "loss": 0.7474, + "step": 2929 + }, + { + "epoch": 0.56, + "learning_rate": 8.419954948138867e-06, + "loss": 0.8167, + "step": 2930 + }, + { + "epoch": 0.56, + "learning_rate": 8.413799015895679e-06, + "loss": 0.8305, + "step": 2931 + }, + { + "epoch": 0.56, + "learning_rate": 8.407643700203806e-06, + "loss": 0.7602, + "step": 2932 + }, + { + "epoch": 0.56, + "learning_rate": 8.401489003455802e-06, + "loss": 1.2792, + "step": 2933 + }, + { + "epoch": 0.56, + "learning_rate": 8.395334928043982e-06, + "loss": 0.8034, + "step": 2934 + }, + { + "epoch": 0.56, + "learning_rate": 8.389181476360407e-06, + "loss": 0.8422, + "step": 2935 + }, + { + "epoch": 0.57, + "learning_rate": 8.383028650796908e-06, + "loss": 0.8239, + "step": 2936 + }, + { + "epoch": 0.57, + "learning_rate": 8.37687645374507e-06, + "loss": 0.769, + "step": 2937 + }, + { + "epoch": 0.57, + "learning_rate": 8.370724887596237e-06, + "loss": 0.8292, + "step": 2938 + }, + { + "epoch": 0.57, + "learning_rate": 8.364573954741495e-06, + "loss": 0.8327, + "step": 2939 + }, + { + "epoch": 0.57, + "learning_rate": 8.358423657571698e-06, + "loss": 0.797, + "step": 2940 + }, + { + "epoch": 0.57, + "learning_rate": 8.352273998477442e-06, + "loss": 1.2814, + "step": 2941 + }, + { + "epoch": 0.57, + "learning_rate": 8.346124979849082e-06, + "loss": 0.731, + "step": 2942 + }, + { + "epoch": 0.57, + "learning_rate": 8.339976604076724e-06, + "loss": 0.8337, + "step": 2943 + }, + { + "epoch": 0.57, + "learning_rate": 8.33382887355022e-06, + "loss": 0.7568, + "step": 2944 + }, + { + "epoch": 0.57, + "learning_rate": 8.327681790659179e-06, + "loss": 0.703, + "step": 2945 + }, + { + "epoch": 0.57, + "learning_rate": 8.321535357792947e-06, + "loss": 0.8045, + "step": 2946 + }, + { + "epoch": 0.57, + "learning_rate": 8.315389577340625e-06, + "loss": 1.2868, + "step": 2947 + }, + { + "epoch": 0.57, + "learning_rate": 8.309244451691055e-06, + "loss": 0.7617, + "step": 2948 + }, + { + "epoch": 0.57, + "learning_rate": 8.30309998323283e-06, + "loss": 0.7849, + "step": 2949 + }, + { + "epoch": 0.57, + "learning_rate": 8.296956174354288e-06, + "loss": 0.8032, + "step": 2950 + }, + { + "epoch": 0.57, + "learning_rate": 8.290813027443508e-06, + "loss": 0.7593, + "step": 2951 + }, + { + "epoch": 0.57, + "learning_rate": 8.28467054488831e-06, + "loss": 0.8377, + "step": 2952 + }, + { + "epoch": 0.57, + "learning_rate": 8.278528729076256e-06, + "loss": 0.7263, + "step": 2953 + }, + { + "epoch": 0.57, + "learning_rate": 8.272387582394652e-06, + "loss": 0.7796, + "step": 2954 + }, + { + "epoch": 0.57, + "learning_rate": 8.266247107230548e-06, + "loss": 0.8101, + "step": 2955 + }, + { + "epoch": 0.57, + "learning_rate": 8.260107305970716e-06, + "loss": 1.3075, + "step": 2956 + }, + { + "epoch": 0.57, + "learning_rate": 8.253968181001688e-06, + "loss": 0.7981, + "step": 2957 + }, + { + "epoch": 0.57, + "learning_rate": 8.247829734709716e-06, + "loss": 0.8025, + "step": 2958 + }, + { + "epoch": 0.57, + "learning_rate": 8.241691969480794e-06, + "loss": 1.3402, + "step": 2959 + }, + { + "epoch": 0.57, + "learning_rate": 8.235554887700656e-06, + "loss": 0.8279, + "step": 2960 + }, + { + "epoch": 0.57, + "learning_rate": 8.229418491754766e-06, + "loss": 0.7726, + "step": 2961 + }, + { + "epoch": 0.57, + "learning_rate": 8.22328278402832e-06, + "loss": 0.7381, + "step": 2962 + }, + { + "epoch": 0.57, + "learning_rate": 8.217147766906253e-06, + "loss": 0.8307, + "step": 2963 + }, + { + "epoch": 0.57, + "learning_rate": 8.211013442773218e-06, + "loss": 0.7832, + "step": 2964 + }, + { + "epoch": 0.57, + "learning_rate": 8.204879814013612e-06, + "loss": 0.843, + "step": 2965 + }, + { + "epoch": 0.57, + "learning_rate": 8.198746883011555e-06, + "loss": 1.2771, + "step": 2966 + }, + { + "epoch": 0.57, + "learning_rate": 8.192614652150905e-06, + "loss": 0.8048, + "step": 2967 + }, + { + "epoch": 0.57, + "learning_rate": 8.186483123815233e-06, + "loss": 1.3677, + "step": 2968 + }, + { + "epoch": 0.57, + "learning_rate": 8.180352300387849e-06, + "loss": 0.771, + "step": 2969 + }, + { + "epoch": 0.57, + "learning_rate": 8.174222184251781e-06, + "loss": 0.8077, + "step": 2970 + }, + { + "epoch": 0.57, + "learning_rate": 8.168092777789793e-06, + "loss": 0.7857, + "step": 2971 + }, + { + "epoch": 0.57, + "learning_rate": 8.161964083384357e-06, + "loss": 0.7871, + "step": 2972 + }, + { + "epoch": 0.57, + "learning_rate": 8.155836103417684e-06, + "loss": 0.7237, + "step": 2973 + }, + { + "epoch": 0.57, + "learning_rate": 8.149708840271694e-06, + "loss": 0.7881, + "step": 2974 + }, + { + "epoch": 0.57, + "learning_rate": 8.143582296328041e-06, + "loss": 1.3039, + "step": 2975 + }, + { + "epoch": 0.57, + "learning_rate": 8.13745647396809e-06, + "loss": 0.7868, + "step": 2976 + }, + { + "epoch": 0.57, + "learning_rate": 8.131331375572931e-06, + "loss": 0.8031, + "step": 2977 + }, + { + "epoch": 0.57, + "learning_rate": 8.125207003523368e-06, + "loss": 0.8303, + "step": 2978 + }, + { + "epoch": 0.57, + "learning_rate": 8.119083360199926e-06, + "loss": 0.8214, + "step": 2979 + }, + { + "epoch": 0.57, + "learning_rate": 8.11296044798285e-06, + "loss": 0.7854, + "step": 2980 + }, + { + "epoch": 0.57, + "learning_rate": 8.106838269252088e-06, + "loss": 0.8601, + "step": 2981 + }, + { + "epoch": 0.57, + "learning_rate": 8.100716826387316e-06, + "loss": 0.8163, + "step": 2982 + }, + { + "epoch": 0.57, + "learning_rate": 8.094596121767923e-06, + "loss": 0.7406, + "step": 2983 + }, + { + "epoch": 0.57, + "learning_rate": 8.088476157773002e-06, + "loss": 0.7713, + "step": 2984 + }, + { + "epoch": 0.57, + "learning_rate": 8.082356936781365e-06, + "loss": 0.8311, + "step": 2985 + }, + { + "epoch": 0.57, + "learning_rate": 8.076238461171536e-06, + "loss": 0.7915, + "step": 2986 + }, + { + "epoch": 0.57, + "learning_rate": 8.070120733321746e-06, + "loss": 0.8176, + "step": 2987 + }, + { + "epoch": 0.58, + "learning_rate": 8.064003755609941e-06, + "loss": 0.7989, + "step": 2988 + }, + { + "epoch": 0.58, + "learning_rate": 8.057887530413764e-06, + "loss": 0.8027, + "step": 2989 + }, + { + "epoch": 0.58, + "learning_rate": 8.051772060110572e-06, + "loss": 0.8603, + "step": 2990 + }, + { + "epoch": 0.58, + "learning_rate": 8.045657347077434e-06, + "loss": 0.8168, + "step": 2991 + }, + { + "epoch": 0.58, + "learning_rate": 8.039543393691116e-06, + "loss": 0.8022, + "step": 2992 + }, + { + "epoch": 0.58, + "learning_rate": 8.033430202328094e-06, + "loss": 0.8319, + "step": 2993 + }, + { + "epoch": 0.58, + "learning_rate": 8.02731777536455e-06, + "loss": 0.8167, + "step": 2994 + }, + { + "epoch": 0.58, + "learning_rate": 8.021206115176357e-06, + "loss": 0.7668, + "step": 2995 + }, + { + "epoch": 0.58, + "learning_rate": 8.015095224139104e-06, + "loss": 0.8056, + "step": 2996 + }, + { + "epoch": 0.58, + "learning_rate": 8.008985104628076e-06, + "loss": 0.7956, + "step": 2997 + }, + { + "epoch": 0.58, + "learning_rate": 8.002875759018251e-06, + "loss": 0.7826, + "step": 2998 + }, + { + "epoch": 0.58, + "learning_rate": 7.996767189684315e-06, + "loss": 0.7673, + "step": 2999 + }, + { + "epoch": 0.58, + "learning_rate": 7.990659399000654e-06, + "loss": 0.8133, + "step": 3000 + }, + { + "epoch": 0.58, + "learning_rate": 7.98455238934134e-06, + "loss": 0.742, + "step": 3001 + }, + { + "epoch": 0.58, + "learning_rate": 7.978446163080155e-06, + "loss": 0.7956, + "step": 3002 + }, + { + "epoch": 0.58, + "learning_rate": 7.972340722590564e-06, + "loss": 0.8175, + "step": 3003 + }, + { + "epoch": 0.58, + "learning_rate": 7.966236070245737e-06, + "loss": 0.8302, + "step": 3004 + }, + { + "epoch": 0.58, + "learning_rate": 7.960132208418533e-06, + "loss": 0.7484, + "step": 3005 + }, + { + "epoch": 0.58, + "learning_rate": 7.954029139481501e-06, + "loss": 0.7502, + "step": 3006 + }, + { + "epoch": 0.58, + "learning_rate": 7.947926865806884e-06, + "loss": 0.7719, + "step": 3007 + }, + { + "epoch": 0.58, + "learning_rate": 7.941825389766618e-06, + "loss": 0.7853, + "step": 3008 + }, + { + "epoch": 0.58, + "learning_rate": 7.935724713732328e-06, + "loss": 0.8296, + "step": 3009 + }, + { + "epoch": 0.58, + "learning_rate": 7.929624840075329e-06, + "loss": 0.789, + "step": 3010 + }, + { + "epoch": 0.58, + "learning_rate": 7.92352577116662e-06, + "loss": 0.8031, + "step": 3011 + }, + { + "epoch": 0.58, + "learning_rate": 7.917427509376889e-06, + "loss": 0.7772, + "step": 3012 + }, + { + "epoch": 0.58, + "learning_rate": 7.911330057076514e-06, + "loss": 0.8169, + "step": 3013 + }, + { + "epoch": 0.58, + "learning_rate": 7.905233416635558e-06, + "loss": 0.7848, + "step": 3014 + }, + { + "epoch": 0.58, + "learning_rate": 7.899137590423758e-06, + "loss": 0.7502, + "step": 3015 + }, + { + "epoch": 0.58, + "learning_rate": 7.89304258081055e-06, + "loss": 0.7433, + "step": 3016 + }, + { + "epoch": 0.58, + "learning_rate": 7.886948390165038e-06, + "loss": 0.8532, + "step": 3017 + }, + { + "epoch": 0.58, + "learning_rate": 7.88085502085602e-06, + "loss": 0.7856, + "step": 3018 + }, + { + "epoch": 0.58, + "learning_rate": 7.874762475251966e-06, + "loss": 0.8122, + "step": 3019 + }, + { + "epoch": 0.58, + "learning_rate": 7.868670755721033e-06, + "loss": 0.8116, + "step": 3020 + }, + { + "epoch": 0.58, + "learning_rate": 7.86257986463105e-06, + "loss": 1.3661, + "step": 3021 + }, + { + "epoch": 0.58, + "learning_rate": 7.856489804349532e-06, + "loss": 0.7881, + "step": 3022 + }, + { + "epoch": 0.58, + "learning_rate": 7.850400577243658e-06, + "loss": 1.2617, + "step": 3023 + }, + { + "epoch": 0.58, + "learning_rate": 7.844312185680298e-06, + "loss": 0.7286, + "step": 3024 + }, + { + "epoch": 0.58, + "learning_rate": 7.838224632025986e-06, + "loss": 0.8107, + "step": 3025 + }, + { + "epoch": 0.58, + "learning_rate": 7.83213791864694e-06, + "loss": 0.8551, + "step": 3026 + }, + { + "epoch": 0.58, + "learning_rate": 7.826052047909042e-06, + "loss": 0.8143, + "step": 3027 + }, + { + "epoch": 0.58, + "learning_rate": 7.819967022177853e-06, + "loss": 0.7619, + "step": 3028 + }, + { + "epoch": 0.58, + "learning_rate": 7.8138828438186e-06, + "loss": 0.8136, + "step": 3029 + }, + { + "epoch": 0.58, + "learning_rate": 7.807799515196188e-06, + "loss": 0.8521, + "step": 3030 + }, + { + "epoch": 0.58, + "learning_rate": 7.801717038675192e-06, + "loss": 0.802, + "step": 3031 + }, + { + "epoch": 0.58, + "learning_rate": 7.795635416619843e-06, + "loss": 0.8392, + "step": 3032 + }, + { + "epoch": 0.58, + "learning_rate": 7.789554651394047e-06, + "loss": 0.783, + "step": 3033 + }, + { + "epoch": 0.58, + "learning_rate": 7.783474745361384e-06, + "loss": 0.7438, + "step": 3034 + }, + { + "epoch": 0.58, + "learning_rate": 7.777395700885092e-06, + "loss": 0.838, + "step": 3035 + }, + { + "epoch": 0.58, + "learning_rate": 7.771317520328077e-06, + "loss": 0.84, + "step": 3036 + }, + { + "epoch": 0.58, + "learning_rate": 7.76524020605291e-06, + "loss": 0.8544, + "step": 3037 + }, + { + "epoch": 0.58, + "learning_rate": 7.75916376042182e-06, + "loss": 0.6826, + "step": 3038 + }, + { + "epoch": 0.58, + "learning_rate": 7.753088185796712e-06, + "loss": 0.7726, + "step": 3039 + }, + { + "epoch": 0.59, + "learning_rate": 7.747013484539127e-06, + "loss": 0.8081, + "step": 3040 + }, + { + "epoch": 0.59, + "learning_rate": 7.740939659010292e-06, + "loss": 0.8141, + "step": 3041 + }, + { + "epoch": 0.59, + "learning_rate": 7.734866711571083e-06, + "loss": 0.8129, + "step": 3042 + }, + { + "epoch": 0.59, + "learning_rate": 7.728794644582035e-06, + "loss": 1.3064, + "step": 3043 + }, + { + "epoch": 0.59, + "learning_rate": 7.722723460403342e-06, + "loss": 0.8188, + "step": 3044 + }, + { + "epoch": 0.59, + "learning_rate": 7.716653161394852e-06, + "loss": 0.8181, + "step": 3045 + }, + { + "epoch": 0.59, + "learning_rate": 7.710583749916072e-06, + "loss": 0.7714, + "step": 3046 + }, + { + "epoch": 0.59, + "learning_rate": 7.704515228326169e-06, + "loss": 0.8172, + "step": 3047 + }, + { + "epoch": 0.59, + "learning_rate": 7.698447598983946e-06, + "loss": 0.7997, + "step": 3048 + }, + { + "epoch": 0.59, + "learning_rate": 7.692380864247882e-06, + "loss": 0.8065, + "step": 3049 + }, + { + "epoch": 0.59, + "learning_rate": 7.68631502647609e-06, + "loss": 0.8489, + "step": 3050 + }, + { + "epoch": 0.59, + "learning_rate": 7.680250088026345e-06, + "loss": 0.7746, + "step": 3051 + }, + { + "epoch": 0.59, + "learning_rate": 7.674186051256071e-06, + "loss": 0.7638, + "step": 3052 + }, + { + "epoch": 0.59, + "learning_rate": 7.668122918522342e-06, + "loss": 0.8087, + "step": 3053 + }, + { + "epoch": 0.59, + "learning_rate": 7.662060692181873e-06, + "loss": 1.2318, + "step": 3054 + }, + { + "epoch": 0.59, + "learning_rate": 7.655999374591034e-06, + "loss": 0.7751, + "step": 3055 + }, + { + "epoch": 0.59, + "learning_rate": 7.649938968105846e-06, + "loss": 0.8091, + "step": 3056 + }, + { + "epoch": 0.59, + "learning_rate": 7.643879475081961e-06, + "loss": 1.3881, + "step": 3057 + }, + { + "epoch": 0.59, + "learning_rate": 7.637820897874688e-06, + "loss": 0.8194, + "step": 3058 + }, + { + "epoch": 0.59, + "learning_rate": 7.631763238838979e-06, + "loss": 0.8175, + "step": 3059 + }, + { + "epoch": 0.59, + "learning_rate": 7.625706500329424e-06, + "loss": 0.7796, + "step": 3060 + }, + { + "epoch": 0.59, + "learning_rate": 7.6196506847002586e-06, + "loss": 0.8404, + "step": 3061 + }, + { + "epoch": 0.59, + "learning_rate": 7.61359579430536e-06, + "loss": 0.8196, + "step": 3062 + }, + { + "epoch": 0.59, + "learning_rate": 7.607541831498247e-06, + "loss": 0.7912, + "step": 3063 + }, + { + "epoch": 0.59, + "learning_rate": 7.601488798632075e-06, + "loss": 0.8063, + "step": 3064 + }, + { + "epoch": 0.59, + "learning_rate": 7.595436698059637e-06, + "loss": 0.7772, + "step": 3065 + }, + { + "epoch": 0.59, + "learning_rate": 7.589385532133365e-06, + "loss": 0.7315, + "step": 3066 + }, + { + "epoch": 0.59, + "learning_rate": 7.583335303205328e-06, + "loss": 0.7602, + "step": 3067 + }, + { + "epoch": 0.59, + "learning_rate": 7.5772860136272315e-06, + "loss": 0.7564, + "step": 3068 + }, + { + "epoch": 0.59, + "learning_rate": 7.57123766575042e-06, + "loss": 0.8303, + "step": 3069 + }, + { + "epoch": 0.59, + "learning_rate": 7.565190261925859e-06, + "loss": 0.7911, + "step": 3070 + }, + { + "epoch": 0.59, + "learning_rate": 7.55914380450416e-06, + "loss": 0.8327, + "step": 3071 + }, + { + "epoch": 0.59, + "learning_rate": 7.553098295835562e-06, + "loss": 0.7519, + "step": 3072 + }, + { + "epoch": 0.59, + "learning_rate": 7.547053738269937e-06, + "loss": 0.8126, + "step": 3073 + }, + { + "epoch": 0.59, + "learning_rate": 7.54101013415678e-06, + "loss": 1.3388, + "step": 3074 + }, + { + "epoch": 0.59, + "learning_rate": 7.534967485845225e-06, + "loss": 0.8474, + "step": 3075 + }, + { + "epoch": 0.59, + "learning_rate": 7.528925795684028e-06, + "loss": 0.7867, + "step": 3076 + }, + { + "epoch": 0.59, + "learning_rate": 7.522885066021575e-06, + "loss": 0.8267, + "step": 3077 + }, + { + "epoch": 0.59, + "learning_rate": 7.51684529920588e-06, + "loss": 0.752, + "step": 3078 + }, + { + "epoch": 0.59, + "learning_rate": 7.510806497584582e-06, + "loss": 0.7891, + "step": 3079 + }, + { + "epoch": 0.59, + "learning_rate": 7.504768663504942e-06, + "loss": 0.798, + "step": 3080 + }, + { + "epoch": 0.59, + "learning_rate": 7.498731799313852e-06, + "loss": 0.7997, + "step": 3081 + }, + { + "epoch": 0.59, + "learning_rate": 7.492695907357812e-06, + "loss": 0.8045, + "step": 3082 + }, + { + "epoch": 0.59, + "learning_rate": 7.486660989982962e-06, + "loss": 0.8025, + "step": 3083 + }, + { + "epoch": 0.59, + "learning_rate": 7.480627049535054e-06, + "loss": 0.8083, + "step": 3084 + }, + { + "epoch": 0.59, + "learning_rate": 7.474594088359459e-06, + "loss": 0.843, + "step": 3085 + }, + { + "epoch": 0.59, + "learning_rate": 7.468562108801176e-06, + "loss": 0.8193, + "step": 3086 + }, + { + "epoch": 0.59, + "learning_rate": 7.46253111320481e-06, + "loss": 0.7638, + "step": 3087 + }, + { + "epoch": 0.59, + "learning_rate": 7.456501103914593e-06, + "loss": 0.8147, + "step": 3088 + }, + { + "epoch": 0.59, + "learning_rate": 7.450472083274369e-06, + "loss": 1.2536, + "step": 3089 + }, + { + "epoch": 0.59, + "learning_rate": 7.4444440536276055e-06, + "loss": 0.7941, + "step": 3090 + }, + { + "epoch": 0.59, + "learning_rate": 7.438417017317369e-06, + "loss": 0.7885, + "step": 3091 + }, + { + "epoch": 0.6, + "learning_rate": 7.4323909766863555e-06, + "loss": 1.2565, + "step": 3092 + }, + { + "epoch": 0.6, + "learning_rate": 7.426365934076865e-06, + "loss": 0.8464, + "step": 3093 + }, + { + "epoch": 0.6, + "learning_rate": 7.4203418918308135e-06, + "loss": 0.8042, + "step": 3094 + }, + { + "epoch": 0.6, + "learning_rate": 7.414318852289728e-06, + "loss": 0.7503, + "step": 3095 + }, + { + "epoch": 0.6, + "learning_rate": 7.408296817794747e-06, + "loss": 0.8062, + "step": 3096 + }, + { + "epoch": 0.6, + "learning_rate": 7.402275790686611e-06, + "loss": 0.7742, + "step": 3097 + }, + { + "epoch": 0.6, + "learning_rate": 7.396255773305681e-06, + "loss": 0.8116, + "step": 3098 + }, + { + "epoch": 0.6, + "learning_rate": 7.390236767991912e-06, + "loss": 0.744, + "step": 3099 + }, + { + "epoch": 0.6, + "learning_rate": 7.384218777084875e-06, + "loss": 0.682, + "step": 3100 + }, + { + "epoch": 0.6, + "learning_rate": 7.378201802923743e-06, + "loss": 1.2287, + "step": 3101 + }, + { + "epoch": 0.6, + "learning_rate": 7.372185847847301e-06, + "loss": 0.7931, + "step": 3102 + }, + { + "epoch": 0.6, + "learning_rate": 7.366170914193923e-06, + "loss": 0.7825, + "step": 3103 + }, + { + "epoch": 0.6, + "learning_rate": 7.360157004301599e-06, + "loss": 0.787, + "step": 3104 + }, + { + "epoch": 0.6, + "learning_rate": 7.354144120507918e-06, + "loss": 0.7552, + "step": 3105 + }, + { + "epoch": 0.6, + "learning_rate": 7.34813226515007e-06, + "loss": 0.7599, + "step": 3106 + }, + { + "epoch": 0.6, + "learning_rate": 7.342121440564837e-06, + "loss": 0.8039, + "step": 3107 + }, + { + "epoch": 0.6, + "learning_rate": 7.336111649088615e-06, + "loss": 0.7387, + "step": 3108 + }, + { + "epoch": 0.6, + "learning_rate": 7.330102893057387e-06, + "loss": 0.8352, + "step": 3109 + }, + { + "epoch": 0.6, + "learning_rate": 7.324095174806738e-06, + "loss": 0.8128, + "step": 3110 + }, + { + "epoch": 0.6, + "learning_rate": 7.318088496671851e-06, + "loss": 0.7426, + "step": 3111 + }, + { + "epoch": 0.6, + "learning_rate": 7.312082860987501e-06, + "loss": 0.7676, + "step": 3112 + }, + { + "epoch": 0.6, + "learning_rate": 7.306078270088061e-06, + "loss": 0.7718, + "step": 3113 + }, + { + "epoch": 0.6, + "learning_rate": 7.300074726307496e-06, + "loss": 0.7564, + "step": 3114 + }, + { + "epoch": 0.6, + "learning_rate": 7.2940722319793665e-06, + "loss": 0.7869, + "step": 3115 + }, + { + "epoch": 0.6, + "learning_rate": 7.288070789436819e-06, + "loss": 0.7903, + "step": 3116 + }, + { + "epoch": 0.6, + "learning_rate": 7.282070401012595e-06, + "loss": 0.7586, + "step": 3117 + }, + { + "epoch": 0.6, + "learning_rate": 7.276071069039033e-06, + "loss": 0.7463, + "step": 3118 + }, + { + "epoch": 0.6, + "learning_rate": 7.270072795848047e-06, + "loss": 0.813, + "step": 3119 + }, + { + "epoch": 0.6, + "learning_rate": 7.264075583771149e-06, + "loss": 0.7592, + "step": 3120 + }, + { + "epoch": 0.6, + "learning_rate": 7.258079435139439e-06, + "loss": 0.8319, + "step": 3121 + }, + { + "epoch": 0.6, + "learning_rate": 7.2520843522836014e-06, + "loss": 0.779, + "step": 3122 + }, + { + "epoch": 0.6, + "learning_rate": 7.246090337533904e-06, + "loss": 0.8433, + "step": 3123 + }, + { + "epoch": 0.6, + "learning_rate": 7.240097393220201e-06, + "loss": 0.8026, + "step": 3124 + }, + { + "epoch": 0.6, + "learning_rate": 7.23410552167193e-06, + "loss": 0.7965, + "step": 3125 + }, + { + "epoch": 0.6, + "learning_rate": 7.228114725218114e-06, + "loss": 0.7686, + "step": 3126 + }, + { + "epoch": 0.6, + "learning_rate": 7.222125006187357e-06, + "loss": 0.8242, + "step": 3127 + }, + { + "epoch": 0.6, + "learning_rate": 7.216136366907844e-06, + "loss": 0.7833, + "step": 3128 + }, + { + "epoch": 0.6, + "learning_rate": 7.21014880970734e-06, + "loss": 0.8288, + "step": 3129 + }, + { + "epoch": 0.6, + "learning_rate": 7.204162336913187e-06, + "loss": 1.1994, + "step": 3130 + }, + { + "epoch": 0.6, + "learning_rate": 7.198176950852314e-06, + "loss": 0.8218, + "step": 3131 + }, + { + "epoch": 0.6, + "learning_rate": 7.192192653851219e-06, + "loss": 0.7499, + "step": 3132 + }, + { + "epoch": 0.6, + "learning_rate": 7.186209448235974e-06, + "loss": 0.7875, + "step": 3133 + }, + { + "epoch": 0.6, + "learning_rate": 7.18022733633224e-06, + "loss": 0.7659, + "step": 3134 + }, + { + "epoch": 0.6, + "learning_rate": 7.1742463204652415e-06, + "loss": 0.7979, + "step": 3135 + }, + { + "epoch": 0.6, + "learning_rate": 7.1682664029597785e-06, + "loss": 0.7493, + "step": 3136 + }, + { + "epoch": 0.6, + "learning_rate": 7.1622875861402285e-06, + "loss": 0.7917, + "step": 3137 + }, + { + "epoch": 0.6, + "learning_rate": 7.156309872330538e-06, + "loss": 0.8401, + "step": 3138 + }, + { + "epoch": 0.6, + "learning_rate": 7.1503332638542285e-06, + "loss": 0.796, + "step": 3139 + }, + { + "epoch": 0.6, + "learning_rate": 7.144357763034386e-06, + "loss": 0.797, + "step": 3140 + }, + { + "epoch": 0.6, + "learning_rate": 7.13838337219367e-06, + "loss": 0.8209, + "step": 3141 + }, + { + "epoch": 0.6, + "learning_rate": 7.132410093654304e-06, + "loss": 0.8351, + "step": 3142 + }, + { + "epoch": 0.61, + "learning_rate": 7.126437929738085e-06, + "loss": 0.7836, + "step": 3143 + }, + { + "epoch": 0.61, + "learning_rate": 7.120466882766374e-06, + "loss": 0.7656, + "step": 3144 + }, + { + "epoch": 0.61, + "learning_rate": 7.1144969550601e-06, + "loss": 0.7588, + "step": 3145 + }, + { + "epoch": 0.61, + "learning_rate": 7.1085281489397515e-06, + "loss": 1.2276, + "step": 3146 + }, + { + "epoch": 0.61, + "learning_rate": 7.102560466725387e-06, + "loss": 0.8374, + "step": 3147 + }, + { + "epoch": 0.61, + "learning_rate": 7.096593910736624e-06, + "loss": 0.8092, + "step": 3148 + }, + { + "epoch": 0.61, + "learning_rate": 7.090628483292652e-06, + "loss": 0.7733, + "step": 3149 + }, + { + "epoch": 0.61, + "learning_rate": 7.0846641867122e-06, + "loss": 0.795, + "step": 3150 + }, + { + "epoch": 0.61, + "learning_rate": 7.078701023313582e-06, + "loss": 0.7292, + "step": 3151 + }, + { + "epoch": 0.61, + "learning_rate": 7.072738995414654e-06, + "loss": 0.7212, + "step": 3152 + }, + { + "epoch": 0.61, + "learning_rate": 7.066778105332842e-06, + "loss": 0.7629, + "step": 3153 + }, + { + "epoch": 0.61, + "learning_rate": 7.060818355385124e-06, + "loss": 0.758, + "step": 3154 + }, + { + "epoch": 0.61, + "learning_rate": 7.054859747888037e-06, + "loss": 0.7815, + "step": 3155 + }, + { + "epoch": 0.61, + "learning_rate": 7.0489022851576685e-06, + "loss": 0.7896, + "step": 3156 + }, + { + "epoch": 0.61, + "learning_rate": 7.042945969509673e-06, + "loss": 0.713, + "step": 3157 + }, + { + "epoch": 0.61, + "learning_rate": 7.036990803259245e-06, + "loss": 0.7787, + "step": 3158 + }, + { + "epoch": 0.61, + "learning_rate": 7.0310367887211394e-06, + "loss": 0.7607, + "step": 3159 + }, + { + "epoch": 0.61, + "learning_rate": 7.0250839282096635e-06, + "loss": 0.7696, + "step": 3160 + }, + { + "epoch": 0.61, + "learning_rate": 7.019132224038681e-06, + "loss": 0.7015, + "step": 3161 + }, + { + "epoch": 0.61, + "learning_rate": 7.013181678521593e-06, + "loss": 0.8395, + "step": 3162 + }, + { + "epoch": 0.61, + "learning_rate": 7.0072322939713585e-06, + "loss": 0.7697, + "step": 3163 + }, + { + "epoch": 0.61, + "learning_rate": 7.0012840727004895e-06, + "loss": 0.7864, + "step": 3164 + }, + { + "epoch": 0.61, + "learning_rate": 6.9953370170210374e-06, + "loss": 0.7093, + "step": 3165 + }, + { + "epoch": 0.61, + "learning_rate": 6.989391129244607e-06, + "loss": 0.813, + "step": 3166 + }, + { + "epoch": 0.61, + "learning_rate": 6.983446411682343e-06, + "loss": 0.7543, + "step": 3167 + }, + { + "epoch": 0.61, + "learning_rate": 6.9775028666449365e-06, + "loss": 0.7954, + "step": 3168 + }, + { + "epoch": 0.61, + "learning_rate": 6.971560496442627e-06, + "loss": 0.7716, + "step": 3169 + }, + { + "epoch": 0.61, + "learning_rate": 6.965619303385196e-06, + "loss": 0.8074, + "step": 3170 + }, + { + "epoch": 0.61, + "learning_rate": 6.959679289781968e-06, + "loss": 1.201, + "step": 3171 + }, + { + "epoch": 0.61, + "learning_rate": 6.953740457941803e-06, + "loss": 0.6806, + "step": 3172 + }, + { + "epoch": 0.61, + "learning_rate": 6.9478028101731086e-06, + "loss": 0.8593, + "step": 3173 + }, + { + "epoch": 0.61, + "learning_rate": 6.941866348783835e-06, + "loss": 0.7543, + "step": 3174 + }, + { + "epoch": 0.61, + "learning_rate": 6.9359310760814545e-06, + "loss": 0.806, + "step": 3175 + }, + { + "epoch": 0.61, + "learning_rate": 6.929996994372995e-06, + "loss": 0.8486, + "step": 3176 + }, + { + "epoch": 0.61, + "learning_rate": 6.924064105965018e-06, + "loss": 0.738, + "step": 3177 + }, + { + "epoch": 0.61, + "learning_rate": 6.918132413163614e-06, + "loss": 0.827, + "step": 3178 + }, + { + "epoch": 0.61, + "learning_rate": 6.912201918274415e-06, + "loss": 0.8038, + "step": 3179 + }, + { + "epoch": 0.61, + "learning_rate": 6.906272623602587e-06, + "loss": 0.8206, + "step": 3180 + }, + { + "epoch": 0.61, + "learning_rate": 6.900344531452825e-06, + "loss": 0.7769, + "step": 3181 + }, + { + "epoch": 0.61, + "learning_rate": 6.894417644129368e-06, + "loss": 0.8019, + "step": 3182 + }, + { + "epoch": 0.61, + "learning_rate": 6.888491963935968e-06, + "loss": 0.8207, + "step": 3183 + }, + { + "epoch": 0.61, + "learning_rate": 6.882567493175921e-06, + "loss": 0.7762, + "step": 3184 + }, + { + "epoch": 0.61, + "learning_rate": 6.876644234152051e-06, + "loss": 0.7737, + "step": 3185 + }, + { + "epoch": 0.61, + "learning_rate": 6.8707221891667105e-06, + "loss": 0.8196, + "step": 3186 + }, + { + "epoch": 0.61, + "learning_rate": 6.86480136052178e-06, + "loss": 0.7699, + "step": 3187 + }, + { + "epoch": 0.61, + "learning_rate": 6.8588817505186685e-06, + "loss": 0.7713, + "step": 3188 + }, + { + "epoch": 0.61, + "learning_rate": 6.852963361458305e-06, + "loss": 0.8062, + "step": 3189 + }, + { + "epoch": 0.61, + "learning_rate": 6.847046195641151e-06, + "loss": 0.7726, + "step": 3190 + }, + { + "epoch": 0.61, + "learning_rate": 6.841130255367196e-06, + "loss": 0.8163, + "step": 3191 + }, + { + "epoch": 0.61, + "learning_rate": 6.835215542935938e-06, + "loss": 0.7837, + "step": 3192 + }, + { + "epoch": 0.61, + "learning_rate": 6.82930206064641e-06, + "loss": 1.2956, + "step": 3193 + }, + { + "epoch": 0.61, + "learning_rate": 6.823389810797167e-06, + "loss": 0.7646, + "step": 3194 + }, + { + "epoch": 0.62, + "learning_rate": 6.817478795686279e-06, + "loss": 0.8191, + "step": 3195 + }, + { + "epoch": 0.62, + "learning_rate": 6.811569017611337e-06, + "loss": 0.8378, + "step": 3196 + }, + { + "epoch": 0.62, + "learning_rate": 6.805660478869458e-06, + "loss": 0.7783, + "step": 3197 + }, + { + "epoch": 0.62, + "learning_rate": 6.799753181757271e-06, + "loss": 0.7941, + "step": 3198 + }, + { + "epoch": 0.62, + "learning_rate": 6.793847128570923e-06, + "loss": 0.8533, + "step": 3199 + }, + { + "epoch": 0.62, + "learning_rate": 6.787942321606078e-06, + "loss": 0.7582, + "step": 3200 + }, + { + "epoch": 0.62, + "learning_rate": 6.782038763157915e-06, + "loss": 0.7461, + "step": 3201 + }, + { + "epoch": 0.62, + "learning_rate": 6.776136455521128e-06, + "loss": 0.7666, + "step": 3202 + }, + { + "epoch": 0.62, + "learning_rate": 6.770235400989926e-06, + "loss": 0.7886, + "step": 3203 + }, + { + "epoch": 0.62, + "learning_rate": 6.764335601858034e-06, + "loss": 0.7448, + "step": 3204 + }, + { + "epoch": 0.62, + "learning_rate": 6.758437060418681e-06, + "loss": 0.7178, + "step": 3205 + }, + { + "epoch": 0.62, + "learning_rate": 6.752539778964613e-06, + "loss": 0.8347, + "step": 3206 + }, + { + "epoch": 0.62, + "learning_rate": 6.746643759788083e-06, + "loss": 0.7434, + "step": 3207 + }, + { + "epoch": 0.62, + "learning_rate": 6.740749005180862e-06, + "loss": 0.8373, + "step": 3208 + }, + { + "epoch": 0.62, + "learning_rate": 6.734855517434212e-06, + "loss": 0.8214, + "step": 3209 + }, + { + "epoch": 0.62, + "learning_rate": 6.728963298838921e-06, + "loss": 0.7664, + "step": 3210 + }, + { + "epoch": 0.62, + "learning_rate": 6.72307235168527e-06, + "loss": 0.7887, + "step": 3211 + }, + { + "epoch": 0.62, + "learning_rate": 6.717182678263055e-06, + "loss": 0.8002, + "step": 3212 + }, + { + "epoch": 0.62, + "learning_rate": 6.711294280861573e-06, + "loss": 0.8349, + "step": 3213 + }, + { + "epoch": 0.62, + "learning_rate": 6.705407161769628e-06, + "loss": 0.8555, + "step": 3214 + }, + { + "epoch": 0.62, + "learning_rate": 6.69952132327552e-06, + "loss": 0.764, + "step": 3215 + }, + { + "epoch": 0.62, + "learning_rate": 6.69363676766706e-06, + "loss": 0.7223, + "step": 3216 + }, + { + "epoch": 0.62, + "learning_rate": 6.687753497231552e-06, + "loss": 0.84, + "step": 3217 + }, + { + "epoch": 0.62, + "learning_rate": 6.681871514255807e-06, + "loss": 1.2321, + "step": 3218 + }, + { + "epoch": 0.62, + "learning_rate": 6.675990821026131e-06, + "loss": 0.7783, + "step": 3219 + }, + { + "epoch": 0.62, + "learning_rate": 6.6701114198283355e-06, + "loss": 0.7807, + "step": 3220 + }, + { + "epoch": 0.62, + "learning_rate": 6.664233312947721e-06, + "loss": 0.7744, + "step": 3221 + }, + { + "epoch": 0.62, + "learning_rate": 6.658356502669091e-06, + "loss": 0.8368, + "step": 3222 + }, + { + "epoch": 0.62, + "learning_rate": 6.652480991276742e-06, + "loss": 0.8511, + "step": 3223 + }, + { + "epoch": 0.62, + "learning_rate": 6.6466067810544676e-06, + "loss": 0.7922, + "step": 3224 + }, + { + "epoch": 0.62, + "learning_rate": 6.64073387428556e-06, + "loss": 0.8364, + "step": 3225 + }, + { + "epoch": 0.62, + "learning_rate": 6.6348622732527915e-06, + "loss": 0.7785, + "step": 3226 + }, + { + "epoch": 0.62, + "learning_rate": 6.628991980238435e-06, + "loss": 0.7841, + "step": 3227 + }, + { + "epoch": 0.62, + "learning_rate": 6.623122997524257e-06, + "loss": 0.7941, + "step": 3228 + }, + { + "epoch": 0.62, + "learning_rate": 6.617255327391514e-06, + "loss": 1.3055, + "step": 3229 + }, + { + "epoch": 0.62, + "learning_rate": 6.611388972120949e-06, + "loss": 0.7787, + "step": 3230 + }, + { + "epoch": 0.62, + "learning_rate": 6.6055239339928e-06, + "loss": 0.8154, + "step": 3231 + }, + { + "epoch": 0.62, + "learning_rate": 6.599660215286783e-06, + "loss": 0.7486, + "step": 3232 + }, + { + "epoch": 0.62, + "learning_rate": 6.593797818282113e-06, + "loss": 0.7708, + "step": 3233 + }, + { + "epoch": 0.62, + "learning_rate": 6.5879367452574775e-06, + "loss": 0.7423, + "step": 3234 + }, + { + "epoch": 0.62, + "learning_rate": 6.582076998491061e-06, + "loss": 0.7577, + "step": 3235 + }, + { + "epoch": 0.62, + "learning_rate": 6.5762185802605294e-06, + "loss": 0.8116, + "step": 3236 + }, + { + "epoch": 0.62, + "learning_rate": 6.5703614928430336e-06, + "loss": 0.7769, + "step": 3237 + }, + { + "epoch": 0.62, + "learning_rate": 6.564505738515199e-06, + "loss": 0.7769, + "step": 3238 + }, + { + "epoch": 0.62, + "learning_rate": 6.558651319553142e-06, + "loss": 0.7812, + "step": 3239 + }, + { + "epoch": 0.62, + "learning_rate": 6.552798238232457e-06, + "loss": 0.7855, + "step": 3240 + }, + { + "epoch": 0.62, + "learning_rate": 6.54694649682822e-06, + "loss": 0.7678, + "step": 3241 + }, + { + "epoch": 0.62, + "learning_rate": 6.541096097614983e-06, + "loss": 1.2276, + "step": 3242 + }, + { + "epoch": 0.62, + "learning_rate": 6.535247042866777e-06, + "loss": 0.7492, + "step": 3243 + }, + { + "epoch": 0.62, + "learning_rate": 6.529399334857109e-06, + "loss": 0.7894, + "step": 3244 + }, + { + "epoch": 0.62, + "learning_rate": 6.523552975858967e-06, + "loss": 0.7713, + "step": 3245 + }, + { + "epoch": 0.62, + "learning_rate": 6.517707968144812e-06, + "loss": 0.7926, + "step": 3246 + }, + { + "epoch": 0.63, + "learning_rate": 6.511864313986582e-06, + "loss": 1.2593, + "step": 3247 + }, + { + "epoch": 0.63, + "learning_rate": 6.506022015655684e-06, + "loss": 0.7911, + "step": 3248 + }, + { + "epoch": 0.63, + "learning_rate": 6.500181075423001e-06, + "loss": 0.7839, + "step": 3249 + }, + { + "epoch": 0.63, + "learning_rate": 6.494341495558894e-06, + "loss": 0.7949, + "step": 3250 + }, + { + "epoch": 0.63, + "learning_rate": 6.4885032783331804e-06, + "loss": 0.7981, + "step": 3251 + }, + { + "epoch": 0.63, + "learning_rate": 6.482666426015161e-06, + "loss": 0.8281, + "step": 3252 + }, + { + "epoch": 0.63, + "learning_rate": 6.476830940873603e-06, + "loss": 0.817, + "step": 3253 + }, + { + "epoch": 0.63, + "learning_rate": 6.470996825176739e-06, + "loss": 0.7674, + "step": 3254 + }, + { + "epoch": 0.63, + "learning_rate": 6.46516408119227e-06, + "loss": 0.8722, + "step": 3255 + }, + { + "epoch": 0.63, + "learning_rate": 6.4593327111873695e-06, + "loss": 0.7702, + "step": 3256 + }, + { + "epoch": 0.63, + "learning_rate": 6.45350271742867e-06, + "loss": 0.8265, + "step": 3257 + }, + { + "epoch": 0.63, + "learning_rate": 6.447674102182275e-06, + "loss": 0.7932, + "step": 3258 + }, + { + "epoch": 0.63, + "learning_rate": 6.441846867713744e-06, + "loss": 0.8147, + "step": 3259 + }, + { + "epoch": 0.63, + "learning_rate": 6.4360210162881054e-06, + "loss": 0.8068, + "step": 3260 + }, + { + "epoch": 0.63, + "learning_rate": 6.430196550169849e-06, + "loss": 0.8043, + "step": 3261 + }, + { + "epoch": 0.63, + "learning_rate": 6.42437347162293e-06, + "loss": 0.7847, + "step": 3262 + }, + { + "epoch": 0.63, + "learning_rate": 6.41855178291076e-06, + "loss": 0.7224, + "step": 3263 + }, + { + "epoch": 0.63, + "learning_rate": 6.412731486296206e-06, + "loss": 0.7411, + "step": 3264 + }, + { + "epoch": 0.63, + "learning_rate": 6.406912584041605e-06, + "loss": 0.8164, + "step": 3265 + }, + { + "epoch": 0.63, + "learning_rate": 6.401095078408741e-06, + "loss": 0.8539, + "step": 3266 + }, + { + "epoch": 0.63, + "learning_rate": 6.395278971658867e-06, + "loss": 0.7896, + "step": 3267 + }, + { + "epoch": 0.63, + "learning_rate": 6.389464266052679e-06, + "loss": 0.7946, + "step": 3268 + }, + { + "epoch": 0.63, + "learning_rate": 6.383650963850336e-06, + "loss": 0.8126, + "step": 3269 + }, + { + "epoch": 0.63, + "learning_rate": 6.377839067311449e-06, + "loss": 0.8013, + "step": 3270 + }, + { + "epoch": 0.63, + "learning_rate": 6.3720285786950865e-06, + "loss": 0.801, + "step": 3271 + }, + { + "epoch": 0.63, + "learning_rate": 6.366219500259766e-06, + "loss": 0.7789, + "step": 3272 + }, + { + "epoch": 0.63, + "learning_rate": 6.360411834263458e-06, + "loss": 0.7212, + "step": 3273 + }, + { + "epoch": 0.63, + "learning_rate": 6.354605582963587e-06, + "loss": 0.8059, + "step": 3274 + }, + { + "epoch": 0.63, + "learning_rate": 6.348800748617022e-06, + "loss": 0.8392, + "step": 3275 + }, + { + "epoch": 0.63, + "learning_rate": 6.342997333480081e-06, + "loss": 0.7685, + "step": 3276 + }, + { + "epoch": 0.63, + "learning_rate": 6.337195339808535e-06, + "loss": 0.7439, + "step": 3277 + }, + { + "epoch": 0.63, + "learning_rate": 6.3313947698576006e-06, + "loss": 0.7743, + "step": 3278 + }, + { + "epoch": 0.63, + "learning_rate": 6.3255956258819415e-06, + "loss": 0.7796, + "step": 3279 + }, + { + "epoch": 0.63, + "learning_rate": 6.3197979101356696e-06, + "loss": 0.7503, + "step": 3280 + }, + { + "epoch": 0.63, + "learning_rate": 6.314001624872335e-06, + "loss": 0.8123, + "step": 3281 + }, + { + "epoch": 0.63, + "learning_rate": 6.308206772344935e-06, + "loss": 0.8353, + "step": 3282 + }, + { + "epoch": 0.63, + "learning_rate": 6.302413354805912e-06, + "loss": 0.844, + "step": 3283 + }, + { + "epoch": 0.63, + "learning_rate": 6.296621374507154e-06, + "loss": 0.7907, + "step": 3284 + }, + { + "epoch": 0.63, + "learning_rate": 6.290830833699975e-06, + "loss": 0.81, + "step": 3285 + }, + { + "epoch": 0.63, + "learning_rate": 6.285041734635149e-06, + "loss": 1.1693, + "step": 3286 + }, + { + "epoch": 0.63, + "learning_rate": 6.279254079562873e-06, + "loss": 0.8037, + "step": 3287 + }, + { + "epoch": 0.63, + "learning_rate": 6.273467870732797e-06, + "loss": 0.7661, + "step": 3288 + }, + { + "epoch": 0.63, + "learning_rate": 6.267683110393996e-06, + "loss": 0.7325, + "step": 3289 + }, + { + "epoch": 0.63, + "learning_rate": 6.261899800794996e-06, + "loss": 0.7569, + "step": 3290 + }, + { + "epoch": 0.63, + "learning_rate": 6.2561179441837435e-06, + "loss": 0.8028, + "step": 3291 + }, + { + "epoch": 0.63, + "learning_rate": 6.250337542807636e-06, + "loss": 0.7797, + "step": 3292 + }, + { + "epoch": 0.63, + "learning_rate": 6.244558598913487e-06, + "loss": 0.7832, + "step": 3293 + }, + { + "epoch": 0.63, + "learning_rate": 6.238781114747561e-06, + "loss": 0.7869, + "step": 3294 + }, + { + "epoch": 0.63, + "learning_rate": 6.233005092555544e-06, + "loss": 0.849, + "step": 3295 + }, + { + "epoch": 0.63, + "learning_rate": 6.2272305345825624e-06, + "loss": 0.7782, + "step": 3296 + }, + { + "epoch": 0.63, + "learning_rate": 6.221457443073164e-06, + "loss": 0.7506, + "step": 3297 + }, + { + "epoch": 0.63, + "learning_rate": 6.215685820271332e-06, + "loss": 1.1714, + "step": 3298 + }, + { + "epoch": 0.64, + "learning_rate": 6.20991566842048e-06, + "loss": 0.8022, + "step": 3299 + }, + { + "epoch": 0.64, + "learning_rate": 6.204146989763449e-06, + "loss": 0.8058, + "step": 3300 + }, + { + "epoch": 0.64, + "learning_rate": 6.198379786542503e-06, + "loss": 0.7978, + "step": 3301 + }, + { + "epoch": 0.64, + "learning_rate": 6.192614060999337e-06, + "loss": 0.8206, + "step": 3302 + }, + { + "epoch": 0.64, + "learning_rate": 6.1868498153750685e-06, + "loss": 0.7693, + "step": 3303 + }, + { + "epoch": 0.64, + "learning_rate": 6.181087051910242e-06, + "loss": 0.7712, + "step": 3304 + }, + { + "epoch": 0.64, + "learning_rate": 6.175325772844828e-06, + "loss": 0.7441, + "step": 3305 + }, + { + "epoch": 0.64, + "learning_rate": 6.1695659804182175e-06, + "loss": 0.8179, + "step": 3306 + }, + { + "epoch": 0.64, + "learning_rate": 6.16380767686922e-06, + "loss": 0.7219, + "step": 3307 + }, + { + "epoch": 0.64, + "learning_rate": 6.158050864436073e-06, + "loss": 0.8213, + "step": 3308 + }, + { + "epoch": 0.64, + "learning_rate": 6.152295545356434e-06, + "loss": 0.7851, + "step": 3309 + }, + { + "epoch": 0.64, + "learning_rate": 6.14654172186737e-06, + "loss": 1.2747, + "step": 3310 + }, + { + "epoch": 0.64, + "learning_rate": 6.1407893962053765e-06, + "loss": 0.748, + "step": 3311 + }, + { + "epoch": 0.64, + "learning_rate": 6.1350385706063685e-06, + "loss": 0.8223, + "step": 3312 + }, + { + "epoch": 0.64, + "learning_rate": 6.12928924730567e-06, + "loss": 0.7863, + "step": 3313 + }, + { + "epoch": 0.64, + "learning_rate": 6.123541428538025e-06, + "loss": 0.7289, + "step": 3314 + }, + { + "epoch": 0.64, + "learning_rate": 6.117795116537593e-06, + "loss": 0.7651, + "step": 3315 + }, + { + "epoch": 0.64, + "learning_rate": 6.11205031353795e-06, + "loss": 0.798, + "step": 3316 + }, + { + "epoch": 0.64, + "learning_rate": 6.10630702177208e-06, + "loss": 0.7876, + "step": 3317 + }, + { + "epoch": 0.64, + "learning_rate": 6.1005652434723825e-06, + "loss": 0.8331, + "step": 3318 + }, + { + "epoch": 0.64, + "learning_rate": 6.094824980870669e-06, + "loss": 0.7982, + "step": 3319 + }, + { + "epoch": 0.64, + "learning_rate": 6.089086236198159e-06, + "loss": 0.7532, + "step": 3320 + }, + { + "epoch": 0.64, + "learning_rate": 6.083349011685487e-06, + "loss": 0.7917, + "step": 3321 + }, + { + "epoch": 0.64, + "learning_rate": 6.077613309562697e-06, + "loss": 0.8158, + "step": 3322 + }, + { + "epoch": 0.64, + "learning_rate": 6.0718791320592325e-06, + "loss": 0.7868, + "step": 3323 + }, + { + "epoch": 0.64, + "learning_rate": 6.066146481403953e-06, + "loss": 0.7998, + "step": 3324 + }, + { + "epoch": 0.64, + "learning_rate": 6.060415359825123e-06, + "loss": 0.8345, + "step": 3325 + }, + { + "epoch": 0.64, + "learning_rate": 6.0546857695504115e-06, + "loss": 0.7784, + "step": 3326 + }, + { + "epoch": 0.64, + "learning_rate": 6.048957712806888e-06, + "loss": 0.7713, + "step": 3327 + }, + { + "epoch": 0.64, + "learning_rate": 6.043231191821033e-06, + "loss": 0.7978, + "step": 3328 + }, + { + "epoch": 0.64, + "learning_rate": 6.037506208818728e-06, + "loss": 0.7693, + "step": 3329 + }, + { + "epoch": 0.64, + "learning_rate": 6.031782766025253e-06, + "loss": 0.8119, + "step": 3330 + }, + { + "epoch": 0.64, + "learning_rate": 6.026060865665293e-06, + "loss": 0.7267, + "step": 3331 + }, + { + "epoch": 0.64, + "learning_rate": 6.020340509962935e-06, + "loss": 0.7751, + "step": 3332 + }, + { + "epoch": 0.64, + "learning_rate": 6.014621701141663e-06, + "loss": 0.7099, + "step": 3333 + }, + { + "epoch": 0.64, + "learning_rate": 6.008904441424359e-06, + "loss": 0.837, + "step": 3334 + }, + { + "epoch": 0.64, + "learning_rate": 6.003188733033303e-06, + "loss": 0.7929, + "step": 3335 + }, + { + "epoch": 0.64, + "learning_rate": 5.997474578190171e-06, + "loss": 0.8319, + "step": 3336 + }, + { + "epoch": 0.64, + "learning_rate": 5.9917619791160395e-06, + "loss": 0.714, + "step": 3337 + }, + { + "epoch": 0.64, + "learning_rate": 5.986050938031378e-06, + "loss": 0.798, + "step": 3338 + }, + { + "epoch": 0.64, + "learning_rate": 5.980341457156051e-06, + "loss": 0.7709, + "step": 3339 + }, + { + "epoch": 0.64, + "learning_rate": 5.974633538709311e-06, + "loss": 0.7851, + "step": 3340 + }, + { + "epoch": 0.64, + "learning_rate": 5.968927184909812e-06, + "loss": 0.8099, + "step": 3341 + }, + { + "epoch": 0.64, + "learning_rate": 5.963222397975595e-06, + "loss": 0.8006, + "step": 3342 + }, + { + "epoch": 0.64, + "learning_rate": 5.957519180124097e-06, + "loss": 0.8174, + "step": 3343 + }, + { + "epoch": 0.64, + "learning_rate": 5.951817533572133e-06, + "loss": 0.7964, + "step": 3344 + }, + { + "epoch": 0.64, + "learning_rate": 5.9461174605359185e-06, + "loss": 1.2692, + "step": 3345 + }, + { + "epoch": 0.64, + "learning_rate": 5.940418963231051e-06, + "loss": 0.8142, + "step": 3346 + }, + { + "epoch": 0.64, + "learning_rate": 5.934722043872524e-06, + "loss": 0.7955, + "step": 3347 + }, + { + "epoch": 0.64, + "learning_rate": 5.929026704674707e-06, + "loss": 0.7889, + "step": 3348 + }, + { + "epoch": 0.64, + "learning_rate": 5.923332947851365e-06, + "loss": 0.7832, + "step": 3349 + }, + { + "epoch": 0.64, + "learning_rate": 5.917640775615641e-06, + "loss": 0.7532, + "step": 3350 + }, + { + "epoch": 0.65, + "learning_rate": 5.911950190180067e-06, + "loss": 0.7575, + "step": 3351 + }, + { + "epoch": 0.65, + "learning_rate": 5.9062611937565485e-06, + "loss": 0.761, + "step": 3352 + }, + { + "epoch": 0.65, + "learning_rate": 5.900573788556384e-06, + "loss": 0.8281, + "step": 3353 + }, + { + "epoch": 0.65, + "learning_rate": 5.894887976790251e-06, + "loss": 0.7861, + "step": 3354 + }, + { + "epoch": 0.65, + "learning_rate": 5.8892037606682094e-06, + "loss": 0.8481, + "step": 3355 + }, + { + "epoch": 0.65, + "learning_rate": 5.883521142399691e-06, + "loss": 0.796, + "step": 3356 + }, + { + "epoch": 0.65, + "learning_rate": 5.877840124193513e-06, + "loss": 0.7548, + "step": 3357 + }, + { + "epoch": 0.65, + "learning_rate": 5.87216070825787e-06, + "loss": 0.8459, + "step": 3358 + }, + { + "epoch": 0.65, + "learning_rate": 5.866482896800336e-06, + "loss": 0.8163, + "step": 3359 + }, + { + "epoch": 0.65, + "learning_rate": 5.860806692027854e-06, + "loss": 0.777, + "step": 3360 + }, + { + "epoch": 0.65, + "learning_rate": 5.85513209614675e-06, + "loss": 0.7938, + "step": 3361 + }, + { + "epoch": 0.65, + "learning_rate": 5.8494591113627165e-06, + "loss": 0.7921, + "step": 3362 + }, + { + "epoch": 0.65, + "learning_rate": 5.843787739880827e-06, + "loss": 1.3007, + "step": 3363 + }, + { + "epoch": 0.65, + "learning_rate": 5.8381179839055305e-06, + "loss": 0.7872, + "step": 3364 + }, + { + "epoch": 0.65, + "learning_rate": 5.8324498456406344e-06, + "loss": 0.7864, + "step": 3365 + }, + { + "epoch": 0.65, + "learning_rate": 5.826783327289336e-06, + "loss": 0.7826, + "step": 3366 + }, + { + "epoch": 0.65, + "learning_rate": 5.8211184310541835e-06, + "loss": 0.8082, + "step": 3367 + }, + { + "epoch": 0.65, + "learning_rate": 5.815455159137118e-06, + "loss": 0.7421, + "step": 3368 + }, + { + "epoch": 0.65, + "learning_rate": 5.809793513739421e-06, + "loss": 1.2202, + "step": 3369 + }, + { + "epoch": 0.65, + "learning_rate": 5.804133497061759e-06, + "loss": 0.8003, + "step": 3370 + }, + { + "epoch": 0.65, + "learning_rate": 5.798475111304168e-06, + "loss": 0.7949, + "step": 3371 + }, + { + "epoch": 0.65, + "learning_rate": 5.7928183586660395e-06, + "loss": 0.8154, + "step": 3372 + }, + { + "epoch": 0.65, + "learning_rate": 5.787163241346141e-06, + "loss": 0.7718, + "step": 3373 + }, + { + "epoch": 0.65, + "learning_rate": 5.781509761542594e-06, + "loss": 0.789, + "step": 3374 + }, + { + "epoch": 0.65, + "learning_rate": 5.7758579214528875e-06, + "loss": 0.7981, + "step": 3375 + }, + { + "epoch": 0.65, + "learning_rate": 5.770207723273881e-06, + "loss": 0.7888, + "step": 3376 + }, + { + "epoch": 0.65, + "learning_rate": 5.764559169201783e-06, + "loss": 0.7438, + "step": 3377 + }, + { + "epoch": 0.65, + "learning_rate": 5.75891226143217e-06, + "loss": 1.1786, + "step": 3378 + }, + { + "epoch": 0.65, + "learning_rate": 5.753267002159972e-06, + "loss": 0.7542, + "step": 3379 + }, + { + "epoch": 0.65, + "learning_rate": 5.747623393579494e-06, + "loss": 0.7929, + "step": 3380 + }, + { + "epoch": 0.65, + "learning_rate": 5.741981437884381e-06, + "loss": 0.7156, + "step": 3381 + }, + { + "epoch": 0.65, + "learning_rate": 5.736341137267642e-06, + "loss": 0.7691, + "step": 3382 + }, + { + "epoch": 0.65, + "learning_rate": 5.730702493921653e-06, + "loss": 0.7917, + "step": 3383 + }, + { + "epoch": 0.65, + "learning_rate": 5.72506551003813e-06, + "loss": 0.8229, + "step": 3384 + }, + { + "epoch": 0.65, + "learning_rate": 5.719430187808153e-06, + "loss": 1.1332, + "step": 3385 + }, + { + "epoch": 0.65, + "learning_rate": 5.7137965294221534e-06, + "loss": 0.7686, + "step": 3386 + }, + { + "epoch": 0.65, + "learning_rate": 5.708164537069911e-06, + "loss": 0.7924, + "step": 3387 + }, + { + "epoch": 0.65, + "learning_rate": 5.702534212940575e-06, + "loss": 0.7499, + "step": 3388 + }, + { + "epoch": 0.65, + "learning_rate": 5.696905559222623e-06, + "loss": 0.7555, + "step": 3389 + }, + { + "epoch": 0.65, + "learning_rate": 5.691278578103905e-06, + "loss": 1.2469, + "step": 3390 + }, + { + "epoch": 0.65, + "learning_rate": 5.685653271771605e-06, + "loss": 0.7656, + "step": 3391 + }, + { + "epoch": 0.65, + "learning_rate": 5.680029642412259e-06, + "loss": 0.7681, + "step": 3392 + }, + { + "epoch": 0.65, + "learning_rate": 5.6744076922117665e-06, + "loss": 0.7544, + "step": 3393 + }, + { + "epoch": 0.65, + "learning_rate": 5.668787423355344e-06, + "loss": 0.7927, + "step": 3394 + }, + { + "epoch": 0.65, + "learning_rate": 5.663168838027587e-06, + "loss": 0.8166, + "step": 3395 + }, + { + "epoch": 0.65, + "learning_rate": 5.657551938412416e-06, + "loss": 0.7901, + "step": 3396 + }, + { + "epoch": 0.65, + "learning_rate": 5.651936726693099e-06, + "loss": 0.7953, + "step": 3397 + }, + { + "epoch": 0.65, + "learning_rate": 5.6463232050522575e-06, + "loss": 0.7999, + "step": 3398 + }, + { + "epoch": 0.65, + "learning_rate": 5.640711375671843e-06, + "loss": 0.7804, + "step": 3399 + }, + { + "epoch": 0.65, + "learning_rate": 5.635101240733164e-06, + "loss": 0.8252, + "step": 3400 + }, + { + "epoch": 0.65, + "learning_rate": 5.629492802416858e-06, + "loss": 0.773, + "step": 3401 + }, + { + "epoch": 0.65, + "learning_rate": 5.623886062902906e-06, + "loss": 1.252, + "step": 3402 + }, + { + "epoch": 0.66, + "learning_rate": 5.618281024370632e-06, + "loss": 0.7961, + "step": 3403 + }, + { + "epoch": 0.66, + "learning_rate": 5.612677688998691e-06, + "loss": 0.8008, + "step": 3404 + }, + { + "epoch": 0.66, + "learning_rate": 5.607076058965092e-06, + "loss": 0.7885, + "step": 3405 + }, + { + "epoch": 0.66, + "learning_rate": 5.601476136447165e-06, + "loss": 0.8022, + "step": 3406 + }, + { + "epoch": 0.66, + "learning_rate": 5.595877923621579e-06, + "loss": 0.8144, + "step": 3407 + }, + { + "epoch": 0.66, + "learning_rate": 5.5902814226643485e-06, + "loss": 0.7569, + "step": 3408 + }, + { + "epoch": 0.66, + "learning_rate": 5.584686635750809e-06, + "loss": 0.7945, + "step": 3409 + }, + { + "epoch": 0.66, + "learning_rate": 5.579093565055649e-06, + "loss": 0.8089, + "step": 3410 + }, + { + "epoch": 0.66, + "learning_rate": 5.573502212752861e-06, + "loss": 0.7674, + "step": 3411 + }, + { + "epoch": 0.66, + "learning_rate": 5.567912581015797e-06, + "loss": 0.8384, + "step": 3412 + }, + { + "epoch": 0.66, + "learning_rate": 5.562324672017125e-06, + "loss": 0.7565, + "step": 3413 + }, + { + "epoch": 0.66, + "learning_rate": 5.556738487928845e-06, + "loss": 0.778, + "step": 3414 + }, + { + "epoch": 0.66, + "learning_rate": 5.551154030922297e-06, + "loss": 0.7405, + "step": 3415 + }, + { + "epoch": 0.66, + "learning_rate": 5.5455713031681366e-06, + "loss": 0.7746, + "step": 3416 + }, + { + "epoch": 0.66, + "learning_rate": 5.539990306836349e-06, + "loss": 0.8146, + "step": 3417 + }, + { + "epoch": 0.66, + "learning_rate": 5.534411044096259e-06, + "loss": 0.7815, + "step": 3418 + }, + { + "epoch": 0.66, + "learning_rate": 5.528833517116504e-06, + "loss": 0.8176, + "step": 3419 + }, + { + "epoch": 0.66, + "learning_rate": 5.5232577280650505e-06, + "loss": 0.8247, + "step": 3420 + }, + { + "epoch": 0.66, + "learning_rate": 5.5176836791091846e-06, + "loss": 0.7207, + "step": 3421 + }, + { + "epoch": 0.66, + "learning_rate": 5.512111372415533e-06, + "loss": 0.8296, + "step": 3422 + }, + { + "epoch": 0.66, + "learning_rate": 5.5065408101500275e-06, + "loss": 0.7691, + "step": 3423 + }, + { + "epoch": 0.66, + "learning_rate": 5.500971994477924e-06, + "loss": 0.7595, + "step": 3424 + }, + { + "epoch": 0.66, + "learning_rate": 5.495404927563812e-06, + "loss": 0.8123, + "step": 3425 + }, + { + "epoch": 0.66, + "learning_rate": 5.489839611571586e-06, + "loss": 0.7915, + "step": 3426 + }, + { + "epoch": 0.66, + "learning_rate": 5.484276048664477e-06, + "loss": 1.198, + "step": 3427 + }, + { + "epoch": 0.66, + "learning_rate": 5.4787142410050086e-06, + "loss": 0.8015, + "step": 3428 + }, + { + "epoch": 0.66, + "learning_rate": 5.47315419075505e-06, + "loss": 0.7762, + "step": 3429 + }, + { + "epoch": 0.66, + "learning_rate": 5.467595900075773e-06, + "loss": 0.7752, + "step": 3430 + }, + { + "epoch": 0.66, + "learning_rate": 5.462039371127661e-06, + "loss": 1.2129, + "step": 3431 + }, + { + "epoch": 0.66, + "learning_rate": 5.456484606070529e-06, + "loss": 0.7934, + "step": 3432 + }, + { + "epoch": 0.66, + "learning_rate": 5.4509316070634925e-06, + "loss": 1.2001, + "step": 3433 + }, + { + "epoch": 0.66, + "learning_rate": 5.445380376264979e-06, + "loss": 0.7522, + "step": 3434 + }, + { + "epoch": 0.66, + "learning_rate": 5.439830915832745e-06, + "loss": 0.7491, + "step": 3435 + }, + { + "epoch": 0.66, + "learning_rate": 5.434283227923842e-06, + "loss": 0.754, + "step": 3436 + }, + { + "epoch": 0.66, + "learning_rate": 5.428737314694639e-06, + "loss": 0.7394, + "step": 3437 + }, + { + "epoch": 0.66, + "learning_rate": 5.423193178300813e-06, + "loss": 1.1703, + "step": 3438 + }, + { + "epoch": 0.66, + "learning_rate": 5.4176508208973574e-06, + "loss": 0.7737, + "step": 3439 + }, + { + "epoch": 0.66, + "learning_rate": 5.4121102446385685e-06, + "loss": 0.7759, + "step": 3440 + }, + { + "epoch": 0.66, + "learning_rate": 5.406571451678045e-06, + "loss": 0.8139, + "step": 3441 + }, + { + "epoch": 0.66, + "learning_rate": 5.401034444168705e-06, + "loss": 0.8469, + "step": 3442 + }, + { + "epoch": 0.66, + "learning_rate": 5.395499224262763e-06, + "loss": 0.7667, + "step": 3443 + }, + { + "epoch": 0.66, + "learning_rate": 5.3899657941117426e-06, + "loss": 0.8383, + "step": 3444 + }, + { + "epoch": 0.66, + "learning_rate": 5.384434155866467e-06, + "loss": 0.7785, + "step": 3445 + }, + { + "epoch": 0.66, + "learning_rate": 5.378904311677067e-06, + "loss": 0.7699, + "step": 3446 + }, + { + "epoch": 0.66, + "learning_rate": 5.373376263692982e-06, + "loss": 0.7526, + "step": 3447 + }, + { + "epoch": 0.66, + "learning_rate": 5.367850014062937e-06, + "loss": 0.7674, + "step": 3448 + }, + { + "epoch": 0.66, + "learning_rate": 5.362325564934978e-06, + "loss": 0.8091, + "step": 3449 + }, + { + "epoch": 0.66, + "learning_rate": 5.356802918456437e-06, + "loss": 0.8256, + "step": 3450 + }, + { + "epoch": 0.66, + "learning_rate": 5.351282076773945e-06, + "loss": 0.7566, + "step": 3451 + }, + { + "epoch": 0.66, + "learning_rate": 5.34576304203344e-06, + "loss": 0.7329, + "step": 3452 + }, + { + "epoch": 0.66, + "learning_rate": 5.340245816380156e-06, + "loss": 0.7439, + "step": 3453 + }, + { + "epoch": 0.66, + "learning_rate": 5.334730401958616e-06, + "loss": 0.7612, + "step": 3454 + }, + { + "epoch": 0.67, + "learning_rate": 5.329216800912646e-06, + "loss": 0.8292, + "step": 3455 + }, + { + "epoch": 0.67, + "learning_rate": 5.323705015385362e-06, + "loss": 0.7332, + "step": 3456 + }, + { + "epoch": 0.67, + "learning_rate": 5.318195047519184e-06, + "loss": 0.7816, + "step": 3457 + }, + { + "epoch": 0.67, + "learning_rate": 5.312686899455813e-06, + "loss": 0.7606, + "step": 3458 + }, + { + "epoch": 0.67, + "learning_rate": 5.3071805733362555e-06, + "loss": 0.7752, + "step": 3459 + }, + { + "epoch": 0.67, + "learning_rate": 5.3016760713008e-06, + "loss": 0.8364, + "step": 3460 + }, + { + "epoch": 0.67, + "learning_rate": 5.296173395489028e-06, + "loss": 0.7654, + "step": 3461 + }, + { + "epoch": 0.67, + "learning_rate": 5.290672548039812e-06, + "loss": 0.8211, + "step": 3462 + }, + { + "epoch": 0.67, + "learning_rate": 5.285173531091312e-06, + "loss": 0.7538, + "step": 3463 + }, + { + "epoch": 0.67, + "learning_rate": 5.279676346780984e-06, + "loss": 0.7916, + "step": 3464 + }, + { + "epoch": 0.67, + "learning_rate": 5.274180997245564e-06, + "loss": 0.7772, + "step": 3465 + }, + { + "epoch": 0.67, + "learning_rate": 5.268687484621073e-06, + "loss": 0.8265, + "step": 3466 + }, + { + "epoch": 0.67, + "learning_rate": 5.263195811042829e-06, + "loss": 1.2034, + "step": 3467 + }, + { + "epoch": 0.67, + "learning_rate": 5.2577059786454196e-06, + "loss": 0.8587, + "step": 3468 + }, + { + "epoch": 0.67, + "learning_rate": 5.25221798956274e-06, + "loss": 0.852, + "step": 3469 + }, + { + "epoch": 0.67, + "learning_rate": 5.246731845927937e-06, + "loss": 0.825, + "step": 3470 + }, + { + "epoch": 0.67, + "learning_rate": 5.2412475498734675e-06, + "loss": 0.7756, + "step": 3471 + }, + { + "epoch": 0.67, + "learning_rate": 5.235765103531058e-06, + "loss": 0.7683, + "step": 3472 + }, + { + "epoch": 0.67, + "learning_rate": 5.230284509031716e-06, + "loss": 0.8596, + "step": 3473 + }, + { + "epoch": 0.67, + "learning_rate": 5.224805768505734e-06, + "loss": 0.7327, + "step": 3474 + }, + { + "epoch": 0.67, + "learning_rate": 5.2193288840826775e-06, + "loss": 0.8407, + "step": 3475 + }, + { + "epoch": 0.67, + "learning_rate": 5.2138538578914e-06, + "loss": 0.7562, + "step": 3476 + }, + { + "epoch": 0.67, + "learning_rate": 5.208380692060023e-06, + "loss": 0.7735, + "step": 3477 + }, + { + "epoch": 0.67, + "learning_rate": 5.202909388715951e-06, + "loss": 0.7524, + "step": 3478 + }, + { + "epoch": 0.67, + "learning_rate": 5.1974399499858595e-06, + "loss": 0.7437, + "step": 3479 + }, + { + "epoch": 0.67, + "learning_rate": 5.1919723779957e-06, + "loss": 0.7753, + "step": 3480 + }, + { + "epoch": 0.67, + "learning_rate": 5.186506674870708e-06, + "loss": 0.7868, + "step": 3481 + }, + { + "epoch": 0.67, + "learning_rate": 5.181042842735381e-06, + "loss": 0.7918, + "step": 3482 + }, + { + "epoch": 0.67, + "learning_rate": 5.175580883713489e-06, + "loss": 0.718, + "step": 3483 + }, + { + "epoch": 0.67, + "learning_rate": 5.170120799928087e-06, + "loss": 0.7346, + "step": 3484 + }, + { + "epoch": 0.67, + "learning_rate": 5.164662593501484e-06, + "loss": 0.8014, + "step": 3485 + }, + { + "epoch": 0.67, + "learning_rate": 5.159206266555278e-06, + "loss": 0.785, + "step": 3486 + }, + { + "epoch": 0.67, + "learning_rate": 5.1537518212103125e-06, + "loss": 0.8027, + "step": 3487 + }, + { + "epoch": 0.67, + "learning_rate": 5.148299259586723e-06, + "loss": 0.7592, + "step": 3488 + }, + { + "epoch": 0.67, + "learning_rate": 5.142848583803901e-06, + "loss": 0.7568, + "step": 3489 + }, + { + "epoch": 0.67, + "learning_rate": 5.137399795980502e-06, + "loss": 0.7384, + "step": 3490 + }, + { + "epoch": 0.67, + "learning_rate": 5.1319528982344614e-06, + "loss": 0.7632, + "step": 3491 + }, + { + "epoch": 0.67, + "learning_rate": 5.126507892682966e-06, + "loss": 0.7111, + "step": 3492 + }, + { + "epoch": 0.67, + "learning_rate": 5.121064781442469e-06, + "loss": 0.8269, + "step": 3493 + }, + { + "epoch": 0.67, + "learning_rate": 5.115623566628698e-06, + "loss": 0.7632, + "step": 3494 + }, + { + "epoch": 0.67, + "learning_rate": 5.110184250356633e-06, + "loss": 0.8052, + "step": 3495 + }, + { + "epoch": 0.67, + "learning_rate": 5.104746834740518e-06, + "loss": 0.7971, + "step": 3496 + }, + { + "epoch": 0.67, + "learning_rate": 5.099311321893856e-06, + "loss": 0.7642, + "step": 3497 + }, + { + "epoch": 0.67, + "learning_rate": 5.09387771392942e-06, + "loss": 0.7829, + "step": 3498 + }, + { + "epoch": 0.67, + "learning_rate": 5.088446012959236e-06, + "loss": 1.2205, + "step": 3499 + }, + { + "epoch": 0.67, + "learning_rate": 5.083016221094582e-06, + "loss": 0.7645, + "step": 3500 + }, + { + "epoch": 0.67, + "learning_rate": 5.077588340446009e-06, + "loss": 0.7319, + "step": 3501 + }, + { + "epoch": 0.67, + "learning_rate": 5.0721623731233145e-06, + "loss": 0.8052, + "step": 3502 + }, + { + "epoch": 0.67, + "learning_rate": 5.066738321235554e-06, + "loss": 0.7852, + "step": 3503 + }, + { + "epoch": 0.67, + "learning_rate": 5.061316186891039e-06, + "loss": 0.7405, + "step": 3504 + }, + { + "epoch": 0.67, + "learning_rate": 5.055895972197334e-06, + "loss": 0.8299, + "step": 3505 + }, + { + "epoch": 0.67, + "learning_rate": 5.050477679261264e-06, + "loss": 0.7705, + "step": 3506 + }, + { + "epoch": 0.68, + "learning_rate": 5.045061310188897e-06, + "loss": 0.7861, + "step": 3507 + }, + { + "epoch": 0.68, + "learning_rate": 5.0396468670855654e-06, + "loss": 0.7343, + "step": 3508 + }, + { + "epoch": 0.68, + "learning_rate": 5.034234352055843e-06, + "loss": 0.8264, + "step": 3509 + }, + { + "epoch": 0.68, + "learning_rate": 5.0288237672035526e-06, + "loss": 0.8062, + "step": 3510 + }, + { + "epoch": 0.68, + "learning_rate": 5.02341511463178e-06, + "loss": 0.7801, + "step": 3511 + }, + { + "epoch": 0.68, + "learning_rate": 5.018008396442847e-06, + "loss": 0.8022, + "step": 3512 + }, + { + "epoch": 0.68, + "learning_rate": 5.012603614738328e-06, + "loss": 0.773, + "step": 3513 + }, + { + "epoch": 0.68, + "learning_rate": 5.007200771619045e-06, + "loss": 0.7735, + "step": 3514 + }, + { + "epoch": 0.68, + "learning_rate": 5.001799869185061e-06, + "loss": 0.7994, + "step": 3515 + }, + { + "epoch": 0.68, + "learning_rate": 4.996400909535698e-06, + "loss": 0.784, + "step": 3516 + }, + { + "epoch": 0.68, + "learning_rate": 4.991003894769508e-06, + "loss": 0.7299, + "step": 3517 + }, + { + "epoch": 0.68, + "learning_rate": 4.9856088269842995e-06, + "loss": 0.7633, + "step": 3518 + }, + { + "epoch": 0.68, + "learning_rate": 4.980215708277116e-06, + "loss": 0.7783, + "step": 3519 + }, + { + "epoch": 0.68, + "learning_rate": 4.974824540744245e-06, + "loss": 0.7461, + "step": 3520 + }, + { + "epoch": 0.68, + "learning_rate": 4.969435326481217e-06, + "loss": 0.7304, + "step": 3521 + }, + { + "epoch": 0.68, + "learning_rate": 4.964048067582797e-06, + "loss": 0.7875, + "step": 3522 + }, + { + "epoch": 0.68, + "learning_rate": 4.958662766143006e-06, + "loss": 0.7967, + "step": 3523 + }, + { + "epoch": 0.68, + "learning_rate": 4.953279424255083e-06, + "loss": 1.1518, + "step": 3524 + }, + { + "epoch": 0.68, + "learning_rate": 4.947898044011525e-06, + "loss": 1.1688, + "step": 3525 + }, + { + "epoch": 0.68, + "learning_rate": 4.942518627504054e-06, + "loss": 0.6801, + "step": 3526 + }, + { + "epoch": 0.68, + "learning_rate": 4.9371411768236286e-06, + "loss": 0.7548, + "step": 3527 + }, + { + "epoch": 0.68, + "learning_rate": 4.931765694060457e-06, + "loss": 0.7243, + "step": 3528 + }, + { + "epoch": 0.68, + "learning_rate": 4.92639218130396e-06, + "loss": 0.7922, + "step": 3529 + }, + { + "epoch": 0.68, + "learning_rate": 4.921020640642812e-06, + "loss": 0.7405, + "step": 3530 + }, + { + "epoch": 0.68, + "learning_rate": 4.9156510741649135e-06, + "loss": 0.8494, + "step": 3531 + }, + { + "epoch": 0.68, + "learning_rate": 4.9102834839573934e-06, + "loss": 0.7862, + "step": 3532 + }, + { + "epoch": 0.68, + "learning_rate": 4.904917872106625e-06, + "loss": 1.3618, + "step": 3533 + }, + { + "epoch": 0.68, + "learning_rate": 4.899554240698195e-06, + "loss": 0.7915, + "step": 3534 + }, + { + "epoch": 0.68, + "learning_rate": 4.894192591816942e-06, + "loss": 0.7906, + "step": 3535 + }, + { + "epoch": 0.68, + "learning_rate": 4.888832927546914e-06, + "loss": 0.7345, + "step": 3536 + }, + { + "epoch": 0.68, + "learning_rate": 4.883475249971396e-06, + "loss": 0.7532, + "step": 3537 + }, + { + "epoch": 0.68, + "learning_rate": 4.878119561172904e-06, + "loss": 0.8169, + "step": 3538 + }, + { + "epoch": 0.68, + "learning_rate": 4.87276586323317e-06, + "loss": 1.1021, + "step": 3539 + }, + { + "epoch": 0.68, + "learning_rate": 4.867414158233167e-06, + "loss": 0.7322, + "step": 3540 + }, + { + "epoch": 0.68, + "learning_rate": 4.862064448253084e-06, + "loss": 0.7942, + "step": 3541 + }, + { + "epoch": 0.68, + "learning_rate": 4.856716735372332e-06, + "loss": 0.8073, + "step": 3542 + }, + { + "epoch": 0.68, + "learning_rate": 4.851371021669556e-06, + "loss": 0.7717, + "step": 3543 + }, + { + "epoch": 0.68, + "learning_rate": 4.846027309222614e-06, + "loss": 0.8102, + "step": 3544 + }, + { + "epoch": 0.68, + "learning_rate": 4.840685600108598e-06, + "loss": 0.7298, + "step": 3545 + }, + { + "epoch": 0.68, + "learning_rate": 4.835345896403801e-06, + "loss": 0.7568, + "step": 3546 + }, + { + "epoch": 0.68, + "learning_rate": 4.8300082001837575e-06, + "loss": 0.7444, + "step": 3547 + }, + { + "epoch": 0.68, + "learning_rate": 4.824672513523212e-06, + "loss": 0.8101, + "step": 3548 + }, + { + "epoch": 0.68, + "learning_rate": 4.8193388384961235e-06, + "loss": 0.7763, + "step": 3549 + }, + { + "epoch": 0.68, + "learning_rate": 4.814007177175683e-06, + "loss": 0.769, + "step": 3550 + }, + { + "epoch": 0.68, + "learning_rate": 4.808677531634288e-06, + "loss": 0.7484, + "step": 3551 + }, + { + "epoch": 0.68, + "learning_rate": 4.803349903943549e-06, + "loss": 0.7823, + "step": 3552 + }, + { + "epoch": 0.68, + "learning_rate": 4.798024296174306e-06, + "loss": 0.7498, + "step": 3553 + }, + { + "epoch": 0.68, + "learning_rate": 4.792700710396603e-06, + "loss": 0.7134, + "step": 3554 + }, + { + "epoch": 0.68, + "learning_rate": 4.787379148679699e-06, + "loss": 0.7813, + "step": 3555 + }, + { + "epoch": 0.68, + "learning_rate": 4.7820596130920685e-06, + "loss": 0.7607, + "step": 3556 + }, + { + "epoch": 0.68, + "learning_rate": 4.776742105701402e-06, + "loss": 0.7761, + "step": 3557 + }, + { + "epoch": 0.68, + "learning_rate": 4.771426628574594e-06, + "loss": 0.7654, + "step": 3558 + }, + { + "epoch": 0.69, + "learning_rate": 4.766113183777753e-06, + "loss": 1.2137, + "step": 3559 + }, + { + "epoch": 0.69, + "learning_rate": 4.7608017733762035e-06, + "loss": 0.7815, + "step": 3560 + }, + { + "epoch": 0.69, + "learning_rate": 4.7554923994344674e-06, + "loss": 0.7753, + "step": 3561 + }, + { + "epoch": 0.69, + "learning_rate": 4.750185064016292e-06, + "loss": 0.8187, + "step": 3562 + }, + { + "epoch": 0.69, + "learning_rate": 4.744879769184611e-06, + "loss": 0.7833, + "step": 3563 + }, + { + "epoch": 0.69, + "learning_rate": 4.739576517001575e-06, + "loss": 0.7443, + "step": 3564 + }, + { + "epoch": 0.69, + "learning_rate": 4.73427530952855e-06, + "loss": 0.7718, + "step": 3565 + }, + { + "epoch": 0.69, + "learning_rate": 4.728976148826091e-06, + "loss": 0.8064, + "step": 3566 + }, + { + "epoch": 0.69, + "learning_rate": 4.723679036953972e-06, + "loss": 0.7667, + "step": 3567 + }, + { + "epoch": 0.69, + "learning_rate": 4.71838397597116e-06, + "loss": 0.7994, + "step": 3568 + }, + { + "epoch": 0.69, + "learning_rate": 4.713090967935825e-06, + "loss": 1.2296, + "step": 3569 + }, + { + "epoch": 0.69, + "learning_rate": 4.707800014905351e-06, + "loss": 0.7746, + "step": 3570 + }, + { + "epoch": 0.69, + "learning_rate": 4.702511118936308e-06, + "loss": 0.7535, + "step": 3571 + }, + { + "epoch": 0.69, + "learning_rate": 4.6972242820844774e-06, + "loss": 0.7706, + "step": 3572 + }, + { + "epoch": 0.69, + "learning_rate": 4.691939506404828e-06, + "loss": 0.7406, + "step": 3573 + }, + { + "epoch": 0.69, + "learning_rate": 4.686656793951545e-06, + "loss": 0.7923, + "step": 3574 + }, + { + "epoch": 0.69, + "learning_rate": 4.681376146777999e-06, + "loss": 0.7851, + "step": 3575 + }, + { + "epoch": 0.69, + "learning_rate": 4.676097566936756e-06, + "loss": 0.7777, + "step": 3576 + }, + { + "epoch": 0.69, + "learning_rate": 4.670821056479592e-06, + "loss": 0.7658, + "step": 3577 + }, + { + "epoch": 0.69, + "learning_rate": 4.6655466174574635e-06, + "loss": 0.7867, + "step": 3578 + }, + { + "epoch": 0.69, + "learning_rate": 4.6602742519205325e-06, + "loss": 0.7735, + "step": 3579 + }, + { + "epoch": 0.69, + "learning_rate": 4.655003961918146e-06, + "loss": 0.7854, + "step": 3580 + }, + { + "epoch": 0.69, + "learning_rate": 4.64973574949885e-06, + "loss": 0.8049, + "step": 3581 + }, + { + "epoch": 0.69, + "learning_rate": 4.644469616710386e-06, + "loss": 0.7743, + "step": 3582 + }, + { + "epoch": 0.69, + "learning_rate": 4.639205565599678e-06, + "loss": 1.1762, + "step": 3583 + }, + { + "epoch": 0.69, + "learning_rate": 4.633943598212852e-06, + "loss": 0.7495, + "step": 3584 + }, + { + "epoch": 0.69, + "learning_rate": 4.628683716595216e-06, + "loss": 0.7587, + "step": 3585 + }, + { + "epoch": 0.69, + "learning_rate": 4.623425922791264e-06, + "loss": 0.8094, + "step": 3586 + }, + { + "epoch": 0.69, + "learning_rate": 4.618170218844692e-06, + "loss": 0.7301, + "step": 3587 + }, + { + "epoch": 0.69, + "learning_rate": 4.612916606798371e-06, + "loss": 0.7073, + "step": 3588 + }, + { + "epoch": 0.69, + "learning_rate": 4.607665088694365e-06, + "loss": 0.7758, + "step": 3589 + }, + { + "epoch": 0.69, + "learning_rate": 4.602415666573922e-06, + "loss": 0.7894, + "step": 3590 + }, + { + "epoch": 0.69, + "learning_rate": 4.597168342477472e-06, + "loss": 0.7814, + "step": 3591 + }, + { + "epoch": 0.69, + "learning_rate": 4.59192311844464e-06, + "loss": 0.8355, + "step": 3592 + }, + { + "epoch": 0.69, + "learning_rate": 4.5866799965142205e-06, + "loss": 0.8139, + "step": 3593 + }, + { + "epoch": 0.69, + "learning_rate": 4.581438978724208e-06, + "loss": 0.7556, + "step": 3594 + }, + { + "epoch": 0.69, + "learning_rate": 4.576200067111763e-06, + "loss": 0.7997, + "step": 3595 + }, + { + "epoch": 0.69, + "learning_rate": 4.570963263713236e-06, + "loss": 0.8076, + "step": 3596 + }, + { + "epoch": 0.69, + "learning_rate": 4.565728570564156e-06, + "loss": 1.3216, + "step": 3597 + }, + { + "epoch": 0.69, + "learning_rate": 4.560495989699226e-06, + "loss": 0.7301, + "step": 3598 + }, + { + "epoch": 0.69, + "learning_rate": 4.555265523152344e-06, + "loss": 0.7988, + "step": 3599 + }, + { + "epoch": 0.69, + "learning_rate": 4.55003717295657e-06, + "loss": 0.8051, + "step": 3600 + }, + { + "epoch": 0.69, + "learning_rate": 4.544810941144143e-06, + "loss": 0.723, + "step": 3601 + }, + { + "epoch": 0.69, + "learning_rate": 4.539586829746492e-06, + "loss": 0.7805, + "step": 3602 + }, + { + "epoch": 0.69, + "learning_rate": 4.534364840794204e-06, + "loss": 0.7817, + "step": 3603 + }, + { + "epoch": 0.69, + "learning_rate": 4.5291449763170614e-06, + "loss": 0.7671, + "step": 3604 + }, + { + "epoch": 0.69, + "learning_rate": 4.5239272383439936e-06, + "loss": 0.7664, + "step": 3605 + }, + { + "epoch": 0.69, + "learning_rate": 4.518711628903131e-06, + "loss": 0.8106, + "step": 3606 + }, + { + "epoch": 0.69, + "learning_rate": 4.51349815002176e-06, + "loss": 0.7789, + "step": 3607 + }, + { + "epoch": 0.69, + "learning_rate": 4.50828680372634e-06, + "loss": 0.7439, + "step": 3608 + }, + { + "epoch": 0.69, + "learning_rate": 4.503077592042512e-06, + "loss": 0.8354, + "step": 3609 + }, + { + "epoch": 0.69, + "learning_rate": 4.497870516995073e-06, + "loss": 0.7589, + "step": 3610 + }, + { + "epoch": 0.7, + "learning_rate": 4.492665580608005e-06, + "loss": 0.7646, + "step": 3611 + }, + { + "epoch": 0.7, + "learning_rate": 4.4874627849044435e-06, + "loss": 1.1448, + "step": 3612 + }, + { + "epoch": 0.7, + "learning_rate": 4.482262131906702e-06, + "loss": 0.8069, + "step": 3613 + }, + { + "epoch": 0.7, + "learning_rate": 4.477063623636258e-06, + "loss": 0.7554, + "step": 3614 + }, + { + "epoch": 0.7, + "learning_rate": 4.471867262113749e-06, + "loss": 0.7882, + "step": 3615 + }, + { + "epoch": 0.7, + "learning_rate": 4.466673049358993e-06, + "loss": 0.8075, + "step": 3616 + }, + { + "epoch": 0.7, + "learning_rate": 4.46148098739096e-06, + "loss": 0.6988, + "step": 3617 + }, + { + "epoch": 0.7, + "learning_rate": 4.456291078227787e-06, + "loss": 0.7794, + "step": 3618 + }, + { + "epoch": 0.7, + "learning_rate": 4.451103323886778e-06, + "loss": 1.2143, + "step": 3619 + }, + { + "epoch": 0.7, + "learning_rate": 4.445917726384395e-06, + "loss": 0.7502, + "step": 3620 + }, + { + "epoch": 0.7, + "learning_rate": 4.440734287736268e-06, + "loss": 0.7789, + "step": 3621 + }, + { + "epoch": 0.7, + "learning_rate": 4.435553009957174e-06, + "loss": 0.8071, + "step": 3622 + }, + { + "epoch": 0.7, + "learning_rate": 4.4303738950610675e-06, + "loss": 0.7945, + "step": 3623 + }, + { + "epoch": 0.7, + "learning_rate": 4.425196945061052e-06, + "loss": 0.7286, + "step": 3624 + }, + { + "epoch": 0.7, + "learning_rate": 4.420022161969386e-06, + "loss": 0.7643, + "step": 3625 + }, + { + "epoch": 0.7, + "learning_rate": 4.414849547797501e-06, + "loss": 1.1842, + "step": 3626 + }, + { + "epoch": 0.7, + "learning_rate": 4.40967910455597e-06, + "loss": 0.755, + "step": 3627 + }, + { + "epoch": 0.7, + "learning_rate": 4.404510834254526e-06, + "loss": 0.7559, + "step": 3628 + }, + { + "epoch": 0.7, + "learning_rate": 4.399344738902066e-06, + "loss": 0.7498, + "step": 3629 + }, + { + "epoch": 0.7, + "learning_rate": 4.39418082050663e-06, + "loss": 0.7952, + "step": 3630 + }, + { + "epoch": 0.7, + "learning_rate": 4.38901908107542e-06, + "loss": 0.7815, + "step": 3631 + }, + { + "epoch": 0.7, + "learning_rate": 4.383859522614781e-06, + "loss": 0.8042, + "step": 3632 + }, + { + "epoch": 0.7, + "learning_rate": 4.378702147130226e-06, + "loss": 0.8159, + "step": 3633 + }, + { + "epoch": 0.7, + "learning_rate": 4.3735469566264065e-06, + "loss": 0.7689, + "step": 3634 + }, + { + "epoch": 0.7, + "learning_rate": 4.368393953107125e-06, + "loss": 0.7759, + "step": 3635 + }, + { + "epoch": 0.7, + "learning_rate": 4.363243138575345e-06, + "loss": 0.7637, + "step": 3636 + }, + { + "epoch": 0.7, + "learning_rate": 4.3580945150331685e-06, + "loss": 0.8008, + "step": 3637 + }, + { + "epoch": 0.7, + "learning_rate": 4.35294808448185e-06, + "loss": 0.8099, + "step": 3638 + }, + { + "epoch": 0.7, + "learning_rate": 4.347803848921789e-06, + "loss": 0.7553, + "step": 3639 + }, + { + "epoch": 0.7, + "learning_rate": 4.342661810352531e-06, + "loss": 0.82, + "step": 3640 + }, + { + "epoch": 0.7, + "learning_rate": 4.337521970772778e-06, + "loss": 1.2579, + "step": 3641 + }, + { + "epoch": 0.7, + "learning_rate": 4.332384332180362e-06, + "loss": 0.7633, + "step": 3642 + }, + { + "epoch": 0.7, + "learning_rate": 4.327248896572272e-06, + "loss": 0.7949, + "step": 3643 + }, + { + "epoch": 0.7, + "learning_rate": 4.322115665944634e-06, + "loss": 0.7602, + "step": 3644 + }, + { + "epoch": 0.7, + "learning_rate": 4.3169846422927154e-06, + "loss": 0.8052, + "step": 3645 + }, + { + "epoch": 0.7, + "learning_rate": 4.3118558276109345e-06, + "loss": 0.794, + "step": 3646 + }, + { + "epoch": 0.7, + "learning_rate": 4.3067292238928435e-06, + "loss": 0.7818, + "step": 3647 + }, + { + "epoch": 0.7, + "learning_rate": 4.301604833131136e-06, + "loss": 0.807, + "step": 3648 + }, + { + "epoch": 0.7, + "learning_rate": 4.296482657317646e-06, + "loss": 0.8045, + "step": 3649 + }, + { + "epoch": 0.7, + "learning_rate": 4.291362698443344e-06, + "loss": 0.7658, + "step": 3650 + }, + { + "epoch": 0.7, + "learning_rate": 4.28624495849835e-06, + "loss": 0.8008, + "step": 3651 + }, + { + "epoch": 0.7, + "learning_rate": 4.281129439471906e-06, + "loss": 0.7214, + "step": 3652 + }, + { + "epoch": 0.7, + "learning_rate": 4.276016143352404e-06, + "loss": 0.8214, + "step": 3653 + }, + { + "epoch": 0.7, + "learning_rate": 4.270905072127362e-06, + "loss": 0.8076, + "step": 3654 + }, + { + "epoch": 0.7, + "learning_rate": 4.265796227783441e-06, + "loss": 0.8055, + "step": 3655 + }, + { + "epoch": 0.7, + "learning_rate": 4.2606896123064274e-06, + "loss": 0.7083, + "step": 3656 + }, + { + "epoch": 0.7, + "learning_rate": 4.255585227681247e-06, + "loss": 0.8015, + "step": 3657 + }, + { + "epoch": 0.7, + "learning_rate": 4.2504830758919646e-06, + "loss": 1.2403, + "step": 3658 + }, + { + "epoch": 0.7, + "learning_rate": 4.245383158921764e-06, + "loss": 0.7738, + "step": 3659 + }, + { + "epoch": 0.7, + "learning_rate": 4.2402854787529665e-06, + "loss": 0.7779, + "step": 3660 + }, + { + "epoch": 0.7, + "learning_rate": 4.235190037367031e-06, + "loss": 0.7597, + "step": 3661 + }, + { + "epoch": 0.7, + "learning_rate": 4.2300968367445304e-06, + "loss": 0.8004, + "step": 3662 + }, + { + "epoch": 0.71, + "learning_rate": 4.225005878865185e-06, + "loss": 0.7702, + "step": 3663 + }, + { + "epoch": 0.71, + "learning_rate": 4.219917165707829e-06, + "loss": 0.7906, + "step": 3664 + }, + { + "epoch": 0.71, + "learning_rate": 4.214830699250431e-06, + "loss": 0.7192, + "step": 3665 + }, + { + "epoch": 0.71, + "learning_rate": 4.209746481470081e-06, + "loss": 0.786, + "step": 3666 + }, + { + "epoch": 0.71, + "learning_rate": 4.204664514342999e-06, + "loss": 0.8222, + "step": 3667 + }, + { + "epoch": 0.71, + "learning_rate": 4.199584799844534e-06, + "loss": 0.7611, + "step": 3668 + }, + { + "epoch": 0.71, + "learning_rate": 4.1945073399491486e-06, + "loss": 0.7692, + "step": 3669 + }, + { + "epoch": 0.71, + "learning_rate": 4.189432136630442e-06, + "loss": 0.8179, + "step": 3670 + }, + { + "epoch": 0.71, + "learning_rate": 4.184359191861128e-06, + "loss": 0.7855, + "step": 3671 + }, + { + "epoch": 0.71, + "learning_rate": 4.179288507613042e-06, + "loss": 0.794, + "step": 3672 + }, + { + "epoch": 0.71, + "learning_rate": 4.1742200858571445e-06, + "loss": 0.7401, + "step": 3673 + }, + { + "epoch": 0.71, + "learning_rate": 4.169153928563511e-06, + "loss": 0.8011, + "step": 3674 + }, + { + "epoch": 0.71, + "learning_rate": 4.164090037701347e-06, + "loss": 0.7393, + "step": 3675 + }, + { + "epoch": 0.71, + "learning_rate": 4.159028415238968e-06, + "loss": 0.7674, + "step": 3676 + }, + { + "epoch": 0.71, + "learning_rate": 4.153969063143808e-06, + "loss": 0.7984, + "step": 3677 + }, + { + "epoch": 0.71, + "learning_rate": 4.148911983382428e-06, + "loss": 0.7981, + "step": 3678 + }, + { + "epoch": 0.71, + "learning_rate": 4.143857177920491e-06, + "loss": 0.8025, + "step": 3679 + }, + { + "epoch": 0.71, + "learning_rate": 4.138804648722795e-06, + "loss": 0.774, + "step": 3680 + }, + { + "epoch": 0.71, + "learning_rate": 4.133754397753229e-06, + "loss": 0.7561, + "step": 3681 + }, + { + "epoch": 0.71, + "learning_rate": 4.128706426974818e-06, + "loss": 0.8003, + "step": 3682 + }, + { + "epoch": 0.71, + "learning_rate": 4.1236607383496904e-06, + "loss": 0.8248, + "step": 3683 + }, + { + "epoch": 0.71, + "learning_rate": 4.118617333839085e-06, + "loss": 0.7808, + "step": 3684 + }, + { + "epoch": 0.71, + "learning_rate": 4.113576215403366e-06, + "loss": 0.7355, + "step": 3685 + }, + { + "epoch": 0.71, + "learning_rate": 4.108537385001995e-06, + "loss": 0.8139, + "step": 3686 + }, + { + "epoch": 0.71, + "learning_rate": 4.103500844593546e-06, + "loss": 0.7873, + "step": 3687 + }, + { + "epoch": 0.71, + "learning_rate": 4.098466596135715e-06, + "loss": 0.7456, + "step": 3688 + }, + { + "epoch": 0.71, + "learning_rate": 4.093434641585293e-06, + "loss": 1.2071, + "step": 3689 + }, + { + "epoch": 0.71, + "learning_rate": 4.088404982898186e-06, + "loss": 0.7186, + "step": 3690 + }, + { + "epoch": 0.71, + "learning_rate": 4.083377622029403e-06, + "loss": 1.1454, + "step": 3691 + }, + { + "epoch": 0.71, + "learning_rate": 4.078352560933069e-06, + "loss": 0.7708, + "step": 3692 + }, + { + "epoch": 0.71, + "learning_rate": 4.0733298015624075e-06, + "loss": 0.8385, + "step": 3693 + }, + { + "epoch": 0.71, + "learning_rate": 4.068309345869745e-06, + "loss": 0.7841, + "step": 3694 + }, + { + "epoch": 0.71, + "learning_rate": 4.063291195806524e-06, + "loss": 0.7708, + "step": 3695 + }, + { + "epoch": 0.71, + "learning_rate": 4.05827535332328e-06, + "loss": 0.8143, + "step": 3696 + }, + { + "epoch": 0.71, + "learning_rate": 4.053261820369655e-06, + "loss": 1.2651, + "step": 3697 + }, + { + "epoch": 0.71, + "learning_rate": 4.0482505988943935e-06, + "loss": 0.7654, + "step": 3698 + }, + { + "epoch": 0.71, + "learning_rate": 4.043241690845338e-06, + "loss": 0.7638, + "step": 3699 + }, + { + "epoch": 0.71, + "learning_rate": 4.038235098169442e-06, + "loss": 1.2481, + "step": 3700 + }, + { + "epoch": 0.71, + "learning_rate": 4.033230822812745e-06, + "loss": 0.7241, + "step": 3701 + }, + { + "epoch": 0.71, + "learning_rate": 4.028228866720402e-06, + "loss": 0.7779, + "step": 3702 + }, + { + "epoch": 0.71, + "learning_rate": 4.023229231836651e-06, + "loss": 0.7745, + "step": 3703 + }, + { + "epoch": 0.71, + "learning_rate": 4.0182319201048335e-06, + "loss": 0.7861, + "step": 3704 + }, + { + "epoch": 0.71, + "learning_rate": 4.0132369334673945e-06, + "loss": 0.7656, + "step": 3705 + }, + { + "epoch": 0.71, + "learning_rate": 4.008244273865867e-06, + "loss": 0.7561, + "step": 3706 + }, + { + "epoch": 0.71, + "learning_rate": 4.00325394324088e-06, + "loss": 0.7804, + "step": 3707 + }, + { + "epoch": 0.71, + "learning_rate": 3.998265943532161e-06, + "loss": 0.7667, + "step": 3708 + }, + { + "epoch": 0.71, + "learning_rate": 3.993280276678526e-06, + "loss": 0.7488, + "step": 3709 + }, + { + "epoch": 0.71, + "learning_rate": 3.988296944617894e-06, + "loss": 0.7918, + "step": 3710 + }, + { + "epoch": 0.71, + "learning_rate": 3.983315949287265e-06, + "loss": 0.7725, + "step": 3711 + }, + { + "epoch": 0.71, + "learning_rate": 3.978337292622743e-06, + "loss": 0.7325, + "step": 3712 + }, + { + "epoch": 0.71, + "learning_rate": 3.973360976559512e-06, + "loss": 1.1583, + "step": 3713 + }, + { + "epoch": 0.71, + "learning_rate": 3.96838700303185e-06, + "loss": 0.7517, + "step": 3714 + }, + { + "epoch": 0.72, + "learning_rate": 3.963415373973124e-06, + "loss": 0.7855, + "step": 3715 + }, + { + "epoch": 0.72, + "learning_rate": 3.958446091315789e-06, + "loss": 0.7581, + "step": 3716 + }, + { + "epoch": 0.72, + "learning_rate": 3.953479156991396e-06, + "loss": 0.7725, + "step": 3717 + }, + { + "epoch": 0.72, + "learning_rate": 3.9485145729305685e-06, + "loss": 0.8016, + "step": 3718 + }, + { + "epoch": 0.72, + "learning_rate": 3.943552341063034e-06, + "loss": 0.7736, + "step": 3719 + }, + { + "epoch": 0.72, + "learning_rate": 3.93859246331759e-06, + "loss": 0.811, + "step": 3720 + }, + { + "epoch": 0.72, + "learning_rate": 3.933634941622124e-06, + "loss": 0.7528, + "step": 3721 + }, + { + "epoch": 0.72, + "learning_rate": 3.928679777903616e-06, + "loss": 0.7651, + "step": 3722 + }, + { + "epoch": 0.72, + "learning_rate": 3.923726974088117e-06, + "loss": 0.7606, + "step": 3723 + }, + { + "epoch": 0.72, + "learning_rate": 3.918776532100768e-06, + "loss": 0.7438, + "step": 3724 + }, + { + "epoch": 0.72, + "learning_rate": 3.913828453865789e-06, + "loss": 0.7513, + "step": 3725 + }, + { + "epoch": 0.72, + "learning_rate": 3.90888274130648e-06, + "loss": 0.7986, + "step": 3726 + }, + { + "epoch": 0.72, + "learning_rate": 3.903939396345231e-06, + "loss": 0.7707, + "step": 3727 + }, + { + "epoch": 0.72, + "learning_rate": 3.898998420903497e-06, + "loss": 0.7589, + "step": 3728 + }, + { + "epoch": 0.72, + "learning_rate": 3.894059816901826e-06, + "loss": 0.7243, + "step": 3729 + }, + { + "epoch": 0.72, + "learning_rate": 3.889123586259835e-06, + "loss": 1.193, + "step": 3730 + }, + { + "epoch": 0.72, + "learning_rate": 3.884189730896221e-06, + "loss": 0.7372, + "step": 3731 + }, + { + "epoch": 0.72, + "learning_rate": 3.879258252728758e-06, + "loss": 0.7483, + "step": 3732 + }, + { + "epoch": 0.72, + "learning_rate": 3.874329153674293e-06, + "loss": 0.7588, + "step": 3733 + }, + { + "epoch": 0.72, + "learning_rate": 3.869402435648758e-06, + "loss": 0.8353, + "step": 3734 + }, + { + "epoch": 0.72, + "learning_rate": 3.864478100567149e-06, + "loss": 0.7483, + "step": 3735 + }, + { + "epoch": 0.72, + "learning_rate": 3.859556150343536e-06, + "loss": 0.8023, + "step": 3736 + }, + { + "epoch": 0.72, + "learning_rate": 3.854636586891073e-06, + "loss": 0.7645, + "step": 3737 + }, + { + "epoch": 0.72, + "learning_rate": 3.849719412121971e-06, + "loss": 0.7518, + "step": 3738 + }, + { + "epoch": 0.72, + "learning_rate": 3.844804627947528e-06, + "loss": 0.7771, + "step": 3739 + }, + { + "epoch": 0.72, + "learning_rate": 3.839892236278102e-06, + "loss": 0.8175, + "step": 3740 + }, + { + "epoch": 0.72, + "learning_rate": 3.8349822390231225e-06, + "loss": 0.8161, + "step": 3741 + }, + { + "epoch": 0.72, + "learning_rate": 3.830074638091092e-06, + "loss": 0.7913, + "step": 3742 + }, + { + "epoch": 0.72, + "learning_rate": 3.825169435389574e-06, + "loss": 0.7363, + "step": 3743 + }, + { + "epoch": 0.72, + "learning_rate": 3.820266632825214e-06, + "loss": 0.7889, + "step": 3744 + }, + { + "epoch": 0.72, + "learning_rate": 3.815366232303711e-06, + "loss": 1.1392, + "step": 3745 + }, + { + "epoch": 0.72, + "learning_rate": 3.8104682357298327e-06, + "loss": 0.7672, + "step": 3746 + }, + { + "epoch": 0.72, + "learning_rate": 3.8055726450074215e-06, + "loss": 0.7748, + "step": 3747 + }, + { + "epoch": 0.72, + "learning_rate": 3.800679462039375e-06, + "loss": 0.7266, + "step": 3748 + }, + { + "epoch": 0.72, + "learning_rate": 3.7957886887276574e-06, + "loss": 0.788, + "step": 3749 + }, + { + "epoch": 0.72, + "learning_rate": 3.7909003269732926e-06, + "loss": 0.7722, + "step": 3750 + }, + { + "epoch": 0.72, + "learning_rate": 3.7860143786763805e-06, + "loss": 0.7807, + "step": 3751 + }, + { + "epoch": 0.72, + "learning_rate": 3.7811308457360683e-06, + "loss": 0.8154, + "step": 3752 + }, + { + "epoch": 0.72, + "learning_rate": 3.7762497300505676e-06, + "loss": 0.8175, + "step": 3753 + }, + { + "epoch": 0.72, + "learning_rate": 3.771371033517159e-06, + "loss": 1.2248, + "step": 3754 + }, + { + "epoch": 0.72, + "learning_rate": 3.766494758032171e-06, + "loss": 1.1719, + "step": 3755 + }, + { + "epoch": 0.72, + "learning_rate": 3.7616209054910047e-06, + "loss": 0.7511, + "step": 3756 + }, + { + "epoch": 0.72, + "learning_rate": 3.756749477788101e-06, + "loss": 0.7274, + "step": 3757 + }, + { + "epoch": 0.72, + "learning_rate": 3.7518804768169704e-06, + "loss": 0.8364, + "step": 3758 + }, + { + "epoch": 0.72, + "learning_rate": 3.7470139044701824e-06, + "loss": 0.7805, + "step": 3759 + }, + { + "epoch": 0.72, + "learning_rate": 3.7421497626393545e-06, + "loss": 0.7024, + "step": 3760 + }, + { + "epoch": 0.72, + "learning_rate": 3.737288053215168e-06, + "loss": 0.7524, + "step": 3761 + }, + { + "epoch": 0.72, + "learning_rate": 3.7324287780873503e-06, + "loss": 0.7883, + "step": 3762 + }, + { + "epoch": 0.72, + "learning_rate": 3.727571939144685e-06, + "loss": 0.7595, + "step": 3763 + }, + { + "epoch": 0.72, + "learning_rate": 3.7227175382750145e-06, + "loss": 0.7885, + "step": 3764 + }, + { + "epoch": 0.72, + "learning_rate": 3.7178655773652283e-06, + "loss": 0.7672, + "step": 3765 + }, + { + "epoch": 0.72, + "learning_rate": 3.7130160583012666e-06, + "loss": 1.2901, + "step": 3766 + }, + { + "epoch": 0.73, + "learning_rate": 3.708168982968118e-06, + "loss": 0.7626, + "step": 3767 + }, + { + "epoch": 0.73, + "learning_rate": 3.703324353249833e-06, + "loss": 0.8268, + "step": 3768 + }, + { + "epoch": 0.73, + "learning_rate": 3.698482171029502e-06, + "loss": 0.7568, + "step": 3769 + }, + { + "epoch": 0.73, + "learning_rate": 3.69364243818926e-06, + "loss": 0.7475, + "step": 3770 + }, + { + "epoch": 0.73, + "learning_rate": 3.6888051566103044e-06, + "loss": 0.7538, + "step": 3771 + }, + { + "epoch": 0.73, + "learning_rate": 3.6839703281728677e-06, + "loss": 0.8194, + "step": 3772 + }, + { + "epoch": 0.73, + "learning_rate": 3.679137954756232e-06, + "loss": 0.7866, + "step": 3773 + }, + { + "epoch": 0.73, + "learning_rate": 3.674308038238725e-06, + "loss": 0.8196, + "step": 3774 + }, + { + "epoch": 0.73, + "learning_rate": 3.6694805804977183e-06, + "loss": 0.731, + "step": 3775 + }, + { + "epoch": 0.73, + "learning_rate": 3.6646555834096355e-06, + "loss": 0.7629, + "step": 3776 + }, + { + "epoch": 0.73, + "learning_rate": 3.659833048849929e-06, + "loss": 0.8304, + "step": 3777 + }, + { + "epoch": 0.73, + "learning_rate": 3.655012978693113e-06, + "loss": 0.7851, + "step": 3778 + }, + { + "epoch": 0.73, + "learning_rate": 3.6501953748127283e-06, + "loss": 0.7865, + "step": 3779 + }, + { + "epoch": 0.73, + "learning_rate": 3.6453802390813586e-06, + "loss": 0.7215, + "step": 3780 + }, + { + "epoch": 0.73, + "learning_rate": 3.640567573370639e-06, + "loss": 0.7821, + "step": 3781 + }, + { + "epoch": 0.73, + "learning_rate": 3.6357573795512347e-06, + "loss": 0.8062, + "step": 3782 + }, + { + "epoch": 0.73, + "learning_rate": 3.630949659492853e-06, + "loss": 0.7739, + "step": 3783 + }, + { + "epoch": 0.73, + "learning_rate": 3.6261444150642387e-06, + "loss": 0.815, + "step": 3784 + }, + { + "epoch": 0.73, + "learning_rate": 3.621341648133172e-06, + "loss": 0.8086, + "step": 3785 + }, + { + "epoch": 0.73, + "learning_rate": 3.61654136056648e-06, + "loss": 0.7513, + "step": 3786 + }, + { + "epoch": 0.73, + "learning_rate": 3.611743554230013e-06, + "loss": 0.7267, + "step": 3787 + }, + { + "epoch": 0.73, + "learning_rate": 3.6069482309886695e-06, + "loss": 0.782, + "step": 3788 + }, + { + "epoch": 0.73, + "learning_rate": 3.6021553927063725e-06, + "loss": 0.7625, + "step": 3789 + }, + { + "epoch": 0.73, + "learning_rate": 3.597365041246085e-06, + "loss": 0.7173, + "step": 3790 + }, + { + "epoch": 0.73, + "learning_rate": 3.5925771784697993e-06, + "loss": 0.7725, + "step": 3791 + }, + { + "epoch": 0.73, + "learning_rate": 3.587791806238541e-06, + "loss": 0.7973, + "step": 3792 + }, + { + "epoch": 0.73, + "learning_rate": 3.583008926412375e-06, + "loss": 0.7634, + "step": 3793 + }, + { + "epoch": 0.73, + "learning_rate": 3.578228540850388e-06, + "loss": 0.7802, + "step": 3794 + }, + { + "epoch": 0.73, + "learning_rate": 3.5734506514106983e-06, + "loss": 0.7853, + "step": 3795 + }, + { + "epoch": 0.73, + "learning_rate": 3.5686752599504624e-06, + "loss": 0.7848, + "step": 3796 + }, + { + "epoch": 0.73, + "learning_rate": 3.563902368325853e-06, + "loss": 0.7624, + "step": 3797 + }, + { + "epoch": 0.73, + "learning_rate": 3.559131978392086e-06, + "loss": 0.7735, + "step": 3798 + }, + { + "epoch": 0.73, + "learning_rate": 3.5543640920033928e-06, + "loss": 0.728, + "step": 3799 + }, + { + "epoch": 0.73, + "learning_rate": 3.549598711013035e-06, + "loss": 0.8054, + "step": 3800 + }, + { + "epoch": 0.73, + "learning_rate": 3.5448358372733018e-06, + "loss": 0.778, + "step": 3801 + }, + { + "epoch": 0.73, + "learning_rate": 3.540075472635505e-06, + "loss": 0.7995, + "step": 3802 + }, + { + "epoch": 0.73, + "learning_rate": 3.5353176189499873e-06, + "loss": 0.7497, + "step": 3803 + }, + { + "epoch": 0.73, + "learning_rate": 3.5305622780661074e-06, + "loss": 0.7593, + "step": 3804 + }, + { + "epoch": 0.73, + "learning_rate": 3.525809451832257e-06, + "loss": 0.793, + "step": 3805 + }, + { + "epoch": 0.73, + "learning_rate": 3.5210591420958408e-06, + "loss": 0.7881, + "step": 3806 + }, + { + "epoch": 0.73, + "learning_rate": 3.5163113507032898e-06, + "loss": 0.7067, + "step": 3807 + }, + { + "epoch": 0.73, + "learning_rate": 3.511566079500055e-06, + "loss": 0.7512, + "step": 3808 + }, + { + "epoch": 0.73, + "learning_rate": 3.5068233303306056e-06, + "loss": 0.8103, + "step": 3809 + }, + { + "epoch": 0.73, + "learning_rate": 3.5020831050384395e-06, + "loss": 0.7544, + "step": 3810 + }, + { + "epoch": 0.73, + "learning_rate": 3.497345405466065e-06, + "loss": 0.7686, + "step": 3811 + }, + { + "epoch": 0.73, + "learning_rate": 3.492610233455006e-06, + "loss": 0.7914, + "step": 3812 + }, + { + "epoch": 0.73, + "learning_rate": 3.4878775908458174e-06, + "loss": 0.7679, + "step": 3813 + }, + { + "epoch": 0.73, + "learning_rate": 3.483147479478054e-06, + "loss": 0.7607, + "step": 3814 + }, + { + "epoch": 0.73, + "learning_rate": 3.478419901190305e-06, + "loss": 0.831, + "step": 3815 + }, + { + "epoch": 0.73, + "learning_rate": 3.4736948578201534e-06, + "loss": 0.7982, + "step": 3816 + }, + { + "epoch": 0.73, + "learning_rate": 3.4689723512042183e-06, + "loss": 0.7883, + "step": 3817 + }, + { + "epoch": 0.73, + "learning_rate": 3.4642523831781206e-06, + "loss": 0.7926, + "step": 3818 + }, + { + "epoch": 0.74, + "learning_rate": 3.4595349555764914e-06, + "loss": 0.774, + "step": 3819 + }, + { + "epoch": 0.74, + "learning_rate": 3.454820070232987e-06, + "loss": 0.7732, + "step": 3820 + }, + { + "epoch": 0.74, + "learning_rate": 3.4501077289802665e-06, + "loss": 0.6924, + "step": 3821 + }, + { + "epoch": 0.74, + "learning_rate": 3.4453979336499975e-06, + "loss": 0.7507, + "step": 3822 + }, + { + "epoch": 0.74, + "learning_rate": 3.4406906860728705e-06, + "loss": 0.7889, + "step": 3823 + }, + { + "epoch": 0.74, + "learning_rate": 3.435985988078574e-06, + "loss": 0.7364, + "step": 3824 + }, + { + "epoch": 0.74, + "learning_rate": 3.4312838414958084e-06, + "loss": 0.759, + "step": 3825 + }, + { + "epoch": 0.74, + "learning_rate": 3.4265842481522817e-06, + "loss": 0.7948, + "step": 3826 + }, + { + "epoch": 0.74, + "learning_rate": 3.4218872098747147e-06, + "loss": 0.7182, + "step": 3827 + }, + { + "epoch": 0.74, + "learning_rate": 3.4171927284888307e-06, + "loss": 0.7387, + "step": 3828 + }, + { + "epoch": 0.74, + "learning_rate": 3.4125008058193564e-06, + "loss": 0.7649, + "step": 3829 + }, + { + "epoch": 0.74, + "learning_rate": 3.4078114436900323e-06, + "loss": 0.7541, + "step": 3830 + }, + { + "epoch": 0.74, + "learning_rate": 3.4031246439235965e-06, + "loss": 0.7561, + "step": 3831 + }, + { + "epoch": 0.74, + "learning_rate": 3.398440408341792e-06, + "loss": 0.7613, + "step": 3832 + }, + { + "epoch": 0.74, + "learning_rate": 3.393758738765368e-06, + "loss": 0.7598, + "step": 3833 + }, + { + "epoch": 0.74, + "learning_rate": 3.389079637014071e-06, + "loss": 0.7703, + "step": 3834 + }, + { + "epoch": 0.74, + "learning_rate": 3.3844031049066594e-06, + "loss": 0.7657, + "step": 3835 + }, + { + "epoch": 0.74, + "learning_rate": 3.3797291442608805e-06, + "loss": 1.1791, + "step": 3836 + }, + { + "epoch": 0.74, + "learning_rate": 3.3750577568934937e-06, + "loss": 0.7566, + "step": 3837 + }, + { + "epoch": 0.74, + "learning_rate": 3.3703889446202497e-06, + "loss": 0.7534, + "step": 3838 + }, + { + "epoch": 0.74, + "learning_rate": 3.3657227092558975e-06, + "loss": 0.7816, + "step": 3839 + }, + { + "epoch": 0.74, + "learning_rate": 3.3610590526141938e-06, + "loss": 0.7949, + "step": 3840 + }, + { + "epoch": 0.74, + "learning_rate": 3.356397976507887e-06, + "loss": 0.7049, + "step": 3841 + }, + { + "epoch": 0.74, + "learning_rate": 3.3517394827487194e-06, + "loss": 0.8039, + "step": 3842 + }, + { + "epoch": 0.74, + "learning_rate": 3.347083573147434e-06, + "loss": 0.7637, + "step": 3843 + }, + { + "epoch": 0.74, + "learning_rate": 3.342430249513765e-06, + "loss": 0.7894, + "step": 3844 + }, + { + "epoch": 0.74, + "learning_rate": 3.3377795136564515e-06, + "loss": 0.7709, + "step": 3845 + }, + { + "epoch": 0.74, + "learning_rate": 3.3331313673832132e-06, + "loss": 0.786, + "step": 3846 + }, + { + "epoch": 0.74, + "learning_rate": 3.328485812500776e-06, + "loss": 0.7129, + "step": 3847 + }, + { + "epoch": 0.74, + "learning_rate": 3.323842850814849e-06, + "loss": 0.7689, + "step": 3848 + }, + { + "epoch": 0.74, + "learning_rate": 3.3192024841301373e-06, + "loss": 0.7487, + "step": 3849 + }, + { + "epoch": 0.74, + "learning_rate": 3.314564714250337e-06, + "loss": 0.7567, + "step": 3850 + }, + { + "epoch": 0.74, + "learning_rate": 3.3099295429781296e-06, + "loss": 0.76, + "step": 3851 + }, + { + "epoch": 0.74, + "learning_rate": 3.3052969721152007e-06, + "loss": 0.7373, + "step": 3852 + }, + { + "epoch": 0.74, + "learning_rate": 3.300667003462208e-06, + "loss": 0.7361, + "step": 3853 + }, + { + "epoch": 0.74, + "learning_rate": 3.2960396388188122e-06, + "loss": 0.8288, + "step": 3854 + }, + { + "epoch": 0.74, + "learning_rate": 3.291414879983652e-06, + "loss": 0.7207, + "step": 3855 + }, + { + "epoch": 0.74, + "learning_rate": 3.2867927287543535e-06, + "loss": 1.1389, + "step": 3856 + }, + { + "epoch": 0.74, + "learning_rate": 3.282173186927539e-06, + "loss": 0.7355, + "step": 3857 + }, + { + "epoch": 0.74, + "learning_rate": 3.277556256298806e-06, + "loss": 0.785, + "step": 3858 + }, + { + "epoch": 0.74, + "learning_rate": 3.2729419386627414e-06, + "loss": 0.8176, + "step": 3859 + }, + { + "epoch": 0.74, + "learning_rate": 3.2683302358129164e-06, + "loss": 0.8204, + "step": 3860 + }, + { + "epoch": 0.74, + "learning_rate": 3.263721149541881e-06, + "loss": 0.7912, + "step": 3861 + }, + { + "epoch": 0.74, + "learning_rate": 3.25911468164118e-06, + "loss": 0.7486, + "step": 3862 + }, + { + "epoch": 0.74, + "learning_rate": 3.2545108339013254e-06, + "loss": 0.7406, + "step": 3863 + }, + { + "epoch": 0.74, + "learning_rate": 3.2499096081118254e-06, + "loss": 0.7887, + "step": 3864 + }, + { + "epoch": 0.74, + "learning_rate": 3.245311006061159e-06, + "loss": 0.6952, + "step": 3865 + }, + { + "epoch": 0.74, + "learning_rate": 3.240715029536787e-06, + "loss": 0.7667, + "step": 3866 + }, + { + "epoch": 0.74, + "learning_rate": 3.2361216803251528e-06, + "loss": 0.8074, + "step": 3867 + }, + { + "epoch": 0.74, + "learning_rate": 3.231530960211672e-06, + "loss": 0.7723, + "step": 3868 + }, + { + "epoch": 0.74, + "learning_rate": 3.2269428709807505e-06, + "loss": 0.7505, + "step": 3869 + }, + { + "epoch": 0.74, + "learning_rate": 3.22235741441576e-06, + "loss": 0.7503, + "step": 3870 + }, + { + "epoch": 0.75, + "learning_rate": 3.217774592299051e-06, + "loss": 0.8255, + "step": 3871 + }, + { + "epoch": 0.75, + "learning_rate": 3.213194406411957e-06, + "loss": 0.8293, + "step": 3872 + }, + { + "epoch": 0.75, + "learning_rate": 3.2086168585347756e-06, + "loss": 0.7731, + "step": 3873 + }, + { + "epoch": 0.75, + "learning_rate": 3.204041950446792e-06, + "loss": 0.8047, + "step": 3874 + }, + { + "epoch": 0.75, + "learning_rate": 3.1994696839262562e-06, + "loss": 0.7575, + "step": 3875 + }, + { + "epoch": 0.75, + "learning_rate": 3.194900060750393e-06, + "loss": 0.717, + "step": 3876 + }, + { + "epoch": 0.75, + "learning_rate": 3.1903330826954006e-06, + "loss": 0.7603, + "step": 3877 + }, + { + "epoch": 0.75, + "learning_rate": 3.1857687515364445e-06, + "loss": 0.7718, + "step": 3878 + }, + { + "epoch": 0.75, + "learning_rate": 3.181207069047674e-06, + "loss": 0.7577, + "step": 3879 + }, + { + "epoch": 0.75, + "learning_rate": 3.1766480370021967e-06, + "loss": 0.7884, + "step": 3880 + }, + { + "epoch": 0.75, + "learning_rate": 3.1720916571720915e-06, + "loss": 0.7499, + "step": 3881 + }, + { + "epoch": 0.75, + "learning_rate": 3.167537931328414e-06, + "loss": 0.7345, + "step": 3882 + }, + { + "epoch": 0.75, + "learning_rate": 3.162986861241181e-06, + "loss": 0.7921, + "step": 3883 + }, + { + "epoch": 0.75, + "learning_rate": 3.1584384486793774e-06, + "loss": 0.8441, + "step": 3884 + }, + { + "epoch": 0.75, + "learning_rate": 3.153892695410956e-06, + "loss": 0.7605, + "step": 3885 + }, + { + "epoch": 0.75, + "learning_rate": 3.1493496032028416e-06, + "loss": 0.7107, + "step": 3886 + }, + { + "epoch": 0.75, + "learning_rate": 3.1448091738209165e-06, + "loss": 0.7327, + "step": 3887 + }, + { + "epoch": 0.75, + "learning_rate": 3.140271409030029e-06, + "loss": 0.7479, + "step": 3888 + }, + { + "epoch": 0.75, + "learning_rate": 3.1357363105939997e-06, + "loss": 0.7568, + "step": 3889 + }, + { + "epoch": 0.75, + "learning_rate": 3.131203880275604e-06, + "loss": 0.7774, + "step": 3890 + }, + { + "epoch": 0.75, + "learning_rate": 3.1266741198365834e-06, + "loss": 1.2203, + "step": 3891 + }, + { + "epoch": 0.75, + "learning_rate": 3.1221470310376423e-06, + "loss": 0.7699, + "step": 3892 + }, + { + "epoch": 0.75, + "learning_rate": 3.1176226156384405e-06, + "loss": 0.8065, + "step": 3893 + }, + { + "epoch": 0.75, + "learning_rate": 3.1131008753976123e-06, + "loss": 0.7619, + "step": 3894 + }, + { + "epoch": 0.75, + "learning_rate": 3.1085818120727363e-06, + "loss": 0.735, + "step": 3895 + }, + { + "epoch": 0.75, + "learning_rate": 3.104065427420364e-06, + "loss": 0.7266, + "step": 3896 + }, + { + "epoch": 0.75, + "learning_rate": 3.0995517231959994e-06, + "loss": 1.2077, + "step": 3897 + }, + { + "epoch": 0.75, + "learning_rate": 3.0950407011540996e-06, + "loss": 0.6905, + "step": 3898 + }, + { + "epoch": 0.75, + "learning_rate": 3.0905323630480912e-06, + "loss": 0.7742, + "step": 3899 + }, + { + "epoch": 0.75, + "learning_rate": 3.0860267106303487e-06, + "loss": 0.7729, + "step": 3900 + }, + { + "epoch": 0.75, + "learning_rate": 3.081523745652204e-06, + "loss": 0.8238, + "step": 3901 + }, + { + "epoch": 0.75, + "learning_rate": 3.0770234698639434e-06, + "loss": 0.8042, + "step": 3902 + }, + { + "epoch": 0.75, + "learning_rate": 3.072525885014814e-06, + "loss": 0.7633, + "step": 3903 + }, + { + "epoch": 0.75, + "learning_rate": 3.068030992853013e-06, + "loss": 0.8117, + "step": 3904 + }, + { + "epoch": 0.75, + "learning_rate": 3.0635387951256846e-06, + "loss": 0.783, + "step": 3905 + }, + { + "epoch": 0.75, + "learning_rate": 3.0590492935789396e-06, + "loss": 0.7768, + "step": 3906 + }, + { + "epoch": 0.75, + "learning_rate": 3.054562489957831e-06, + "loss": 0.6831, + "step": 3907 + }, + { + "epoch": 0.75, + "learning_rate": 3.050078386006362e-06, + "loss": 0.7998, + "step": 3908 + }, + { + "epoch": 0.75, + "learning_rate": 3.0455969834674926e-06, + "loss": 0.7605, + "step": 3909 + }, + { + "epoch": 0.75, + "learning_rate": 3.0411182840831255e-06, + "loss": 0.8155, + "step": 3910 + }, + { + "epoch": 0.75, + "learning_rate": 3.036642289594124e-06, + "loss": 0.7727, + "step": 3911 + }, + { + "epoch": 0.75, + "learning_rate": 3.032169001740285e-06, + "loss": 0.7584, + "step": 3912 + }, + { + "epoch": 0.75, + "learning_rate": 3.02769842226037e-06, + "loss": 0.7378, + "step": 3913 + }, + { + "epoch": 0.75, + "learning_rate": 3.0232305528920748e-06, + "loss": 0.849, + "step": 3914 + }, + { + "epoch": 0.75, + "learning_rate": 3.018765395372042e-06, + "loss": 0.8129, + "step": 3915 + }, + { + "epoch": 0.75, + "learning_rate": 3.0143029514358725e-06, + "loss": 0.7725, + "step": 3916 + }, + { + "epoch": 0.75, + "learning_rate": 3.0098432228180994e-06, + "loss": 0.7661, + "step": 3917 + }, + { + "epoch": 0.75, + "learning_rate": 3.005386211252207e-06, + "loss": 0.7841, + "step": 3918 + }, + { + "epoch": 0.75, + "learning_rate": 3.00093191847062e-06, + "loss": 0.7934, + "step": 3919 + }, + { + "epoch": 0.75, + "learning_rate": 2.9964803462047055e-06, + "loss": 0.7461, + "step": 3920 + }, + { + "epoch": 0.75, + "learning_rate": 2.992031496184781e-06, + "loss": 0.7471, + "step": 3921 + }, + { + "epoch": 0.75, + "learning_rate": 2.9875853701400947e-06, + "loss": 0.7719, + "step": 3922 + }, + { + "epoch": 0.76, + "learning_rate": 2.9831419697988486e-06, + "loss": 1.2252, + "step": 3923 + }, + { + "epoch": 0.76, + "learning_rate": 2.9787012968881755e-06, + "loss": 0.8063, + "step": 3924 + }, + { + "epoch": 0.76, + "learning_rate": 2.9742633531341493e-06, + "loss": 0.7244, + "step": 3925 + }, + { + "epoch": 0.76, + "learning_rate": 2.9698281402617856e-06, + "loss": 0.756, + "step": 3926 + }, + { + "epoch": 0.76, + "learning_rate": 2.965395659995035e-06, + "loss": 0.7426, + "step": 3927 + }, + { + "epoch": 0.76, + "learning_rate": 2.9609659140567947e-06, + "loss": 0.7456, + "step": 3928 + }, + { + "epoch": 0.76, + "learning_rate": 2.9565389041688896e-06, + "loss": 0.8143, + "step": 3929 + }, + { + "epoch": 0.76, + "learning_rate": 2.952114632052081e-06, + "loss": 0.7991, + "step": 3930 + }, + { + "epoch": 0.76, + "learning_rate": 2.9476930994260764e-06, + "loss": 0.7508, + "step": 3931 + }, + { + "epoch": 0.76, + "learning_rate": 2.943274308009505e-06, + "loss": 1.155, + "step": 3932 + }, + { + "epoch": 0.76, + "learning_rate": 2.9388582595199442e-06, + "loss": 0.8017, + "step": 3933 + }, + { + "epoch": 0.76, + "learning_rate": 2.934444955673893e-06, + "loss": 0.8083, + "step": 3934 + }, + { + "epoch": 0.76, + "learning_rate": 2.9300343981867906e-06, + "loss": 0.8033, + "step": 3935 + }, + { + "epoch": 0.76, + "learning_rate": 2.925626588773005e-06, + "loss": 0.7796, + "step": 3936 + }, + { + "epoch": 0.76, + "learning_rate": 2.9212215291458368e-06, + "loss": 0.7691, + "step": 3937 + }, + { + "epoch": 0.76, + "learning_rate": 2.9168192210175238e-06, + "loss": 1.1556, + "step": 3938 + }, + { + "epoch": 0.76, + "learning_rate": 2.9124196660992255e-06, + "loss": 0.7673, + "step": 3939 + }, + { + "epoch": 0.76, + "learning_rate": 2.9080228661010333e-06, + "loss": 0.7739, + "step": 3940 + }, + { + "epoch": 0.76, + "learning_rate": 2.903628822731975e-06, + "loss": 0.7754, + "step": 3941 + }, + { + "epoch": 0.76, + "learning_rate": 2.899237537699998e-06, + "loss": 0.7095, + "step": 3942 + }, + { + "epoch": 0.76, + "learning_rate": 2.894849012711982e-06, + "loss": 0.7502, + "step": 3943 + }, + { + "epoch": 0.76, + "learning_rate": 2.8904632494737283e-06, + "loss": 0.7175, + "step": 3944 + }, + { + "epoch": 0.76, + "learning_rate": 2.8860802496899765e-06, + "loss": 0.7819, + "step": 3945 + }, + { + "epoch": 0.76, + "learning_rate": 2.8817000150643813e-06, + "loss": 0.7557, + "step": 3946 + }, + { + "epoch": 0.76, + "learning_rate": 2.8773225472995224e-06, + "loss": 1.1978, + "step": 3947 + }, + { + "epoch": 0.76, + "learning_rate": 2.8729478480969154e-06, + "loss": 0.776, + "step": 3948 + }, + { + "epoch": 0.76, + "learning_rate": 2.8685759191569852e-06, + "loss": 0.7326, + "step": 3949 + }, + { + "epoch": 0.76, + "learning_rate": 2.8642067621790926e-06, + "loss": 0.7735, + "step": 3950 + }, + { + "epoch": 0.76, + "learning_rate": 2.859840378861515e-06, + "loss": 0.7393, + "step": 3951 + }, + { + "epoch": 0.76, + "learning_rate": 2.855476770901442e-06, + "loss": 0.7098, + "step": 3952 + }, + { + "epoch": 0.76, + "learning_rate": 2.851115939995005e-06, + "loss": 0.7916, + "step": 3953 + }, + { + "epoch": 0.76, + "learning_rate": 2.8467578878372394e-06, + "loss": 0.7565, + "step": 3954 + }, + { + "epoch": 0.76, + "learning_rate": 2.84240261612211e-06, + "loss": 0.7774, + "step": 3955 + }, + { + "epoch": 0.76, + "learning_rate": 2.8380501265424963e-06, + "loss": 1.2595, + "step": 3956 + }, + { + "epoch": 0.76, + "learning_rate": 2.833700420790193e-06, + "loss": 0.7177, + "step": 3957 + }, + { + "epoch": 0.76, + "learning_rate": 2.8293535005559237e-06, + "loss": 0.731, + "step": 3958 + }, + { + "epoch": 0.76, + "learning_rate": 2.82500936752932e-06, + "loss": 0.7912, + "step": 3959 + }, + { + "epoch": 0.76, + "learning_rate": 2.8206680233989314e-06, + "loss": 0.7582, + "step": 3960 + }, + { + "epoch": 0.76, + "learning_rate": 2.8163294698522224e-06, + "loss": 0.6975, + "step": 3961 + }, + { + "epoch": 0.76, + "learning_rate": 2.811993708575581e-06, + "loss": 0.7846, + "step": 3962 + }, + { + "epoch": 0.76, + "learning_rate": 2.807660741254302e-06, + "loss": 0.7952, + "step": 3963 + }, + { + "epoch": 0.76, + "learning_rate": 2.803330569572591e-06, + "loss": 0.7562, + "step": 3964 + }, + { + "epoch": 0.76, + "learning_rate": 2.79900319521358e-06, + "loss": 0.746, + "step": 3965 + }, + { + "epoch": 0.76, + "learning_rate": 2.794678619859301e-06, + "loss": 0.6961, + "step": 3966 + }, + { + "epoch": 0.76, + "learning_rate": 2.7903568451907036e-06, + "loss": 0.7253, + "step": 3967 + }, + { + "epoch": 0.76, + "learning_rate": 2.7860378728876493e-06, + "loss": 0.8343, + "step": 3968 + }, + { + "epoch": 0.76, + "learning_rate": 2.7817217046289037e-06, + "loss": 1.1623, + "step": 3969 + }, + { + "epoch": 0.76, + "learning_rate": 2.777408342092155e-06, + "loss": 0.7688, + "step": 3970 + }, + { + "epoch": 0.76, + "learning_rate": 2.7730977869539878e-06, + "loss": 0.6961, + "step": 3971 + }, + { + "epoch": 0.76, + "learning_rate": 2.768790040889906e-06, + "loss": 0.7522, + "step": 3972 + }, + { + "epoch": 0.76, + "learning_rate": 2.764485105574316e-06, + "loss": 0.8109, + "step": 3973 + }, + { + "epoch": 0.76, + "learning_rate": 2.760182982680528e-06, + "loss": 0.7617, + "step": 3974 + }, + { + "epoch": 0.77, + "learning_rate": 2.7558836738807704e-06, + "loss": 0.7466, + "step": 3975 + }, + { + "epoch": 0.77, + "learning_rate": 2.751587180846167e-06, + "loss": 0.8031, + "step": 3976 + }, + { + "epoch": 0.77, + "learning_rate": 2.747293505246752e-06, + "loss": 0.7094, + "step": 3977 + }, + { + "epoch": 0.77, + "learning_rate": 2.7430026487514628e-06, + "loss": 0.7432, + "step": 3978 + }, + { + "epoch": 0.77, + "learning_rate": 2.7387146130281394e-06, + "loss": 0.7835, + "step": 3979 + }, + { + "epoch": 0.77, + "learning_rate": 2.734429399743533e-06, + "loss": 0.7724, + "step": 3980 + }, + { + "epoch": 0.77, + "learning_rate": 2.7301470105632875e-06, + "loss": 0.8196, + "step": 3981 + }, + { + "epoch": 0.77, + "learning_rate": 2.725867447151961e-06, + "loss": 0.7518, + "step": 3982 + }, + { + "epoch": 0.77, + "learning_rate": 2.721590711173e-06, + "loss": 0.7661, + "step": 3983 + }, + { + "epoch": 0.77, + "learning_rate": 2.717316804288761e-06, + "loss": 0.7786, + "step": 3984 + }, + { + "epoch": 0.77, + "learning_rate": 2.713045728160496e-06, + "loss": 0.7328, + "step": 3985 + }, + { + "epoch": 0.77, + "learning_rate": 2.708777484448358e-06, + "loss": 0.7499, + "step": 3986 + }, + { + "epoch": 0.77, + "learning_rate": 2.704512074811405e-06, + "loss": 0.8226, + "step": 3987 + }, + { + "epoch": 0.77, + "learning_rate": 2.7002495009075856e-06, + "loss": 0.768, + "step": 3988 + }, + { + "epoch": 0.77, + "learning_rate": 2.6959897643937448e-06, + "loss": 0.782, + "step": 3989 + }, + { + "epoch": 0.77, + "learning_rate": 2.691732866925636e-06, + "loss": 0.7476, + "step": 3990 + }, + { + "epoch": 0.77, + "learning_rate": 2.687478810157895e-06, + "loss": 0.7623, + "step": 3991 + }, + { + "epoch": 0.77, + "learning_rate": 2.6832275957440658e-06, + "loss": 0.8096, + "step": 3992 + }, + { + "epoch": 0.77, + "learning_rate": 2.67897922533658e-06, + "loss": 0.6826, + "step": 3993 + }, + { + "epoch": 0.77, + "learning_rate": 2.674733700586766e-06, + "loss": 0.8375, + "step": 3994 + }, + { + "epoch": 0.77, + "learning_rate": 2.6704910231448446e-06, + "loss": 0.7539, + "step": 3995 + }, + { + "epoch": 0.77, + "learning_rate": 2.666251194659929e-06, + "loss": 0.7722, + "step": 3996 + }, + { + "epoch": 0.77, + "learning_rate": 2.6620142167800335e-06, + "loss": 0.7059, + "step": 3997 + }, + { + "epoch": 0.77, + "learning_rate": 2.65778009115205e-06, + "loss": 0.7642, + "step": 3998 + }, + { + "epoch": 0.77, + "learning_rate": 2.6535488194217786e-06, + "loss": 0.7813, + "step": 3999 + }, + { + "epoch": 0.77, + "learning_rate": 2.649320403233897e-06, + "loss": 0.7971, + "step": 4000 + }, + { + "epoch": 0.77, + "learning_rate": 2.6450948442319767e-06, + "loss": 0.7571, + "step": 4001 + }, + { + "epoch": 0.77, + "learning_rate": 2.6408721440584793e-06, + "loss": 0.8291, + "step": 4002 + }, + { + "epoch": 0.77, + "learning_rate": 2.6366523043547534e-06, + "loss": 0.8367, + "step": 4003 + }, + { + "epoch": 0.77, + "learning_rate": 2.6324353267610413e-06, + "loss": 0.6772, + "step": 4004 + }, + { + "epoch": 0.77, + "learning_rate": 2.6282212129164676e-06, + "loss": 1.1704, + "step": 4005 + }, + { + "epoch": 0.77, + "learning_rate": 2.624009964459041e-06, + "loss": 0.7266, + "step": 4006 + }, + { + "epoch": 0.77, + "learning_rate": 2.619801583025666e-06, + "loss": 0.7687, + "step": 4007 + }, + { + "epoch": 0.77, + "learning_rate": 2.615596070252123e-06, + "loss": 0.7544, + "step": 4008 + }, + { + "epoch": 0.77, + "learning_rate": 2.6113934277730866e-06, + "loss": 0.8181, + "step": 4009 + }, + { + "epoch": 0.77, + "learning_rate": 2.607193657222108e-06, + "loss": 0.8149, + "step": 4010 + }, + { + "epoch": 0.77, + "learning_rate": 2.602996760231624e-06, + "loss": 0.764, + "step": 4011 + }, + { + "epoch": 0.77, + "learning_rate": 2.5988027384329562e-06, + "loss": 0.757, + "step": 4012 + }, + { + "epoch": 0.77, + "learning_rate": 2.594611593456303e-06, + "loss": 0.75, + "step": 4013 + }, + { + "epoch": 0.77, + "learning_rate": 2.5904233269307566e-06, + "loss": 0.7562, + "step": 4014 + }, + { + "epoch": 0.77, + "learning_rate": 2.5862379404842795e-06, + "loss": 0.7887, + "step": 4015 + }, + { + "epoch": 0.77, + "learning_rate": 2.5820554357437166e-06, + "loss": 0.7729, + "step": 4016 + }, + { + "epoch": 0.77, + "learning_rate": 2.5778758143347983e-06, + "loss": 0.7553, + "step": 4017 + }, + { + "epoch": 0.77, + "learning_rate": 2.5736990778821268e-06, + "loss": 0.805, + "step": 4018 + }, + { + "epoch": 0.77, + "learning_rate": 2.5695252280091888e-06, + "loss": 0.7339, + "step": 4019 + }, + { + "epoch": 0.77, + "learning_rate": 2.5653542663383426e-06, + "loss": 0.832, + "step": 4020 + }, + { + "epoch": 0.77, + "learning_rate": 2.5611861944908334e-06, + "loss": 0.7799, + "step": 4021 + }, + { + "epoch": 0.77, + "learning_rate": 2.5570210140867747e-06, + "loss": 0.7611, + "step": 4022 + }, + { + "epoch": 0.77, + "learning_rate": 2.5528587267451554e-06, + "loss": 0.8132, + "step": 4023 + }, + { + "epoch": 0.77, + "learning_rate": 2.5486993340838505e-06, + "loss": 0.7385, + "step": 4024 + }, + { + "epoch": 0.77, + "learning_rate": 2.5445428377196e-06, + "loss": 0.779, + "step": 4025 + }, + { + "epoch": 0.77, + "learning_rate": 2.5403892392680197e-06, + "loss": 1.1896, + "step": 4026 + }, + { + "epoch": 0.78, + "learning_rate": 2.5362385403436006e-06, + "loss": 0.7439, + "step": 4027 + }, + { + "epoch": 0.78, + "learning_rate": 2.532090742559704e-06, + "loss": 0.769, + "step": 4028 + }, + { + "epoch": 0.78, + "learning_rate": 2.5279458475285714e-06, + "loss": 0.7591, + "step": 4029 + }, + { + "epoch": 0.78, + "learning_rate": 2.5238038568613045e-06, + "loss": 1.1012, + "step": 4030 + }, + { + "epoch": 0.78, + "learning_rate": 2.5196647721678878e-06, + "loss": 0.7534, + "step": 4031 + }, + { + "epoch": 0.78, + "learning_rate": 2.5155285950571675e-06, + "loss": 0.786, + "step": 4032 + }, + { + "epoch": 0.78, + "learning_rate": 2.5113953271368584e-06, + "loss": 0.771, + "step": 4033 + }, + { + "epoch": 0.78, + "learning_rate": 2.5072649700135575e-06, + "loss": 0.7706, + "step": 4034 + }, + { + "epoch": 0.78, + "learning_rate": 2.503137525292716e-06, + "loss": 0.8177, + "step": 4035 + }, + { + "epoch": 0.78, + "learning_rate": 2.49901299457866e-06, + "loss": 1.2941, + "step": 4036 + }, + { + "epoch": 0.78, + "learning_rate": 2.494891379474581e-06, + "loss": 0.786, + "step": 4037 + }, + { + "epoch": 0.78, + "learning_rate": 2.490772681582535e-06, + "loss": 0.8324, + "step": 4038 + }, + { + "epoch": 0.78, + "learning_rate": 2.4866569025034527e-06, + "loss": 0.7648, + "step": 4039 + }, + { + "epoch": 0.78, + "learning_rate": 2.4825440438371186e-06, + "loss": 0.8472, + "step": 4040 + }, + { + "epoch": 0.78, + "learning_rate": 2.478434107182194e-06, + "loss": 0.7997, + "step": 4041 + }, + { + "epoch": 0.78, + "learning_rate": 2.4743270941361953e-06, + "loss": 0.7554, + "step": 4042 + }, + { + "epoch": 0.78, + "learning_rate": 2.4702230062955055e-06, + "loss": 0.841, + "step": 4043 + }, + { + "epoch": 0.78, + "learning_rate": 2.46612184525537e-06, + "loss": 0.7515, + "step": 4044 + }, + { + "epoch": 0.78, + "learning_rate": 2.462023612609895e-06, + "loss": 0.8043, + "step": 4045 + }, + { + "epoch": 0.78, + "learning_rate": 2.4579283099520556e-06, + "loss": 0.7837, + "step": 4046 + }, + { + "epoch": 0.78, + "learning_rate": 2.4538359388736775e-06, + "loss": 0.7656, + "step": 4047 + }, + { + "epoch": 0.78, + "learning_rate": 2.4497465009654597e-06, + "loss": 0.757, + "step": 4048 + }, + { + "epoch": 0.78, + "learning_rate": 2.4456599978169495e-06, + "loss": 0.7207, + "step": 4049 + }, + { + "epoch": 0.78, + "learning_rate": 2.4415764310165546e-06, + "loss": 0.791, + "step": 4050 + }, + { + "epoch": 0.78, + "learning_rate": 2.4374958021515505e-06, + "loss": 0.7416, + "step": 4051 + }, + { + "epoch": 0.78, + "learning_rate": 2.4334181128080626e-06, + "loss": 0.8293, + "step": 4052 + }, + { + "epoch": 0.78, + "learning_rate": 2.429343364571075e-06, + "loss": 0.7254, + "step": 4053 + }, + { + "epoch": 0.78, + "learning_rate": 2.4252715590244303e-06, + "loss": 0.7358, + "step": 4054 + }, + { + "epoch": 0.78, + "learning_rate": 2.421202697750822e-06, + "loss": 0.7926, + "step": 4055 + }, + { + "epoch": 0.78, + "learning_rate": 2.4171367823318115e-06, + "loss": 0.7814, + "step": 4056 + }, + { + "epoch": 0.78, + "learning_rate": 2.4130738143478005e-06, + "loss": 0.7611, + "step": 4057 + }, + { + "epoch": 0.78, + "learning_rate": 2.409013795378058e-06, + "loss": 0.7754, + "step": 4058 + }, + { + "epoch": 0.78, + "learning_rate": 2.404956727000698e-06, + "loss": 0.7809, + "step": 4059 + }, + { + "epoch": 0.78, + "learning_rate": 2.400902610792688e-06, + "loss": 0.7669, + "step": 4060 + }, + { + "epoch": 0.78, + "learning_rate": 2.396851448329853e-06, + "loss": 0.839, + "step": 4061 + }, + { + "epoch": 0.78, + "learning_rate": 2.392803241186862e-06, + "loss": 0.7573, + "step": 4062 + }, + { + "epoch": 0.78, + "learning_rate": 2.3887579909372472e-06, + "loss": 0.8159, + "step": 4063 + }, + { + "epoch": 0.78, + "learning_rate": 2.3847156991533825e-06, + "loss": 0.7657, + "step": 4064 + }, + { + "epoch": 0.78, + "learning_rate": 2.3806763674064893e-06, + "loss": 0.748, + "step": 4065 + }, + { + "epoch": 0.78, + "learning_rate": 2.3766399972666498e-06, + "loss": 0.7531, + "step": 4066 + }, + { + "epoch": 0.78, + "learning_rate": 2.3726065903027816e-06, + "loss": 0.7887, + "step": 4067 + }, + { + "epoch": 0.78, + "learning_rate": 2.3685761480826653e-06, + "loss": 1.1255, + "step": 4068 + }, + { + "epoch": 0.78, + "learning_rate": 2.364548672172916e-06, + "loss": 0.7625, + "step": 4069 + }, + { + "epoch": 0.78, + "learning_rate": 2.360524164139002e-06, + "loss": 1.2141, + "step": 4070 + }, + { + "epoch": 0.78, + "learning_rate": 2.3565026255452363e-06, + "loss": 0.8026, + "step": 4071 + }, + { + "epoch": 0.78, + "learning_rate": 2.352484057954776e-06, + "loss": 0.7819, + "step": 4072 + }, + { + "epoch": 0.78, + "learning_rate": 2.3484684629296307e-06, + "loss": 0.7882, + "step": 4073 + }, + { + "epoch": 0.78, + "learning_rate": 2.3444558420306464e-06, + "loss": 0.7319, + "step": 4074 + }, + { + "epoch": 0.78, + "learning_rate": 2.340446196817515e-06, + "loss": 1.144, + "step": 4075 + }, + { + "epoch": 0.78, + "learning_rate": 2.336439528848776e-06, + "loss": 0.7421, + "step": 4076 + }, + { + "epoch": 0.78, + "learning_rate": 2.332435839681808e-06, + "loss": 0.738, + "step": 4077 + }, + { + "epoch": 0.78, + "learning_rate": 2.3284351308728325e-06, + "loss": 0.7585, + "step": 4078 + }, + { + "epoch": 0.79, + "learning_rate": 2.324437403976908e-06, + "loss": 0.7964, + "step": 4079 + }, + { + "epoch": 0.79, + "learning_rate": 2.3204426605479448e-06, + "loss": 1.1395, + "step": 4080 + }, + { + "epoch": 0.79, + "learning_rate": 2.3164509021386828e-06, + "loss": 0.7808, + "step": 4081 + }, + { + "epoch": 0.79, + "learning_rate": 2.3124621303007055e-06, + "loss": 0.7552, + "step": 4082 + }, + { + "epoch": 0.79, + "learning_rate": 2.308476346584441e-06, + "loss": 0.7837, + "step": 4083 + }, + { + "epoch": 0.79, + "learning_rate": 2.3044935525391454e-06, + "loss": 0.7692, + "step": 4084 + }, + { + "epoch": 0.79, + "learning_rate": 2.3005137497129193e-06, + "loss": 0.7567, + "step": 4085 + }, + { + "epoch": 0.79, + "learning_rate": 2.2965369396527048e-06, + "loss": 0.788, + "step": 4086 + }, + { + "epoch": 0.79, + "learning_rate": 2.2925631239042666e-06, + "loss": 0.7714, + "step": 4087 + }, + { + "epoch": 0.79, + "learning_rate": 2.2885923040122214e-06, + "loss": 0.8239, + "step": 4088 + }, + { + "epoch": 0.79, + "learning_rate": 2.2846244815200082e-06, + "loss": 0.7266, + "step": 4089 + }, + { + "epoch": 0.79, + "learning_rate": 2.280659657969914e-06, + "loss": 0.769, + "step": 4090 + }, + { + "epoch": 0.79, + "learning_rate": 2.27669783490305e-06, + "loss": 0.8103, + "step": 4091 + }, + { + "epoch": 0.79, + "learning_rate": 2.272739013859361e-06, + "loss": 0.8667, + "step": 4092 + }, + { + "epoch": 0.79, + "learning_rate": 2.268783196377634e-06, + "loss": 0.8043, + "step": 4093 + }, + { + "epoch": 0.79, + "learning_rate": 2.26483038399548e-06, + "loss": 0.7723, + "step": 4094 + }, + { + "epoch": 0.79, + "learning_rate": 2.2608805782493448e-06, + "loss": 0.7534, + "step": 4095 + }, + { + "epoch": 0.79, + "learning_rate": 2.256933780674504e-06, + "loss": 0.7555, + "step": 4096 + }, + { + "epoch": 0.79, + "learning_rate": 2.252989992805068e-06, + "loss": 0.8078, + "step": 4097 + }, + { + "epoch": 0.79, + "learning_rate": 2.2490492161739753e-06, + "loss": 0.7448, + "step": 4098 + }, + { + "epoch": 0.79, + "learning_rate": 2.245111452312987e-06, + "loss": 0.7474, + "step": 4099 + }, + { + "epoch": 0.79, + "learning_rate": 2.2411767027527076e-06, + "loss": 0.7199, + "step": 4100 + }, + { + "epoch": 0.79, + "learning_rate": 2.2372449690225585e-06, + "loss": 0.8119, + "step": 4101 + }, + { + "epoch": 0.79, + "learning_rate": 2.2333162526507923e-06, + "loss": 0.7598, + "step": 4102 + }, + { + "epoch": 0.79, + "learning_rate": 2.229390555164488e-06, + "loss": 0.7779, + "step": 4103 + }, + { + "epoch": 0.79, + "learning_rate": 2.225467878089549e-06, + "loss": 0.8051, + "step": 4104 + }, + { + "epoch": 0.79, + "learning_rate": 2.2215482229507145e-06, + "loss": 0.7832, + "step": 4105 + }, + { + "epoch": 0.79, + "learning_rate": 2.217631591271535e-06, + "loss": 0.803, + "step": 4106 + }, + { + "epoch": 0.79, + "learning_rate": 2.2137179845743986e-06, + "loss": 0.7715, + "step": 4107 + }, + { + "epoch": 0.79, + "learning_rate": 2.2098074043805094e-06, + "loss": 0.8064, + "step": 4108 + }, + { + "epoch": 0.79, + "learning_rate": 2.205899852209895e-06, + "loss": 0.7473, + "step": 4109 + }, + { + "epoch": 0.79, + "learning_rate": 2.2019953295814146e-06, + "loss": 0.7468, + "step": 4110 + }, + { + "epoch": 0.79, + "learning_rate": 2.1980938380127394e-06, + "loss": 0.7713, + "step": 4111 + }, + { + "epoch": 0.79, + "learning_rate": 2.1941953790203686e-06, + "loss": 0.772, + "step": 4112 + }, + { + "epoch": 0.79, + "learning_rate": 2.19029995411962e-06, + "loss": 0.7275, + "step": 4113 + }, + { + "epoch": 0.79, + "learning_rate": 2.1864075648246296e-06, + "loss": 0.7303, + "step": 4114 + }, + { + "epoch": 0.79, + "learning_rate": 2.1825182126483646e-06, + "loss": 0.8494, + "step": 4115 + }, + { + "epoch": 0.79, + "learning_rate": 2.1786318991025956e-06, + "loss": 0.8386, + "step": 4116 + }, + { + "epoch": 0.79, + "learning_rate": 2.174748625697928e-06, + "loss": 0.697, + "step": 4117 + }, + { + "epoch": 0.79, + "learning_rate": 2.1708683939437745e-06, + "loss": 0.7129, + "step": 4118 + }, + { + "epoch": 0.79, + "learning_rate": 2.166991205348369e-06, + "loss": 0.7632, + "step": 4119 + }, + { + "epoch": 0.79, + "learning_rate": 2.1631170614187613e-06, + "loss": 0.706, + "step": 4120 + }, + { + "epoch": 0.79, + "learning_rate": 2.1592459636608187e-06, + "loss": 0.7304, + "step": 4121 + }, + { + "epoch": 0.79, + "learning_rate": 2.1553779135792274e-06, + "loss": 0.7582, + "step": 4122 + }, + { + "epoch": 0.79, + "learning_rate": 2.1515129126774856e-06, + "loss": 0.7418, + "step": 4123 + }, + { + "epoch": 0.79, + "learning_rate": 2.1476509624579035e-06, + "loss": 0.7345, + "step": 4124 + }, + { + "epoch": 0.79, + "learning_rate": 2.1437920644216138e-06, + "loss": 0.7348, + "step": 4125 + }, + { + "epoch": 0.79, + "learning_rate": 2.1399362200685535e-06, + "loss": 0.696, + "step": 4126 + }, + { + "epoch": 0.79, + "learning_rate": 2.1360834308974822e-06, + "loss": 0.7189, + "step": 4127 + }, + { + "epoch": 0.79, + "learning_rate": 2.132233698405963e-06, + "loss": 0.7379, + "step": 4128 + }, + { + "epoch": 0.79, + "learning_rate": 2.128387024090377e-06, + "loss": 0.7461, + "step": 4129 + }, + { + "epoch": 0.79, + "learning_rate": 2.1245434094459137e-06, + "loss": 0.7608, + "step": 4130 + }, + { + "epoch": 0.8, + "learning_rate": 2.12070285596657e-06, + "loss": 0.7706, + "step": 4131 + }, + { + "epoch": 0.8, + "learning_rate": 2.1168653651451633e-06, + "loss": 1.1693, + "step": 4132 + }, + { + "epoch": 0.8, + "learning_rate": 2.1130309384733116e-06, + "loss": 0.8052, + "step": 4133 + }, + { + "epoch": 0.8, + "learning_rate": 2.109199577441441e-06, + "loss": 0.783, + "step": 4134 + }, + { + "epoch": 0.8, + "learning_rate": 2.1053712835387963e-06, + "loss": 0.8266, + "step": 4135 + }, + { + "epoch": 0.8, + "learning_rate": 2.101546058253419e-06, + "loss": 0.7965, + "step": 4136 + }, + { + "epoch": 0.8, + "learning_rate": 2.097723903072162e-06, + "loss": 0.7499, + "step": 4137 + }, + { + "epoch": 0.8, + "learning_rate": 2.0939048194806833e-06, + "loss": 0.7818, + "step": 4138 + }, + { + "epoch": 0.8, + "learning_rate": 2.090088808963454e-06, + "loss": 0.7977, + "step": 4139 + }, + { + "epoch": 0.8, + "learning_rate": 2.0862758730037425e-06, + "loss": 0.6959, + "step": 4140 + }, + { + "epoch": 0.8, + "learning_rate": 2.0824660130836215e-06, + "loss": 1.1799, + "step": 4141 + }, + { + "epoch": 0.8, + "learning_rate": 2.078659230683978e-06, + "loss": 0.7175, + "step": 4142 + }, + { + "epoch": 0.8, + "learning_rate": 2.0748555272844904e-06, + "loss": 0.7767, + "step": 4143 + }, + { + "epoch": 0.8, + "learning_rate": 2.071054904363652e-06, + "loss": 0.7983, + "step": 4144 + }, + { + "epoch": 0.8, + "learning_rate": 2.0672573633987493e-06, + "loss": 0.8174, + "step": 4145 + }, + { + "epoch": 0.8, + "learning_rate": 2.063462905865875e-06, + "loss": 0.6972, + "step": 4146 + }, + { + "epoch": 0.8, + "learning_rate": 2.059671533239924e-06, + "loss": 0.7484, + "step": 4147 + }, + { + "epoch": 0.8, + "learning_rate": 2.0558832469945853e-06, + "loss": 0.7582, + "step": 4148 + }, + { + "epoch": 0.8, + "learning_rate": 2.0520980486023623e-06, + "loss": 0.7655, + "step": 4149 + }, + { + "epoch": 0.8, + "learning_rate": 2.0483159395345454e-06, + "loss": 0.7791, + "step": 4150 + }, + { + "epoch": 0.8, + "learning_rate": 2.0445369212612255e-06, + "loss": 0.7414, + "step": 4151 + }, + { + "epoch": 0.8, + "learning_rate": 2.0407609952513008e-06, + "loss": 0.7668, + "step": 4152 + }, + { + "epoch": 0.8, + "learning_rate": 2.036988162972459e-06, + "loss": 0.8031, + "step": 4153 + }, + { + "epoch": 0.8, + "learning_rate": 2.0332184258911893e-06, + "loss": 0.751, + "step": 4154 + }, + { + "epoch": 0.8, + "learning_rate": 2.0294517854727724e-06, + "loss": 0.7332, + "step": 4155 + }, + { + "epoch": 0.8, + "learning_rate": 2.0256882431812953e-06, + "loss": 0.742, + "step": 4156 + }, + { + "epoch": 0.8, + "learning_rate": 2.021927800479633e-06, + "loss": 0.8245, + "step": 4157 + }, + { + "epoch": 0.8, + "learning_rate": 2.018170458829454e-06, + "loss": 0.7538, + "step": 4158 + }, + { + "epoch": 0.8, + "learning_rate": 2.0144162196912308e-06, + "loss": 0.792, + "step": 4159 + }, + { + "epoch": 0.8, + "learning_rate": 2.0106650845242224e-06, + "loss": 0.7403, + "step": 4160 + }, + { + "epoch": 0.8, + "learning_rate": 2.0069170547864803e-06, + "loss": 0.7098, + "step": 4161 + }, + { + "epoch": 0.8, + "learning_rate": 2.0031721319348596e-06, + "loss": 0.7661, + "step": 4162 + }, + { + "epoch": 0.8, + "learning_rate": 1.9994303174249887e-06, + "loss": 0.7877, + "step": 4163 + }, + { + "epoch": 0.8, + "learning_rate": 1.995691612711308e-06, + "loss": 0.7428, + "step": 4164 + }, + { + "epoch": 0.8, + "learning_rate": 1.9919560192470346e-06, + "loss": 0.7383, + "step": 4165 + }, + { + "epoch": 0.8, + "learning_rate": 1.9882235384841864e-06, + "loss": 0.7764, + "step": 4166 + }, + { + "epoch": 0.8, + "learning_rate": 1.9844941718735653e-06, + "loss": 0.7643, + "step": 4167 + }, + { + "epoch": 0.8, + "learning_rate": 1.9807679208647625e-06, + "loss": 0.7959, + "step": 4168 + }, + { + "epoch": 0.8, + "learning_rate": 1.9770447869061625e-06, + "loss": 1.2125, + "step": 4169 + }, + { + "epoch": 0.8, + "learning_rate": 1.9733247714449354e-06, + "loss": 0.8095, + "step": 4170 + }, + { + "epoch": 0.8, + "learning_rate": 1.9696078759270386e-06, + "loss": 0.724, + "step": 4171 + }, + { + "epoch": 0.8, + "learning_rate": 1.9658941017972187e-06, + "loss": 0.8154, + "step": 4172 + }, + { + "epoch": 0.8, + "learning_rate": 1.9621834504990044e-06, + "loss": 0.7682, + "step": 4173 + }, + { + "epoch": 0.8, + "learning_rate": 1.9584759234747187e-06, + "loss": 0.7696, + "step": 4174 + }, + { + "epoch": 0.8, + "learning_rate": 1.9547715221654617e-06, + "loss": 0.8234, + "step": 4175 + }, + { + "epoch": 0.8, + "learning_rate": 1.951070248011128e-06, + "loss": 0.7091, + "step": 4176 + }, + { + "epoch": 0.8, + "learning_rate": 1.9473721024503865e-06, + "loss": 0.7834, + "step": 4177 + }, + { + "epoch": 0.8, + "learning_rate": 1.943677086920698e-06, + "loss": 0.7356, + "step": 4178 + }, + { + "epoch": 0.8, + "learning_rate": 1.9399852028583e-06, + "loss": 0.7115, + "step": 4179 + }, + { + "epoch": 0.8, + "learning_rate": 1.9362964516982143e-06, + "loss": 0.7398, + "step": 4180 + }, + { + "epoch": 0.8, + "learning_rate": 1.9326108348742545e-06, + "loss": 1.2088, + "step": 4181 + }, + { + "epoch": 0.81, + "learning_rate": 1.928928353819003e-06, + "loss": 0.7729, + "step": 4182 + }, + { + "epoch": 0.81, + "learning_rate": 1.9252490099638265e-06, + "loss": 0.723, + "step": 4183 + }, + { + "epoch": 0.81, + "learning_rate": 1.9215728047388804e-06, + "loss": 0.7785, + "step": 4184 + }, + { + "epoch": 0.81, + "learning_rate": 1.917899739573088e-06, + "loss": 0.8018, + "step": 4185 + }, + { + "epoch": 0.81, + "learning_rate": 1.914229815894164e-06, + "loss": 0.7813, + "step": 4186 + }, + { + "epoch": 0.81, + "learning_rate": 1.910563035128593e-06, + "loss": 0.786, + "step": 4187 + }, + { + "epoch": 0.81, + "learning_rate": 1.9068993987016415e-06, + "loss": 0.7803, + "step": 4188 + }, + { + "epoch": 0.81, + "learning_rate": 1.9032389080373537e-06, + "loss": 0.7771, + "step": 4189 + }, + { + "epoch": 0.81, + "learning_rate": 1.899581564558548e-06, + "loss": 0.7189, + "step": 4190 + }, + { + "epoch": 0.81, + "learning_rate": 1.8959273696868264e-06, + "loss": 0.7228, + "step": 4191 + }, + { + "epoch": 0.81, + "learning_rate": 1.892276324842558e-06, + "loss": 0.7754, + "step": 4192 + }, + { + "epoch": 0.81, + "learning_rate": 1.8886284314449e-06, + "loss": 0.827, + "step": 4193 + }, + { + "epoch": 0.81, + "learning_rate": 1.8849836909117713e-06, + "loss": 0.763, + "step": 4194 + }, + { + "epoch": 0.81, + "learning_rate": 1.8813421046598723e-06, + "loss": 0.8162, + "step": 4195 + }, + { + "epoch": 0.81, + "learning_rate": 1.8777036741046761e-06, + "loss": 0.7067, + "step": 4196 + }, + { + "epoch": 0.81, + "learning_rate": 1.874068400660427e-06, + "loss": 0.7933, + "step": 4197 + }, + { + "epoch": 0.81, + "learning_rate": 1.8704362857401492e-06, + "loss": 0.7951, + "step": 4198 + }, + { + "epoch": 0.81, + "learning_rate": 1.866807330755631e-06, + "loss": 0.781, + "step": 4199 + }, + { + "epoch": 0.81, + "learning_rate": 1.8631815371174344e-06, + "loss": 0.785, + "step": 4200 + }, + { + "epoch": 0.81, + "learning_rate": 1.8595589062348985e-06, + "loss": 0.7712, + "step": 4201 + }, + { + "epoch": 0.81, + "learning_rate": 1.8559394395161223e-06, + "loss": 0.7723, + "step": 4202 + }, + { + "epoch": 0.81, + "learning_rate": 1.8523231383679885e-06, + "loss": 0.7592, + "step": 4203 + }, + { + "epoch": 0.81, + "learning_rate": 1.8487100041961382e-06, + "loss": 0.784, + "step": 4204 + }, + { + "epoch": 0.81, + "learning_rate": 1.8451000384049845e-06, + "loss": 0.8096, + "step": 4205 + }, + { + "epoch": 0.81, + "learning_rate": 1.8414932423977105e-06, + "loss": 0.7743, + "step": 4206 + }, + { + "epoch": 0.81, + "learning_rate": 1.837889617576264e-06, + "loss": 0.75, + "step": 4207 + }, + { + "epoch": 0.81, + "learning_rate": 1.8342891653413676e-06, + "loss": 0.7579, + "step": 4208 + }, + { + "epoch": 0.81, + "learning_rate": 1.8306918870925028e-06, + "loss": 0.7385, + "step": 4209 + }, + { + "epoch": 0.81, + "learning_rate": 1.827097784227917e-06, + "loss": 0.763, + "step": 4210 + }, + { + "epoch": 0.81, + "learning_rate": 1.8235068581446348e-06, + "loss": 0.7595, + "step": 4211 + }, + { + "epoch": 0.81, + "learning_rate": 1.8199191102384317e-06, + "loss": 0.7465, + "step": 4212 + }, + { + "epoch": 0.81, + "learning_rate": 1.8163345419038559e-06, + "loss": 0.801, + "step": 4213 + }, + { + "epoch": 0.81, + "learning_rate": 1.8127531545342147e-06, + "loss": 0.7562, + "step": 4214 + }, + { + "epoch": 0.81, + "learning_rate": 1.809174949521587e-06, + "loss": 0.759, + "step": 4215 + }, + { + "epoch": 0.81, + "learning_rate": 1.8055999282568092e-06, + "loss": 0.7798, + "step": 4216 + }, + { + "epoch": 0.81, + "learning_rate": 1.8020280921294752e-06, + "loss": 0.7762, + "step": 4217 + }, + { + "epoch": 0.81, + "learning_rate": 1.7984594425279534e-06, + "loss": 0.7141, + "step": 4218 + }, + { + "epoch": 0.81, + "learning_rate": 1.7948939808393628e-06, + "loss": 0.818, + "step": 4219 + }, + { + "epoch": 0.81, + "learning_rate": 1.7913317084495862e-06, + "loss": 0.747, + "step": 4220 + }, + { + "epoch": 0.81, + "learning_rate": 1.7877726267432749e-06, + "loss": 1.1651, + "step": 4221 + }, + { + "epoch": 0.81, + "learning_rate": 1.784216737103821e-06, + "loss": 0.7747, + "step": 4222 + }, + { + "epoch": 0.81, + "learning_rate": 1.7806640409133969e-06, + "loss": 0.6959, + "step": 4223 + }, + { + "epoch": 0.81, + "learning_rate": 1.7771145395529188e-06, + "loss": 1.1366, + "step": 4224 + }, + { + "epoch": 0.81, + "learning_rate": 1.7735682344020722e-06, + "loss": 0.7501, + "step": 4225 + }, + { + "epoch": 0.81, + "learning_rate": 1.770025126839291e-06, + "loss": 0.7161, + "step": 4226 + }, + { + "epoch": 0.81, + "learning_rate": 1.766485218241768e-06, + "loss": 0.7524, + "step": 4227 + }, + { + "epoch": 0.81, + "learning_rate": 1.7629485099854604e-06, + "loss": 0.7233, + "step": 4228 + }, + { + "epoch": 0.81, + "learning_rate": 1.7594150034450709e-06, + "loss": 0.8027, + "step": 4229 + }, + { + "epoch": 0.81, + "learning_rate": 1.7558846999940648e-06, + "loss": 0.7496, + "step": 4230 + }, + { + "epoch": 0.81, + "learning_rate": 1.7523576010046585e-06, + "loss": 0.7694, + "step": 4231 + }, + { + "epoch": 0.81, + "learning_rate": 1.7488337078478212e-06, + "loss": 0.7784, + "step": 4232 + }, + { + "epoch": 0.81, + "learning_rate": 1.7453130218932858e-06, + "loss": 0.7786, + "step": 4233 + }, + { + "epoch": 0.82, + "learning_rate": 1.7417955445095258e-06, + "loss": 0.7795, + "step": 4234 + }, + { + "epoch": 0.82, + "learning_rate": 1.7382812770637791e-06, + "loss": 0.7721, + "step": 4235 + }, + { + "epoch": 0.82, + "learning_rate": 1.7347702209220264e-06, + "loss": 0.7209, + "step": 4236 + }, + { + "epoch": 0.82, + "learning_rate": 1.7312623774490057e-06, + "loss": 0.7568, + "step": 4237 + }, + { + "epoch": 0.82, + "learning_rate": 1.7277577480082042e-06, + "loss": 1.1669, + "step": 4238 + }, + { + "epoch": 0.82, + "learning_rate": 1.7242563339618578e-06, + "loss": 0.8169, + "step": 4239 + }, + { + "epoch": 0.82, + "learning_rate": 1.7207581366709603e-06, + "loss": 0.7435, + "step": 4240 + }, + { + "epoch": 0.82, + "learning_rate": 1.7172631574952448e-06, + "loss": 0.7282, + "step": 4241 + }, + { + "epoch": 0.82, + "learning_rate": 1.7137713977932024e-06, + "loss": 0.7334, + "step": 4242 + }, + { + "epoch": 0.82, + "learning_rate": 1.7102828589220689e-06, + "loss": 0.8034, + "step": 4243 + }, + { + "epoch": 0.82, + "learning_rate": 1.7067975422378247e-06, + "loss": 0.7057, + "step": 4244 + }, + { + "epoch": 0.82, + "learning_rate": 1.7033154490952064e-06, + "loss": 0.6886, + "step": 4245 + }, + { + "epoch": 0.82, + "learning_rate": 1.6998365808476891e-06, + "loss": 0.7539, + "step": 4246 + }, + { + "epoch": 0.82, + "learning_rate": 1.6963609388475e-06, + "loss": 0.7731, + "step": 4247 + }, + { + "epoch": 0.82, + "learning_rate": 1.6928885244456084e-06, + "loss": 0.7239, + "step": 4248 + }, + { + "epoch": 0.82, + "learning_rate": 1.689419338991729e-06, + "loss": 0.777, + "step": 4249 + }, + { + "epoch": 0.82, + "learning_rate": 1.685953383834329e-06, + "loss": 0.7917, + "step": 4250 + }, + { + "epoch": 0.82, + "learning_rate": 1.682490660320608e-06, + "loss": 1.1064, + "step": 4251 + }, + { + "epoch": 0.82, + "learning_rate": 1.6790311697965212e-06, + "loss": 0.7321, + "step": 4252 + }, + { + "epoch": 0.82, + "learning_rate": 1.675574913606759e-06, + "loss": 0.7212, + "step": 4253 + }, + { + "epoch": 0.82, + "learning_rate": 1.672121893094758e-06, + "loss": 0.7969, + "step": 4254 + }, + { + "epoch": 0.82, + "learning_rate": 1.6686721096026959e-06, + "loss": 0.6972, + "step": 4255 + }, + { + "epoch": 0.82, + "learning_rate": 1.6652255644714888e-06, + "loss": 0.7476, + "step": 4256 + }, + { + "epoch": 0.82, + "learning_rate": 1.661782259040805e-06, + "loss": 0.7291, + "step": 4257 + }, + { + "epoch": 0.82, + "learning_rate": 1.658342194649043e-06, + "loss": 1.158, + "step": 4258 + }, + { + "epoch": 0.82, + "learning_rate": 1.654905372633343e-06, + "loss": 1.2205, + "step": 4259 + }, + { + "epoch": 0.82, + "learning_rate": 1.651471794329591e-06, + "loss": 0.697, + "step": 4260 + }, + { + "epoch": 0.82, + "learning_rate": 1.6480414610724038e-06, + "loss": 0.745, + "step": 4261 + }, + { + "epoch": 0.82, + "learning_rate": 1.644614374195146e-06, + "loss": 0.7669, + "step": 4262 + }, + { + "epoch": 0.82, + "learning_rate": 1.6411905350299118e-06, + "loss": 0.8075, + "step": 4263 + }, + { + "epoch": 0.82, + "learning_rate": 1.637769944907539e-06, + "loss": 0.754, + "step": 4264 + }, + { + "epoch": 0.82, + "learning_rate": 1.6343526051575976e-06, + "loss": 0.8274, + "step": 4265 + }, + { + "epoch": 0.82, + "learning_rate": 1.630938517108397e-06, + "loss": 0.7374, + "step": 4266 + }, + { + "epoch": 0.82, + "learning_rate": 1.6275276820869845e-06, + "loss": 0.7227, + "step": 4267 + }, + { + "epoch": 0.82, + "learning_rate": 1.6241201014191399e-06, + "loss": 0.8375, + "step": 4268 + }, + { + "epoch": 0.82, + "learning_rate": 1.620715776429378e-06, + "loss": 0.7446, + "step": 4269 + }, + { + "epoch": 0.82, + "learning_rate": 1.6173147084409513e-06, + "loss": 0.727, + "step": 4270 + }, + { + "epoch": 0.82, + "learning_rate": 1.6139168987758437e-06, + "loss": 0.7956, + "step": 4271 + }, + { + "epoch": 0.82, + "learning_rate": 1.6105223487547727e-06, + "loss": 0.7856, + "step": 4272 + }, + { + "epoch": 0.82, + "learning_rate": 1.6071310596971856e-06, + "loss": 0.736, + "step": 4273 + }, + { + "epoch": 0.82, + "learning_rate": 1.6037430329212722e-06, + "loss": 0.7586, + "step": 4274 + }, + { + "epoch": 0.82, + "learning_rate": 1.6003582697439447e-06, + "loss": 0.7571, + "step": 4275 + }, + { + "epoch": 0.82, + "learning_rate": 1.5969767714808481e-06, + "loss": 0.7461, + "step": 4276 + }, + { + "epoch": 0.82, + "learning_rate": 1.5935985394463637e-06, + "loss": 0.7967, + "step": 4277 + }, + { + "epoch": 0.82, + "learning_rate": 1.5902235749535977e-06, + "loss": 0.8176, + "step": 4278 + }, + { + "epoch": 0.82, + "learning_rate": 1.586851879314386e-06, + "loss": 0.7909, + "step": 4279 + }, + { + "epoch": 0.82, + "learning_rate": 1.5834834538393029e-06, + "loss": 0.8185, + "step": 4280 + }, + { + "epoch": 0.82, + "learning_rate": 1.5801182998376363e-06, + "loss": 0.7672, + "step": 4281 + }, + { + "epoch": 0.82, + "learning_rate": 1.5767564186174167e-06, + "loss": 0.7617, + "step": 4282 + }, + { + "epoch": 0.82, + "learning_rate": 1.573397811485392e-06, + "loss": 0.7495, + "step": 4283 + }, + { + "epoch": 0.82, + "learning_rate": 1.5700424797470482e-06, + "loss": 0.7221, + "step": 4284 + }, + { + "epoch": 0.82, + "learning_rate": 1.5666904247065885e-06, + "loss": 0.7233, + "step": 4285 + }, + { + "epoch": 0.83, + "learning_rate": 1.563341647666945e-06, + "loss": 0.7206, + "step": 4286 + }, + { + "epoch": 0.83, + "learning_rate": 1.55999614992978e-06, + "loss": 0.7307, + "step": 4287 + }, + { + "epoch": 0.83, + "learning_rate": 1.5566539327954766e-06, + "loss": 0.7443, + "step": 4288 + }, + { + "epoch": 0.83, + "learning_rate": 1.5533149975631445e-06, + "loss": 0.7909, + "step": 4289 + }, + { + "epoch": 0.83, + "learning_rate": 1.5499793455306133e-06, + "loss": 0.8103, + "step": 4290 + }, + { + "epoch": 0.83, + "learning_rate": 1.5466469779944459e-06, + "loss": 0.7773, + "step": 4291 + }, + { + "epoch": 0.83, + "learning_rate": 1.5433178962499207e-06, + "loss": 0.7647, + "step": 4292 + }, + { + "epoch": 0.83, + "learning_rate": 1.5399921015910402e-06, + "loss": 0.7596, + "step": 4293 + }, + { + "epoch": 0.83, + "learning_rate": 1.5366695953105326e-06, + "loss": 0.7778, + "step": 4294 + }, + { + "epoch": 0.83, + "learning_rate": 1.5333503786998449e-06, + "loss": 0.7797, + "step": 4295 + }, + { + "epoch": 0.83, + "learning_rate": 1.5300344530491428e-06, + "loss": 0.7874, + "step": 4296 + }, + { + "epoch": 0.83, + "learning_rate": 1.5267218196473254e-06, + "loss": 0.7831, + "step": 4297 + }, + { + "epoch": 0.83, + "learning_rate": 1.5234124797819905e-06, + "loss": 0.7554, + "step": 4298 + }, + { + "epoch": 0.83, + "learning_rate": 1.5201064347394768e-06, + "loss": 0.7508, + "step": 4299 + }, + { + "epoch": 0.83, + "learning_rate": 1.5168036858048274e-06, + "loss": 0.764, + "step": 4300 + }, + { + "epoch": 0.83, + "learning_rate": 1.5135042342618178e-06, + "loss": 0.7583, + "step": 4301 + }, + { + "epoch": 0.83, + "learning_rate": 1.5102080813929298e-06, + "loss": 0.7656, + "step": 4302 + }, + { + "epoch": 0.83, + "learning_rate": 1.5069152284793653e-06, + "loss": 0.7693, + "step": 4303 + }, + { + "epoch": 0.83, + "learning_rate": 1.5036256768010516e-06, + "loss": 0.7772, + "step": 4304 + }, + { + "epoch": 0.83, + "learning_rate": 1.5003394276366245e-06, + "loss": 0.7493, + "step": 4305 + }, + { + "epoch": 0.83, + "learning_rate": 1.4970564822634382e-06, + "loss": 0.775, + "step": 4306 + }, + { + "epoch": 0.83, + "learning_rate": 1.4937768419575626e-06, + "loss": 0.7958, + "step": 4307 + }, + { + "epoch": 0.83, + "learning_rate": 1.4905005079937829e-06, + "loss": 0.7744, + "step": 4308 + }, + { + "epoch": 0.83, + "learning_rate": 1.4872274816456034e-06, + "loss": 0.7577, + "step": 4309 + }, + { + "epoch": 0.83, + "learning_rate": 1.4839577641852342e-06, + "loss": 0.7954, + "step": 4310 + }, + { + "epoch": 0.83, + "learning_rate": 1.48069135688361e-06, + "loss": 0.7297, + "step": 4311 + }, + { + "epoch": 0.83, + "learning_rate": 1.4774282610103695e-06, + "loss": 0.7431, + "step": 4312 + }, + { + "epoch": 0.83, + "learning_rate": 1.4741684778338672e-06, + "loss": 0.7869, + "step": 4313 + }, + { + "epoch": 0.83, + "learning_rate": 1.4709120086211726e-06, + "loss": 0.8037, + "step": 4314 + }, + { + "epoch": 0.83, + "learning_rate": 1.467658854638062e-06, + "loss": 0.7895, + "step": 4315 + }, + { + "epoch": 0.83, + "learning_rate": 1.4644090171490298e-06, + "loss": 0.7474, + "step": 4316 + }, + { + "epoch": 0.83, + "learning_rate": 1.4611624974172756e-06, + "loss": 0.7732, + "step": 4317 + }, + { + "epoch": 0.83, + "learning_rate": 1.4579192967047085e-06, + "loss": 0.8465, + "step": 4318 + }, + { + "epoch": 0.83, + "learning_rate": 1.4546794162719568e-06, + "loss": 0.7058, + "step": 4319 + }, + { + "epoch": 0.83, + "learning_rate": 1.4514428573783456e-06, + "loss": 0.7829, + "step": 4320 + }, + { + "epoch": 0.83, + "learning_rate": 1.4482096212819208e-06, + "loss": 0.7101, + "step": 4321 + }, + { + "epoch": 0.83, + "learning_rate": 1.444979709239428e-06, + "loss": 0.7683, + "step": 4322 + }, + { + "epoch": 0.83, + "learning_rate": 1.4417531225063242e-06, + "loss": 0.7438, + "step": 4323 + }, + { + "epoch": 0.83, + "learning_rate": 1.4385298623367727e-06, + "loss": 0.8318, + "step": 4324 + }, + { + "epoch": 0.83, + "learning_rate": 1.4353099299836437e-06, + "loss": 0.7563, + "step": 4325 + }, + { + "epoch": 0.83, + "learning_rate": 1.4320933266985182e-06, + "loss": 0.7113, + "step": 4326 + }, + { + "epoch": 0.83, + "learning_rate": 1.4288800537316772e-06, + "loss": 0.8123, + "step": 4327 + }, + { + "epoch": 0.83, + "learning_rate": 1.4256701123321082e-06, + "loss": 0.7616, + "step": 4328 + }, + { + "epoch": 0.83, + "learning_rate": 1.42246350374751e-06, + "loss": 0.7565, + "step": 4329 + }, + { + "epoch": 0.83, + "learning_rate": 1.4192602292242786e-06, + "loss": 0.7498, + "step": 4330 + }, + { + "epoch": 0.83, + "learning_rate": 1.416060290007517e-06, + "loss": 0.7557, + "step": 4331 + }, + { + "epoch": 0.83, + "learning_rate": 1.4128636873410283e-06, + "loss": 0.7683, + "step": 4332 + }, + { + "epoch": 0.83, + "learning_rate": 1.4096704224673285e-06, + "loss": 0.7659, + "step": 4333 + }, + { + "epoch": 0.83, + "learning_rate": 1.4064804966276247e-06, + "loss": 0.7466, + "step": 4334 + }, + { + "epoch": 0.83, + "learning_rate": 1.4032939110618294e-06, + "loss": 0.7758, + "step": 4335 + }, + { + "epoch": 0.83, + "learning_rate": 1.400110667008564e-06, + "loss": 0.7854, + "step": 4336 + }, + { + "epoch": 0.83, + "learning_rate": 1.3969307657051412e-06, + "loss": 0.7504, + "step": 4337 + }, + { + "epoch": 0.84, + "learning_rate": 1.3937542083875811e-06, + "loss": 0.7996, + "step": 4338 + }, + { + "epoch": 0.84, + "learning_rate": 1.3905809962906002e-06, + "loss": 0.7713, + "step": 4339 + }, + { + "epoch": 0.84, + "learning_rate": 1.3874111306476168e-06, + "loss": 0.7833, + "step": 4340 + }, + { + "epoch": 0.84, + "learning_rate": 1.3842446126907472e-06, + "loss": 0.7829, + "step": 4341 + }, + { + "epoch": 0.84, + "learning_rate": 1.3810814436508046e-06, + "loss": 0.8074, + "step": 4342 + }, + { + "epoch": 0.84, + "learning_rate": 1.3779216247573068e-06, + "loss": 0.8084, + "step": 4343 + }, + { + "epoch": 0.84, + "learning_rate": 1.3747651572384636e-06, + "loss": 0.8085, + "step": 4344 + }, + { + "epoch": 0.84, + "learning_rate": 1.371612042321182e-06, + "loss": 0.7424, + "step": 4345 + }, + { + "epoch": 0.84, + "learning_rate": 1.3684622812310723e-06, + "loss": 0.7949, + "step": 4346 + }, + { + "epoch": 0.84, + "learning_rate": 1.3653158751924334e-06, + "loss": 0.7521, + "step": 4347 + }, + { + "epoch": 0.84, + "learning_rate": 1.3621728254282652e-06, + "loss": 0.7842, + "step": 4348 + }, + { + "epoch": 0.84, + "learning_rate": 1.3590331331602568e-06, + "loss": 0.7513, + "step": 4349 + }, + { + "epoch": 0.84, + "learning_rate": 1.3558967996088034e-06, + "loss": 0.7677, + "step": 4350 + }, + { + "epoch": 0.84, + "learning_rate": 1.3527638259929843e-06, + "loss": 0.7938, + "step": 4351 + }, + { + "epoch": 0.84, + "learning_rate": 1.3496342135305752e-06, + "loss": 0.7119, + "step": 4352 + }, + { + "epoch": 0.84, + "learning_rate": 1.3465079634380496e-06, + "loss": 0.7645, + "step": 4353 + }, + { + "epoch": 0.84, + "learning_rate": 1.34338507693057e-06, + "loss": 0.7676, + "step": 4354 + }, + { + "epoch": 0.84, + "learning_rate": 1.3402655552219902e-06, + "loss": 0.7324, + "step": 4355 + }, + { + "epoch": 0.84, + "learning_rate": 1.3371493995248642e-06, + "loss": 0.7595, + "step": 4356 + }, + { + "epoch": 0.84, + "learning_rate": 1.3340366110504243e-06, + "loss": 0.7257, + "step": 4357 + }, + { + "epoch": 0.84, + "learning_rate": 1.3309271910086074e-06, + "loss": 0.7587, + "step": 4358 + }, + { + "epoch": 0.84, + "learning_rate": 1.327821140608031e-06, + "loss": 0.8, + "step": 4359 + }, + { + "epoch": 0.84, + "learning_rate": 1.3247184610560115e-06, + "loss": 0.7929, + "step": 4360 + }, + { + "epoch": 0.84, + "learning_rate": 1.3216191535585487e-06, + "loss": 0.7163, + "step": 4361 + }, + { + "epoch": 0.84, + "learning_rate": 1.3185232193203311e-06, + "loss": 1.1385, + "step": 4362 + }, + { + "epoch": 0.84, + "learning_rate": 1.3154306595447441e-06, + "loss": 0.7905, + "step": 4363 + }, + { + "epoch": 0.84, + "learning_rate": 1.3123414754338515e-06, + "loss": 0.809, + "step": 4364 + }, + { + "epoch": 0.84, + "learning_rate": 1.3092556681884106e-06, + "loss": 0.74, + "step": 4365 + }, + { + "epoch": 0.84, + "learning_rate": 1.3061732390078652e-06, + "loss": 0.8002, + "step": 4366 + }, + { + "epoch": 0.84, + "learning_rate": 1.3030941890903437e-06, + "loss": 0.782, + "step": 4367 + }, + { + "epoch": 0.84, + "learning_rate": 1.3000185196326665e-06, + "loss": 0.7173, + "step": 4368 + }, + { + "epoch": 0.84, + "learning_rate": 1.2969462318303338e-06, + "loss": 0.805, + "step": 4369 + }, + { + "epoch": 0.84, + "learning_rate": 1.2938773268775373e-06, + "loss": 0.7501, + "step": 4370 + }, + { + "epoch": 0.84, + "learning_rate": 1.290811805967148e-06, + "loss": 0.7668, + "step": 4371 + }, + { + "epoch": 0.84, + "learning_rate": 1.2877496702907232e-06, + "loss": 0.7077, + "step": 4372 + }, + { + "epoch": 0.84, + "learning_rate": 1.2846909210385116e-06, + "loss": 0.7661, + "step": 4373 + }, + { + "epoch": 0.84, + "learning_rate": 1.2816355593994312e-06, + "loss": 0.7427, + "step": 4374 + }, + { + "epoch": 0.84, + "learning_rate": 1.2785835865610974e-06, + "loss": 0.7742, + "step": 4375 + }, + { + "epoch": 0.84, + "learning_rate": 1.2755350037097991e-06, + "loss": 0.8013, + "step": 4376 + }, + { + "epoch": 0.84, + "learning_rate": 1.2724898120305107e-06, + "loss": 0.7678, + "step": 4377 + }, + { + "epoch": 0.84, + "learning_rate": 1.269448012706892e-06, + "loss": 0.7956, + "step": 4378 + }, + { + "epoch": 0.84, + "learning_rate": 1.2664096069212762e-06, + "loss": 0.7323, + "step": 4379 + }, + { + "epoch": 0.84, + "learning_rate": 1.2633745958546862e-06, + "loss": 0.7753, + "step": 4380 + }, + { + "epoch": 0.84, + "learning_rate": 1.2603429806868206e-06, + "loss": 0.7454, + "step": 4381 + }, + { + "epoch": 0.84, + "learning_rate": 1.2573147625960569e-06, + "loss": 0.8148, + "step": 4382 + }, + { + "epoch": 0.84, + "learning_rate": 1.2542899427594545e-06, + "loss": 0.7909, + "step": 4383 + }, + { + "epoch": 0.84, + "learning_rate": 1.2512685223527487e-06, + "loss": 0.7919, + "step": 4384 + }, + { + "epoch": 0.84, + "learning_rate": 1.2482505025503611e-06, + "loss": 0.7648, + "step": 4385 + }, + { + "epoch": 0.84, + "learning_rate": 1.245235884525383e-06, + "loss": 0.7794, + "step": 4386 + }, + { + "epoch": 0.84, + "learning_rate": 1.2422246694495898e-06, + "loss": 0.7718, + "step": 4387 + }, + { + "epoch": 0.84, + "learning_rate": 1.2392168584934283e-06, + "loss": 0.749, + "step": 4388 + }, + { + "epoch": 0.84, + "learning_rate": 1.2362124528260278e-06, + "loss": 0.7535, + "step": 4389 + }, + { + "epoch": 0.85, + "learning_rate": 1.2332114536151895e-06, + "loss": 0.7363, + "step": 4390 + }, + { + "epoch": 0.85, + "learning_rate": 1.2302138620273907e-06, + "loss": 0.7678, + "step": 4391 + }, + { + "epoch": 0.85, + "learning_rate": 1.227219679227789e-06, + "loss": 0.8405, + "step": 4392 + }, + { + "epoch": 0.85, + "learning_rate": 1.2242289063802137e-06, + "loss": 0.7608, + "step": 4393 + }, + { + "epoch": 0.85, + "learning_rate": 1.221241544647165e-06, + "loss": 0.7368, + "step": 4394 + }, + { + "epoch": 0.85, + "learning_rate": 1.2182575951898257e-06, + "loss": 0.7547, + "step": 4395 + }, + { + "epoch": 0.85, + "learning_rate": 1.215277059168044e-06, + "loss": 0.868, + "step": 4396 + }, + { + "epoch": 0.85, + "learning_rate": 1.2122999377403478e-06, + "loss": 0.8214, + "step": 4397 + }, + { + "epoch": 0.85, + "learning_rate": 1.2093262320639333e-06, + "loss": 0.8005, + "step": 4398 + }, + { + "epoch": 0.85, + "learning_rate": 1.2063559432946715e-06, + "loss": 0.7045, + "step": 4399 + }, + { + "epoch": 0.85, + "learning_rate": 1.2033890725871022e-06, + "loss": 0.8685, + "step": 4400 + }, + { + "epoch": 0.85, + "learning_rate": 1.2004256210944377e-06, + "loss": 1.0964, + "step": 4401 + }, + { + "epoch": 0.85, + "learning_rate": 1.1974655899685671e-06, + "loss": 0.7989, + "step": 4402 + }, + { + "epoch": 0.85, + "learning_rate": 1.1945089803600419e-06, + "loss": 0.753, + "step": 4403 + }, + { + "epoch": 0.85, + "learning_rate": 1.1915557934180855e-06, + "loss": 0.7606, + "step": 4404 + }, + { + "epoch": 0.85, + "learning_rate": 1.1886060302905956e-06, + "loss": 0.7804, + "step": 4405 + }, + { + "epoch": 0.85, + "learning_rate": 1.1856596921241359e-06, + "loss": 0.7899, + "step": 4406 + }, + { + "epoch": 0.85, + "learning_rate": 1.1827167800639362e-06, + "loss": 0.7469, + "step": 4407 + }, + { + "epoch": 0.85, + "learning_rate": 1.1797772952538967e-06, + "loss": 0.6897, + "step": 4408 + }, + { + "epoch": 0.85, + "learning_rate": 1.176841238836589e-06, + "loss": 0.7825, + "step": 4409 + }, + { + "epoch": 0.85, + "learning_rate": 1.1739086119532472e-06, + "loss": 0.7578, + "step": 4410 + }, + { + "epoch": 0.85, + "learning_rate": 1.1709794157437738e-06, + "loss": 0.7736, + "step": 4411 + }, + { + "epoch": 0.85, + "learning_rate": 1.1680536513467389e-06, + "loss": 0.7445, + "step": 4412 + }, + { + "epoch": 0.85, + "learning_rate": 1.1651313198993786e-06, + "loss": 0.7601, + "step": 4413 + }, + { + "epoch": 0.85, + "learning_rate": 1.1622124225375909e-06, + "loss": 0.8155, + "step": 4414 + }, + { + "epoch": 0.85, + "learning_rate": 1.1592969603959469e-06, + "loss": 0.7956, + "step": 4415 + }, + { + "epoch": 0.85, + "learning_rate": 1.1563849346076716e-06, + "loss": 0.781, + "step": 4416 + }, + { + "epoch": 0.85, + "learning_rate": 1.1534763463046661e-06, + "loss": 0.7438, + "step": 4417 + }, + { + "epoch": 0.85, + "learning_rate": 1.1505711966174838e-06, + "loss": 0.7693, + "step": 4418 + }, + { + "epoch": 0.85, + "learning_rate": 1.1476694866753513e-06, + "loss": 0.7517, + "step": 4419 + }, + { + "epoch": 0.85, + "learning_rate": 1.1447712176061543e-06, + "loss": 0.6971, + "step": 4420 + }, + { + "epoch": 0.85, + "learning_rate": 1.141876390536436e-06, + "loss": 0.8003, + "step": 4421 + }, + { + "epoch": 0.85, + "learning_rate": 1.1389850065914133e-06, + "loss": 0.7862, + "step": 4422 + }, + { + "epoch": 0.85, + "learning_rate": 1.1360970668949534e-06, + "loss": 0.7135, + "step": 4423 + }, + { + "epoch": 0.85, + "learning_rate": 1.1332125725695918e-06, + "loss": 0.7954, + "step": 4424 + }, + { + "epoch": 0.85, + "learning_rate": 1.130331524736521e-06, + "loss": 0.7662, + "step": 4425 + }, + { + "epoch": 0.85, + "learning_rate": 1.1274539245155925e-06, + "loss": 0.8178, + "step": 4426 + }, + { + "epoch": 0.85, + "learning_rate": 1.124579773025326e-06, + "loss": 0.7961, + "step": 4427 + }, + { + "epoch": 0.85, + "learning_rate": 1.1217090713828904e-06, + "loss": 0.7904, + "step": 4428 + }, + { + "epoch": 0.85, + "learning_rate": 1.1188418207041218e-06, + "loss": 0.756, + "step": 4429 + }, + { + "epoch": 0.85, + "learning_rate": 1.1159780221035111e-06, + "loss": 0.7082, + "step": 4430 + }, + { + "epoch": 0.85, + "learning_rate": 1.1131176766942042e-06, + "loss": 0.7458, + "step": 4431 + }, + { + "epoch": 0.85, + "learning_rate": 1.1102607855880155e-06, + "loss": 0.7534, + "step": 4432 + }, + { + "epoch": 0.85, + "learning_rate": 1.1074073498953996e-06, + "loss": 0.7838, + "step": 4433 + }, + { + "epoch": 0.85, + "learning_rate": 1.1045573707254864e-06, + "loss": 0.8127, + "step": 4434 + }, + { + "epoch": 0.85, + "learning_rate": 1.1017108491860485e-06, + "loss": 0.7601, + "step": 4435 + }, + { + "epoch": 0.85, + "learning_rate": 1.098867786383524e-06, + "loss": 0.7085, + "step": 4436 + }, + { + "epoch": 0.85, + "learning_rate": 1.0960281834230002e-06, + "loss": 0.7722, + "step": 4437 + }, + { + "epoch": 0.85, + "learning_rate": 1.0931920414082197e-06, + "loss": 0.8074, + "step": 4438 + }, + { + "epoch": 0.85, + "learning_rate": 1.0903593614415875e-06, + "loss": 0.8213, + "step": 4439 + }, + { + "epoch": 0.85, + "learning_rate": 1.0875301446241536e-06, + "loss": 0.7998, + "step": 4440 + }, + { + "epoch": 0.85, + "learning_rate": 1.0847043920556266e-06, + "loss": 0.7988, + "step": 4441 + }, + { + "epoch": 0.86, + "learning_rate": 1.0818821048343665e-06, + "loss": 0.8343, + "step": 4442 + }, + { + "epoch": 0.86, + "learning_rate": 1.0790632840573867e-06, + "loss": 0.7209, + "step": 4443 + }, + { + "epoch": 0.86, + "learning_rate": 1.0762479308203567e-06, + "loss": 0.751, + "step": 4444 + }, + { + "epoch": 0.86, + "learning_rate": 1.073436046217593e-06, + "loss": 0.7193, + "step": 4445 + }, + { + "epoch": 0.86, + "learning_rate": 1.0706276313420693e-06, + "loss": 0.82, + "step": 4446 + }, + { + "epoch": 0.86, + "learning_rate": 1.0678226872854058e-06, + "loss": 0.7157, + "step": 4447 + }, + { + "epoch": 0.86, + "learning_rate": 1.0650212151378736e-06, + "loss": 0.7799, + "step": 4448 + }, + { + "epoch": 0.86, + "learning_rate": 1.0622232159884004e-06, + "loss": 0.783, + "step": 4449 + }, + { + "epoch": 0.86, + "learning_rate": 1.0594286909245543e-06, + "loss": 0.7774, + "step": 4450 + }, + { + "epoch": 0.86, + "learning_rate": 1.056637641032563e-06, + "loss": 0.7644, + "step": 4451 + }, + { + "epoch": 0.86, + "learning_rate": 1.0538500673972974e-06, + "loss": 0.7453, + "step": 4452 + }, + { + "epoch": 0.86, + "learning_rate": 1.0510659711022753e-06, + "loss": 0.7789, + "step": 4453 + }, + { + "epoch": 0.86, + "learning_rate": 1.048285353229671e-06, + "loss": 0.8127, + "step": 4454 + }, + { + "epoch": 0.86, + "learning_rate": 1.045508214860298e-06, + "loss": 0.7193, + "step": 4455 + }, + { + "epoch": 0.86, + "learning_rate": 1.0427345570736246e-06, + "loss": 0.7436, + "step": 4456 + }, + { + "epoch": 0.86, + "learning_rate": 1.0399643809477623e-06, + "loss": 0.7292, + "step": 4457 + }, + { + "epoch": 0.86, + "learning_rate": 1.037197687559467e-06, + "loss": 0.6826, + "step": 4458 + }, + { + "epoch": 0.86, + "learning_rate": 1.0344344779841475e-06, + "loss": 0.8215, + "step": 4459 + }, + { + "epoch": 0.86, + "learning_rate": 1.0316747532958493e-06, + "loss": 0.756, + "step": 4460 + }, + { + "epoch": 0.86, + "learning_rate": 1.0289185145672743e-06, + "loss": 1.1297, + "step": 4461 + }, + { + "epoch": 0.86, + "learning_rate": 1.026165762869762e-06, + "loss": 0.7722, + "step": 4462 + }, + { + "epoch": 0.86, + "learning_rate": 1.0234164992732954e-06, + "loss": 0.8167, + "step": 4463 + }, + { + "epoch": 0.86, + "learning_rate": 1.0206707248465086e-06, + "loss": 1.1845, + "step": 4464 + }, + { + "epoch": 0.86, + "learning_rate": 1.0179284406566736e-06, + "loss": 0.7551, + "step": 4465 + }, + { + "epoch": 0.86, + "learning_rate": 1.0151896477697086e-06, + "loss": 0.7157, + "step": 4466 + }, + { + "epoch": 0.86, + "learning_rate": 1.0124543472501713e-06, + "loss": 0.6979, + "step": 4467 + }, + { + "epoch": 0.86, + "learning_rate": 1.0097225401612675e-06, + "loss": 0.7708, + "step": 4468 + }, + { + "epoch": 0.86, + "learning_rate": 1.0069942275648403e-06, + "loss": 0.7571, + "step": 4469 + }, + { + "epoch": 0.86, + "learning_rate": 1.0042694105213747e-06, + "loss": 0.8047, + "step": 4470 + }, + { + "epoch": 0.86, + "learning_rate": 1.0015480900900021e-06, + "loss": 0.8037, + "step": 4471 + }, + { + "epoch": 0.86, + "learning_rate": 9.988302673284877e-07, + "loss": 0.788, + "step": 4472 + }, + { + "epoch": 0.86, + "learning_rate": 9.961159432932443e-07, + "loss": 0.8062, + "step": 4473 + }, + { + "epoch": 0.86, + "learning_rate": 9.9340511903932e-07, + "loss": 0.7699, + "step": 4474 + }, + { + "epoch": 0.86, + "learning_rate": 9.906977956204e-07, + "loss": 0.7527, + "step": 4475 + }, + { + "epoch": 0.86, + "learning_rate": 9.879939740888155e-07, + "loss": 0.7756, + "step": 4476 + }, + { + "epoch": 0.86, + "learning_rate": 9.852936554955328e-07, + "loss": 0.7755, + "step": 4477 + }, + { + "epoch": 0.86, + "learning_rate": 9.825968408901576e-07, + "loss": 0.773, + "step": 4478 + }, + { + "epoch": 0.86, + "learning_rate": 9.799035313209337e-07, + "loss": 1.1851, + "step": 4479 + }, + { + "epoch": 0.86, + "learning_rate": 9.772137278347394e-07, + "loss": 0.7206, + "step": 4480 + }, + { + "epoch": 0.86, + "learning_rate": 9.745274314770968e-07, + "loss": 0.792, + "step": 4481 + }, + { + "epoch": 0.86, + "learning_rate": 9.71844643292159e-07, + "loss": 0.7739, + "step": 4482 + }, + { + "epoch": 0.86, + "learning_rate": 9.69165364322716e-07, + "loss": 0.7835, + "step": 4483 + }, + { + "epoch": 0.86, + "learning_rate": 9.66489595610195e-07, + "loss": 0.7586, + "step": 4484 + }, + { + "epoch": 0.86, + "learning_rate": 9.638173381946626e-07, + "loss": 0.8065, + "step": 4485 + }, + { + "epoch": 0.86, + "learning_rate": 9.611485931148123e-07, + "loss": 0.7804, + "step": 4486 + }, + { + "epoch": 0.86, + "learning_rate": 9.58483361407978e-07, + "loss": 0.8061, + "step": 4487 + }, + { + "epoch": 0.86, + "learning_rate": 9.558216441101297e-07, + "loss": 0.7622, + "step": 4488 + }, + { + "epoch": 0.86, + "learning_rate": 9.531634422558656e-07, + "loss": 0.8041, + "step": 4489 + }, + { + "epoch": 0.86, + "learning_rate": 9.505087568784199e-07, + "loss": 0.8144, + "step": 4490 + }, + { + "epoch": 0.86, + "learning_rate": 9.478575890096664e-07, + "loss": 0.7413, + "step": 4491 + }, + { + "epoch": 0.86, + "learning_rate": 9.452099396800962e-07, + "loss": 0.7487, + "step": 4492 + }, + { + "epoch": 0.86, + "learning_rate": 9.425658099188484e-07, + "loss": 0.7619, + "step": 4493 + }, + { + "epoch": 0.87, + "learning_rate": 9.399252007536863e-07, + "loss": 0.7861, + "step": 4494 + }, + { + "epoch": 0.87, + "learning_rate": 9.372881132110068e-07, + "loss": 0.7508, + "step": 4495 + }, + { + "epoch": 0.87, + "learning_rate": 9.346545483158387e-07, + "loss": 0.753, + "step": 4496 + }, + { + "epoch": 0.87, + "learning_rate": 9.320245070918366e-07, + "loss": 0.7463, + "step": 4497 + }, + { + "epoch": 0.87, + "learning_rate": 9.293979905612938e-07, + "loss": 0.7698, + "step": 4498 + }, + { + "epoch": 0.87, + "learning_rate": 9.267749997451259e-07, + "loss": 0.7616, + "step": 4499 + }, + { + "epoch": 0.87, + "learning_rate": 9.241555356628828e-07, + "loss": 0.7521, + "step": 4500 + }, + { + "epoch": 0.87, + "learning_rate": 9.215395993327414e-07, + "loss": 0.7657, + "step": 4501 + }, + { + "epoch": 0.87, + "learning_rate": 9.189271917715048e-07, + "loss": 0.7622, + "step": 4502 + }, + { + "epoch": 0.87, + "learning_rate": 9.16318313994613e-07, + "loss": 0.7621, + "step": 4503 + }, + { + "epoch": 0.87, + "learning_rate": 9.137129670161238e-07, + "loss": 0.6591, + "step": 4504 + }, + { + "epoch": 0.87, + "learning_rate": 9.111111518487314e-07, + "loss": 0.7403, + "step": 4505 + }, + { + "epoch": 0.87, + "learning_rate": 9.085128695037515e-07, + "loss": 0.7654, + "step": 4506 + }, + { + "epoch": 0.87, + "learning_rate": 9.059181209911272e-07, + "loss": 0.716, + "step": 4507 + }, + { + "epoch": 0.87, + "learning_rate": 9.033269073194318e-07, + "loss": 0.7541, + "step": 4508 + }, + { + "epoch": 0.87, + "learning_rate": 9.007392294958572e-07, + "loss": 0.8126, + "step": 4509 + }, + { + "epoch": 0.87, + "learning_rate": 8.981550885262302e-07, + "loss": 0.7906, + "step": 4510 + }, + { + "epoch": 0.87, + "learning_rate": 8.955744854149961e-07, + "loss": 0.7956, + "step": 4511 + }, + { + "epoch": 0.87, + "learning_rate": 8.92997421165227e-07, + "loss": 0.72, + "step": 4512 + }, + { + "epoch": 0.87, + "learning_rate": 8.904238967786205e-07, + "loss": 0.7832, + "step": 4513 + }, + { + "epoch": 0.87, + "learning_rate": 8.878539132554953e-07, + "loss": 0.7732, + "step": 4514 + }, + { + "epoch": 0.87, + "learning_rate": 8.852874715948001e-07, + "loss": 0.8034, + "step": 4515 + }, + { + "epoch": 0.87, + "learning_rate": 8.827245727941003e-07, + "loss": 0.7721, + "step": 4516 + }, + { + "epoch": 0.87, + "learning_rate": 8.801652178495857e-07, + "loss": 0.7653, + "step": 4517 + }, + { + "epoch": 0.87, + "learning_rate": 8.776094077560704e-07, + "loss": 0.7759, + "step": 4518 + }, + { + "epoch": 0.87, + "learning_rate": 8.750571435069888e-07, + "loss": 0.7366, + "step": 4519 + }, + { + "epoch": 0.87, + "learning_rate": 8.725084260943995e-07, + "loss": 0.7412, + "step": 4520 + }, + { + "epoch": 0.87, + "learning_rate": 8.699632565089811e-07, + "loss": 0.7048, + "step": 4521 + }, + { + "epoch": 0.87, + "learning_rate": 8.674216357400289e-07, + "loss": 0.7702, + "step": 4522 + }, + { + "epoch": 0.87, + "learning_rate": 8.648835647754694e-07, + "loss": 0.7517, + "step": 4523 + }, + { + "epoch": 0.87, + "learning_rate": 8.623490446018379e-07, + "loss": 0.7644, + "step": 4524 + }, + { + "epoch": 0.87, + "learning_rate": 8.598180762042974e-07, + "loss": 0.7684, + "step": 4525 + }, + { + "epoch": 0.87, + "learning_rate": 8.572906605666231e-07, + "loss": 0.7492, + "step": 4526 + }, + { + "epoch": 0.87, + "learning_rate": 8.547667986712182e-07, + "loss": 0.7849, + "step": 4527 + }, + { + "epoch": 0.87, + "learning_rate": 8.522464914990969e-07, + "loss": 0.7438, + "step": 4528 + }, + { + "epoch": 0.87, + "learning_rate": 8.497297400298954e-07, + "loss": 0.7944, + "step": 4529 + }, + { + "epoch": 0.87, + "learning_rate": 8.472165452418679e-07, + "loss": 0.7652, + "step": 4530 + }, + { + "epoch": 0.87, + "learning_rate": 8.447069081118842e-07, + "loss": 0.7667, + "step": 4531 + }, + { + "epoch": 0.87, + "learning_rate": 8.422008296154328e-07, + "loss": 0.7339, + "step": 4532 + }, + { + "epoch": 0.87, + "learning_rate": 8.396983107266199e-07, + "loss": 0.8204, + "step": 4533 + }, + { + "epoch": 0.87, + "learning_rate": 8.371993524181643e-07, + "loss": 0.7517, + "step": 4534 + }, + { + "epoch": 0.87, + "learning_rate": 8.347039556614045e-07, + "loss": 0.8065, + "step": 4535 + }, + { + "epoch": 0.87, + "learning_rate": 8.322121214262924e-07, + "loss": 0.7672, + "step": 4536 + }, + { + "epoch": 0.87, + "learning_rate": 8.297238506813965e-07, + "loss": 0.7056, + "step": 4537 + }, + { + "epoch": 0.87, + "learning_rate": 8.272391443939021e-07, + "loss": 0.772, + "step": 4538 + }, + { + "epoch": 0.87, + "learning_rate": 8.24758003529601e-07, + "loss": 0.7746, + "step": 4539 + }, + { + "epoch": 0.87, + "learning_rate": 8.222804290529108e-07, + "loss": 0.7414, + "step": 4540 + }, + { + "epoch": 0.87, + "learning_rate": 8.198064219268553e-07, + "loss": 0.7508, + "step": 4541 + }, + { + "epoch": 0.87, + "learning_rate": 8.173359831130711e-07, + "loss": 0.7978, + "step": 4542 + }, + { + "epoch": 0.87, + "learning_rate": 8.148691135718112e-07, + "loss": 0.6886, + "step": 4543 + }, + { + "epoch": 0.87, + "learning_rate": 8.124058142619407e-07, + "loss": 0.7473, + "step": 4544 + }, + { + "epoch": 0.87, + "learning_rate": 8.099460861409359e-07, + "loss": 1.1156, + "step": 4545 + }, + { + "epoch": 0.88, + "learning_rate": 8.074899301648842e-07, + "loss": 0.8139, + "step": 4546 + }, + { + "epoch": 0.88, + "learning_rate": 8.050373472884876e-07, + "loss": 0.7859, + "step": 4547 + }, + { + "epoch": 0.88, + "learning_rate": 8.025883384650568e-07, + "loss": 0.7619, + "step": 4548 + }, + { + "epoch": 0.88, + "learning_rate": 8.001429046465104e-07, + "loss": 0.7518, + "step": 4549 + }, + { + "epoch": 0.88, + "learning_rate": 7.97701046783389e-07, + "loss": 0.7918, + "step": 4550 + }, + { + "epoch": 0.88, + "learning_rate": 7.952627658248257e-07, + "loss": 0.7681, + "step": 4551 + }, + { + "epoch": 0.88, + "learning_rate": 7.928280627185781e-07, + "loss": 0.8077, + "step": 4552 + }, + { + "epoch": 0.88, + "learning_rate": 7.903969384110044e-07, + "loss": 0.7835, + "step": 4553 + }, + { + "epoch": 0.88, + "learning_rate": 7.87969393847079e-07, + "loss": 0.773, + "step": 4554 + }, + { + "epoch": 0.88, + "learning_rate": 7.85545429970379e-07, + "loss": 0.7996, + "step": 4555 + }, + { + "epoch": 0.88, + "learning_rate": 7.831250477230889e-07, + "loss": 0.8026, + "step": 4556 + }, + { + "epoch": 0.88, + "learning_rate": 7.807082480460082e-07, + "loss": 0.7977, + "step": 4557 + }, + { + "epoch": 0.88, + "learning_rate": 7.782950318785365e-07, + "loss": 0.797, + "step": 4558 + }, + { + "epoch": 0.88, + "learning_rate": 7.758854001586835e-07, + "loss": 0.794, + "step": 4559 + }, + { + "epoch": 0.88, + "learning_rate": 7.734793538230656e-07, + "loss": 0.7694, + "step": 4560 + }, + { + "epoch": 0.88, + "learning_rate": 7.710768938069046e-07, + "loss": 0.7377, + "step": 4561 + }, + { + "epoch": 0.88, + "learning_rate": 7.686780210440315e-07, + "loss": 0.8234, + "step": 4562 + }, + { + "epoch": 0.88, + "learning_rate": 7.662827364668768e-07, + "loss": 0.7606, + "step": 4563 + }, + { + "epoch": 0.88, + "learning_rate": 7.638910410064848e-07, + "loss": 0.7332, + "step": 4564 + }, + { + "epoch": 0.88, + "learning_rate": 7.615029355924974e-07, + "loss": 0.7446, + "step": 4565 + }, + { + "epoch": 0.88, + "learning_rate": 7.591184211531622e-07, + "loss": 0.796, + "step": 4566 + }, + { + "epoch": 0.88, + "learning_rate": 7.567374986153375e-07, + "loss": 0.7554, + "step": 4567 + }, + { + "epoch": 0.88, + "learning_rate": 7.543601689044733e-07, + "loss": 0.6957, + "step": 4568 + }, + { + "epoch": 0.88, + "learning_rate": 7.519864329446358e-07, + "loss": 0.7727, + "step": 4569 + }, + { + "epoch": 0.88, + "learning_rate": 7.49616291658486e-07, + "loss": 0.7071, + "step": 4570 + }, + { + "epoch": 0.88, + "learning_rate": 7.472497459672901e-07, + "loss": 0.8275, + "step": 4571 + }, + { + "epoch": 0.88, + "learning_rate": 7.44886796790919e-07, + "loss": 0.8304, + "step": 4572 + }, + { + "epoch": 0.88, + "learning_rate": 7.425274450478415e-07, + "loss": 1.1019, + "step": 4573 + }, + { + "epoch": 0.88, + "learning_rate": 7.401716916551316e-07, + "loss": 0.7257, + "step": 4574 + }, + { + "epoch": 0.88, + "learning_rate": 7.378195375284636e-07, + "loss": 0.6697, + "step": 4575 + }, + { + "epoch": 0.88, + "learning_rate": 7.354709835821116e-07, + "loss": 0.8061, + "step": 4576 + }, + { + "epoch": 0.88, + "learning_rate": 7.331260307289501e-07, + "loss": 0.7684, + "step": 4577 + }, + { + "epoch": 0.88, + "learning_rate": 7.307846798804552e-07, + "loss": 0.7804, + "step": 4578 + }, + { + "epoch": 0.88, + "learning_rate": 7.284469319467036e-07, + "loss": 0.7711, + "step": 4579 + }, + { + "epoch": 0.88, + "learning_rate": 7.261127878363694e-07, + "loss": 0.7838, + "step": 4580 + }, + { + "epoch": 0.88, + "learning_rate": 7.237822484567292e-07, + "loss": 1.1084, + "step": 4581 + }, + { + "epoch": 0.88, + "learning_rate": 7.214553147136549e-07, + "loss": 0.7475, + "step": 4582 + }, + { + "epoch": 0.88, + "learning_rate": 7.191319875116165e-07, + "loss": 0.7546, + "step": 4583 + }, + { + "epoch": 0.88, + "learning_rate": 7.168122677536893e-07, + "loss": 1.0881, + "step": 4584 + }, + { + "epoch": 0.88, + "learning_rate": 7.144961563415342e-07, + "loss": 0.7993, + "step": 4585 + }, + { + "epoch": 0.88, + "learning_rate": 7.121836541754212e-07, + "loss": 0.7406, + "step": 4586 + }, + { + "epoch": 0.88, + "learning_rate": 7.098747621542102e-07, + "loss": 1.2514, + "step": 4587 + }, + { + "epoch": 0.88, + "learning_rate": 7.075694811753609e-07, + "loss": 0.7607, + "step": 4588 + }, + { + "epoch": 0.88, + "learning_rate": 7.052678121349299e-07, + "loss": 0.7363, + "step": 4589 + }, + { + "epoch": 0.88, + "learning_rate": 7.029697559275662e-07, + "loss": 0.7613, + "step": 4590 + }, + { + "epoch": 0.88, + "learning_rate": 7.006753134465194e-07, + "loss": 0.8137, + "step": 4591 + }, + { + "epoch": 0.88, + "learning_rate": 6.98384485583632e-07, + "loss": 0.7246, + "step": 4592 + }, + { + "epoch": 0.88, + "learning_rate": 6.960972732293414e-07, + "loss": 0.7559, + "step": 4593 + }, + { + "epoch": 0.88, + "learning_rate": 6.938136772726778e-07, + "loss": 0.75, + "step": 4594 + }, + { + "epoch": 0.88, + "learning_rate": 6.915336986012677e-07, + "loss": 0.7862, + "step": 4595 + }, + { + "epoch": 0.88, + "learning_rate": 6.892573381013357e-07, + "loss": 0.6902, + "step": 4596 + }, + { + "epoch": 0.88, + "learning_rate": 6.869845966576927e-07, + "loss": 0.6926, + "step": 4597 + }, + { + "epoch": 0.89, + "learning_rate": 6.847154751537443e-07, + "loss": 0.7889, + "step": 4598 + }, + { + "epoch": 0.89, + "learning_rate": 6.824499744714952e-07, + "loss": 0.7974, + "step": 4599 + }, + { + "epoch": 0.89, + "learning_rate": 6.801880954915374e-07, + "loss": 0.7645, + "step": 4600 + }, + { + "epoch": 0.89, + "learning_rate": 6.779298390930544e-07, + "loss": 0.7612, + "step": 4601 + }, + { + "epoch": 0.89, + "learning_rate": 6.75675206153823e-07, + "loss": 1.1987, + "step": 4602 + }, + { + "epoch": 0.89, + "learning_rate": 6.734241975502143e-07, + "loss": 0.7571, + "step": 4603 + }, + { + "epoch": 0.89, + "learning_rate": 6.711768141571861e-07, + "loss": 0.7602, + "step": 4604 + }, + { + "epoch": 0.89, + "learning_rate": 6.689330568482888e-07, + "loss": 0.7528, + "step": 4605 + }, + { + "epoch": 0.89, + "learning_rate": 6.666929264956679e-07, + "loss": 0.7906, + "step": 4606 + }, + { + "epoch": 0.89, + "learning_rate": 6.644564239700513e-07, + "loss": 0.716, + "step": 4607 + }, + { + "epoch": 0.89, + "learning_rate": 6.622235501407593e-07, + "loss": 0.7562, + "step": 4608 + }, + { + "epoch": 0.89, + "learning_rate": 6.599943058757085e-07, + "loss": 0.7796, + "step": 4609 + }, + { + "epoch": 0.89, + "learning_rate": 6.577686920413928e-07, + "loss": 0.7489, + "step": 4610 + }, + { + "epoch": 0.89, + "learning_rate": 6.555467095029045e-07, + "loss": 0.7001, + "step": 4611 + }, + { + "epoch": 0.89, + "learning_rate": 6.533283591239203e-07, + "loss": 0.7781, + "step": 4612 + }, + { + "epoch": 0.89, + "learning_rate": 6.511136417667075e-07, + "loss": 0.7276, + "step": 4613 + }, + { + "epoch": 0.89, + "learning_rate": 6.489025582921183e-07, + "loss": 0.7551, + "step": 4614 + }, + { + "epoch": 0.89, + "learning_rate": 6.46695109559593e-07, + "loss": 0.7311, + "step": 4615 + }, + { + "epoch": 0.89, + "learning_rate": 6.444912964271633e-07, + "loss": 0.7558, + "step": 4616 + }, + { + "epoch": 0.89, + "learning_rate": 6.422911197514414e-07, + "loss": 0.6831, + "step": 4617 + }, + { + "epoch": 0.89, + "learning_rate": 6.400945803876302e-07, + "loss": 0.8161, + "step": 4618 + }, + { + "epoch": 0.89, + "learning_rate": 6.379016791895176e-07, + "loss": 0.7969, + "step": 4619 + }, + { + "epoch": 0.89, + "learning_rate": 6.357124170094753e-07, + "loss": 0.7763, + "step": 4620 + }, + { + "epoch": 0.89, + "learning_rate": 6.335267946984658e-07, + "loss": 0.7893, + "step": 4621 + }, + { + "epoch": 0.89, + "learning_rate": 6.313448131060307e-07, + "loss": 0.7989, + "step": 4622 + }, + { + "epoch": 0.89, + "learning_rate": 6.291664730803026e-07, + "loss": 0.7556, + "step": 4623 + }, + { + "epoch": 0.89, + "learning_rate": 6.269917754679944e-07, + "loss": 0.7515, + "step": 4624 + }, + { + "epoch": 0.89, + "learning_rate": 6.248207211144008e-07, + "loss": 0.726, + "step": 4625 + }, + { + "epoch": 0.89, + "learning_rate": 6.226533108634102e-07, + "loss": 1.1801, + "step": 4626 + }, + { + "epoch": 0.89, + "learning_rate": 6.204895455574811e-07, + "loss": 0.7409, + "step": 4627 + }, + { + "epoch": 0.89, + "learning_rate": 6.183294260376671e-07, + "loss": 0.7798, + "step": 4628 + }, + { + "epoch": 0.89, + "learning_rate": 6.161729531435967e-07, + "loss": 1.1696, + "step": 4629 + }, + { + "epoch": 0.89, + "learning_rate": 6.140201277134872e-07, + "loss": 0.7746, + "step": 4630 + }, + { + "epoch": 0.89, + "learning_rate": 6.118709505841324e-07, + "loss": 0.7912, + "step": 4631 + }, + { + "epoch": 0.89, + "learning_rate": 6.097254225909122e-07, + "loss": 0.6999, + "step": 4632 + }, + { + "epoch": 0.89, + "learning_rate": 6.075835445677869e-07, + "loss": 0.7169, + "step": 4633 + }, + { + "epoch": 0.89, + "learning_rate": 6.054453173472962e-07, + "loss": 0.6762, + "step": 4634 + }, + { + "epoch": 0.89, + "learning_rate": 6.033107417605633e-07, + "loss": 0.7405, + "step": 4635 + }, + { + "epoch": 0.89, + "learning_rate": 6.011798186372919e-07, + "loss": 0.7764, + "step": 4636 + }, + { + "epoch": 0.89, + "learning_rate": 5.990525488057608e-07, + "loss": 0.778, + "step": 4637 + }, + { + "epoch": 0.89, + "learning_rate": 5.969289330928385e-07, + "loss": 0.7419, + "step": 4638 + }, + { + "epoch": 0.89, + "learning_rate": 5.948089723239636e-07, + "loss": 0.7824, + "step": 4639 + }, + { + "epoch": 0.89, + "learning_rate": 5.926926673231626e-07, + "loss": 0.706, + "step": 4640 + }, + { + "epoch": 0.89, + "learning_rate": 5.905800189130329e-07, + "loss": 0.8175, + "step": 4641 + }, + { + "epoch": 0.89, + "learning_rate": 5.884710279147543e-07, + "loss": 0.7387, + "step": 4642 + }, + { + "epoch": 0.89, + "learning_rate": 5.863656951480878e-07, + "loss": 0.7525, + "step": 4643 + }, + { + "epoch": 0.89, + "learning_rate": 5.842640214313667e-07, + "loss": 0.7324, + "step": 4644 + }, + { + "epoch": 0.89, + "learning_rate": 5.821660075815061e-07, + "loss": 0.7166, + "step": 4645 + }, + { + "epoch": 0.89, + "learning_rate": 5.800716544139972e-07, + "loss": 0.7557, + "step": 4646 + }, + { + "epoch": 0.89, + "learning_rate": 5.779809627429078e-07, + "loss": 0.7651, + "step": 4647 + }, + { + "epoch": 0.89, + "learning_rate": 5.758939333808855e-07, + "loss": 0.6884, + "step": 4648 + }, + { + "epoch": 0.89, + "learning_rate": 5.73810567139148e-07, + "loss": 0.7441, + "step": 4649 + }, + { + "epoch": 0.9, + "learning_rate": 5.717308648274977e-07, + "loss": 0.8059, + "step": 4650 + }, + { + "epoch": 0.9, + "learning_rate": 5.696548272543068e-07, + "loss": 0.7809, + "step": 4651 + }, + { + "epoch": 0.9, + "learning_rate": 5.67582455226523e-07, + "loss": 0.7389, + "step": 4652 + }, + { + "epoch": 0.9, + "learning_rate": 5.655137495496721e-07, + "loss": 1.1157, + "step": 4653 + }, + { + "epoch": 0.9, + "learning_rate": 5.634487110278519e-07, + "loss": 0.7814, + "step": 4654 + }, + { + "epoch": 0.9, + "learning_rate": 5.613873404637382e-07, + "loss": 0.6713, + "step": 4655 + }, + { + "epoch": 0.9, + "learning_rate": 5.5932963865858e-07, + "loss": 0.751, + "step": 4656 + }, + { + "epoch": 0.9, + "learning_rate": 5.572756064121953e-07, + "loss": 0.7541, + "step": 4657 + }, + { + "epoch": 0.9, + "learning_rate": 5.552252445229855e-07, + "loss": 0.794, + "step": 4658 + }, + { + "epoch": 0.9, + "learning_rate": 5.531785537879141e-07, + "loss": 0.7252, + "step": 4659 + }, + { + "epoch": 0.9, + "learning_rate": 5.511355350025305e-07, + "loss": 0.8045, + "step": 4660 + }, + { + "epoch": 0.9, + "learning_rate": 5.490961889609425e-07, + "loss": 0.7728, + "step": 4661 + }, + { + "epoch": 0.9, + "learning_rate": 5.470605164558407e-07, + "loss": 0.7674, + "step": 4662 + }, + { + "epoch": 0.9, + "learning_rate": 5.450285182784853e-07, + "loss": 0.788, + "step": 4663 + }, + { + "epoch": 0.9, + "learning_rate": 5.430001952187048e-07, + "loss": 0.792, + "step": 4664 + }, + { + "epoch": 0.9, + "learning_rate": 5.409755480649059e-07, + "loss": 0.811, + "step": 4665 + }, + { + "epoch": 0.9, + "learning_rate": 5.389545776040583e-07, + "loss": 0.7225, + "step": 4666 + }, + { + "epoch": 0.9, + "learning_rate": 5.369372846217103e-07, + "loss": 0.762, + "step": 4667 + }, + { + "epoch": 0.9, + "learning_rate": 5.349236699019766e-07, + "loss": 0.8235, + "step": 4668 + }, + { + "epoch": 0.9, + "learning_rate": 5.329137342275403e-07, + "loss": 0.7511, + "step": 4669 + }, + { + "epoch": 0.9, + "learning_rate": 5.309074783796608e-07, + "loss": 0.7654, + "step": 4670 + }, + { + "epoch": 0.9, + "learning_rate": 5.289049031381599e-07, + "loss": 0.7704, + "step": 4671 + }, + { + "epoch": 0.9, + "learning_rate": 5.269060092814348e-07, + "loss": 0.7361, + "step": 4672 + }, + { + "epoch": 0.9, + "learning_rate": 5.249107975864487e-07, + "loss": 0.7309, + "step": 4673 + }, + { + "epoch": 0.9, + "learning_rate": 5.229192688287332e-07, + "loss": 0.7879, + "step": 4674 + }, + { + "epoch": 0.9, + "learning_rate": 5.209314237823904e-07, + "loss": 0.7898, + "step": 4675 + }, + { + "epoch": 0.9, + "learning_rate": 5.189472632200898e-07, + "loss": 0.7388, + "step": 4676 + }, + { + "epoch": 0.9, + "learning_rate": 5.169667879130657e-07, + "loss": 0.8108, + "step": 4677 + }, + { + "epoch": 0.9, + "learning_rate": 5.149899986311246e-07, + "loss": 0.684, + "step": 4678 + }, + { + "epoch": 0.9, + "learning_rate": 5.130168961426385e-07, + "loss": 0.7448, + "step": 4679 + }, + { + "epoch": 0.9, + "learning_rate": 5.110474812145461e-07, + "loss": 1.1064, + "step": 4680 + }, + { + "epoch": 0.9, + "learning_rate": 5.090817546123505e-07, + "loss": 0.81, + "step": 4681 + }, + { + "epoch": 0.9, + "learning_rate": 5.071197171001263e-07, + "loss": 0.779, + "step": 4682 + }, + { + "epoch": 0.9, + "learning_rate": 5.051613694405111e-07, + "loss": 0.7706, + "step": 4683 + }, + { + "epoch": 0.9, + "learning_rate": 5.032067123947049e-07, + "loss": 0.8051, + "step": 4684 + }, + { + "epoch": 0.9, + "learning_rate": 5.012557467224833e-07, + "loss": 0.7972, + "step": 4685 + }, + { + "epoch": 0.9, + "learning_rate": 4.993084731821729e-07, + "loss": 0.7211, + "step": 4686 + }, + { + "epoch": 0.9, + "learning_rate": 4.973648925306773e-07, + "loss": 0.6975, + "step": 4687 + }, + { + "epoch": 0.9, + "learning_rate": 4.954250055234589e-07, + "loss": 0.7778, + "step": 4688 + }, + { + "epoch": 0.9, + "learning_rate": 4.934888129145476e-07, + "loss": 0.7934, + "step": 4689 + }, + { + "epoch": 0.9, + "learning_rate": 4.915563154565328e-07, + "loss": 0.7524, + "step": 4690 + }, + { + "epoch": 0.9, + "learning_rate": 4.896275139005702e-07, + "loss": 0.7969, + "step": 4691 + }, + { + "epoch": 0.9, + "learning_rate": 4.877024089963822e-07, + "loss": 0.7842, + "step": 4692 + }, + { + "epoch": 0.9, + "learning_rate": 4.85781001492247e-07, + "loss": 0.7524, + "step": 4693 + }, + { + "epoch": 0.9, + "learning_rate": 4.838632921350128e-07, + "loss": 0.8081, + "step": 4694 + }, + { + "epoch": 0.9, + "learning_rate": 4.819492816700844e-07, + "loss": 0.7782, + "step": 4695 + }, + { + "epoch": 0.9, + "learning_rate": 4.800389708414321e-07, + "loss": 0.7572, + "step": 4696 + }, + { + "epoch": 0.9, + "learning_rate": 4.7813236039159e-07, + "loss": 0.7401, + "step": 4697 + }, + { + "epoch": 0.9, + "learning_rate": 4.762294510616483e-07, + "loss": 0.7527, + "step": 4698 + }, + { + "epoch": 0.9, + "learning_rate": 4.7433024359126443e-07, + "loss": 0.8097, + "step": 4699 + }, + { + "epoch": 0.9, + "learning_rate": 4.7243473871865455e-07, + "loss": 0.7532, + "step": 4700 + }, + { + "epoch": 0.9, + "learning_rate": 4.705429371805925e-07, + "loss": 0.765, + "step": 4701 + }, + { + "epoch": 0.91, + "learning_rate": 4.6865483971242023e-07, + "loss": 0.7283, + "step": 4702 + }, + { + "epoch": 0.91, + "learning_rate": 4.6677044704802944e-07, + "loss": 0.7707, + "step": 4703 + }, + { + "epoch": 0.91, + "learning_rate": 4.6488975991988207e-07, + "loss": 0.7193, + "step": 4704 + }, + { + "epoch": 0.91, + "learning_rate": 4.6301277905899445e-07, + "loss": 0.7822, + "step": 4705 + }, + { + "epoch": 0.91, + "learning_rate": 4.611395051949408e-07, + "loss": 1.1104, + "step": 4706 + }, + { + "epoch": 0.91, + "learning_rate": 4.592699390558597e-07, + "loss": 0.7954, + "step": 4707 + }, + { + "epoch": 0.91, + "learning_rate": 4.574040813684433e-07, + "loss": 0.7769, + "step": 4708 + }, + { + "epoch": 0.91, + "learning_rate": 4.555419328579469e-07, + "loss": 0.7937, + "step": 4709 + }, + { + "epoch": 0.91, + "learning_rate": 4.536834942481805e-07, + "loss": 0.7365, + "step": 4710 + }, + { + "epoch": 0.91, + "learning_rate": 4.5182876626151286e-07, + "loss": 0.7334, + "step": 4711 + }, + { + "epoch": 0.91, + "learning_rate": 4.4997774961887176e-07, + "loss": 0.7395, + "step": 4712 + }, + { + "epoch": 0.91, + "learning_rate": 4.4813044503973945e-07, + "loss": 0.7637, + "step": 4713 + }, + { + "epoch": 0.91, + "learning_rate": 4.462868532421616e-07, + "loss": 0.7508, + "step": 4714 + }, + { + "epoch": 0.91, + "learning_rate": 4.444469749427316e-07, + "loss": 0.6475, + "step": 4715 + }, + { + "epoch": 0.91, + "learning_rate": 4.426108108566085e-07, + "loss": 0.7528, + "step": 4716 + }, + { + "epoch": 0.91, + "learning_rate": 4.4077836169750145e-07, + "loss": 0.7892, + "step": 4717 + }, + { + "epoch": 0.91, + "learning_rate": 4.3894962817767614e-07, + "loss": 0.7653, + "step": 4718 + }, + { + "epoch": 0.91, + "learning_rate": 4.3712461100796077e-07, + "loss": 0.8256, + "step": 4719 + }, + { + "epoch": 0.91, + "learning_rate": 4.353033108977278e-07, + "loss": 0.7667, + "step": 4720 + }, + { + "epoch": 0.91, + "learning_rate": 4.334857285549143e-07, + "loss": 0.7907, + "step": 4721 + }, + { + "epoch": 0.91, + "learning_rate": 4.316718646860074e-07, + "loss": 0.761, + "step": 4722 + }, + { + "epoch": 0.91, + "learning_rate": 4.2986171999605087e-07, + "loss": 1.1828, + "step": 4723 + }, + { + "epoch": 0.91, + "learning_rate": 4.280552951886419e-07, + "loss": 0.7728, + "step": 4724 + }, + { + "epoch": 0.91, + "learning_rate": 4.26252590965931e-07, + "loss": 0.7723, + "step": 4725 + }, + { + "epoch": 0.91, + "learning_rate": 4.2445360802862657e-07, + "loss": 0.7773, + "step": 4726 + }, + { + "epoch": 0.91, + "learning_rate": 4.22658347075986e-07, + "loss": 0.7896, + "step": 4727 + }, + { + "epoch": 0.91, + "learning_rate": 4.208668088058221e-07, + "loss": 0.7951, + "step": 4728 + }, + { + "epoch": 0.91, + "learning_rate": 4.190789939144979e-07, + "loss": 0.7517, + "step": 4729 + }, + { + "epoch": 0.91, + "learning_rate": 4.172949030969331e-07, + "loss": 0.8029, + "step": 4730 + }, + { + "epoch": 0.91, + "learning_rate": 4.155145370465985e-07, + "loss": 1.0775, + "step": 4731 + }, + { + "epoch": 0.91, + "learning_rate": 4.137378964555172e-07, + "loss": 0.7684, + "step": 4732 + }, + { + "epoch": 0.91, + "learning_rate": 4.119649820142613e-07, + "loss": 0.7873, + "step": 4733 + }, + { + "epoch": 0.91, + "learning_rate": 4.1019579441195945e-07, + "loss": 0.7405, + "step": 4734 + }, + { + "epoch": 0.91, + "learning_rate": 4.0843033433628945e-07, + "loss": 0.7343, + "step": 4735 + }, + { + "epoch": 0.91, + "learning_rate": 4.0666860247347785e-07, + "loss": 0.7396, + "step": 4736 + }, + { + "epoch": 0.91, + "learning_rate": 4.049105995083058e-07, + "loss": 0.7615, + "step": 4737 + }, + { + "epoch": 0.91, + "learning_rate": 4.031563261241034e-07, + "loss": 0.7863, + "step": 4738 + }, + { + "epoch": 0.91, + "learning_rate": 4.014057830027518e-07, + "loss": 0.7238, + "step": 4739 + }, + { + "epoch": 0.91, + "learning_rate": 3.99658970824679e-07, + "loss": 0.7597, + "step": 4740 + }, + { + "epoch": 0.91, + "learning_rate": 3.9791589026886845e-07, + "loss": 0.776, + "step": 4741 + }, + { + "epoch": 0.91, + "learning_rate": 3.961765420128494e-07, + "loss": 0.7111, + "step": 4742 + }, + { + "epoch": 0.91, + "learning_rate": 3.9444092673269875e-07, + "loss": 0.7524, + "step": 4743 + }, + { + "epoch": 0.91, + "learning_rate": 3.927090451030491e-07, + "loss": 0.7378, + "step": 4744 + }, + { + "epoch": 0.91, + "learning_rate": 3.909808977970719e-07, + "loss": 0.7127, + "step": 4745 + }, + { + "epoch": 0.91, + "learning_rate": 3.8925648548649664e-07, + "loss": 0.7414, + "step": 4746 + }, + { + "epoch": 0.91, + "learning_rate": 3.875358088415937e-07, + "loss": 0.6555, + "step": 4747 + }, + { + "epoch": 0.91, + "learning_rate": 3.858188685311892e-07, + "loss": 0.7733, + "step": 4748 + }, + { + "epoch": 0.91, + "learning_rate": 3.8410566522264824e-07, + "loss": 0.7587, + "step": 4749 + }, + { + "epoch": 0.91, + "learning_rate": 3.823961995818892e-07, + "loss": 0.751, + "step": 4750 + }, + { + "epoch": 0.91, + "learning_rate": 3.806904722733762e-07, + "loss": 0.7781, + "step": 4751 + }, + { + "epoch": 0.91, + "learning_rate": 3.78988483960121e-07, + "loss": 0.7999, + "step": 4752 + }, + { + "epoch": 0.91, + "learning_rate": 3.772902353036789e-07, + "loss": 0.7527, + "step": 4753 + }, + { + "epoch": 0.92, + "learning_rate": 3.7559572696415416e-07, + "loss": 0.7361, + "step": 4754 + }, + { + "epoch": 0.92, + "learning_rate": 3.7390495960019645e-07, + "loss": 0.7853, + "step": 4755 + }, + { + "epoch": 0.92, + "learning_rate": 3.722179338690046e-07, + "loss": 0.7431, + "step": 4756 + }, + { + "epoch": 0.92, + "learning_rate": 3.705346504263163e-07, + "loss": 0.8205, + "step": 4757 + }, + { + "epoch": 0.92, + "learning_rate": 3.688551099264226e-07, + "loss": 0.7805, + "step": 4758 + }, + { + "epoch": 0.92, + "learning_rate": 3.671793130221524e-07, + "loss": 0.7659, + "step": 4759 + }, + { + "epoch": 0.92, + "learning_rate": 3.6550726036488237e-07, + "loss": 0.7716, + "step": 4760 + }, + { + "epoch": 0.92, + "learning_rate": 3.638389526045383e-07, + "loss": 0.7377, + "step": 4761 + }, + { + "epoch": 0.92, + "learning_rate": 3.621743903895814e-07, + "loss": 0.8091, + "step": 4762 + }, + { + "epoch": 0.92, + "learning_rate": 3.6051357436702407e-07, + "loss": 0.6896, + "step": 4763 + }, + { + "epoch": 0.92, + "learning_rate": 3.5885650518241887e-07, + "loss": 0.723, + "step": 4764 + }, + { + "epoch": 0.92, + "learning_rate": 3.57203183479865e-07, + "loss": 0.7756, + "step": 4765 + }, + { + "epoch": 0.92, + "learning_rate": 3.5555360990200294e-07, + "loss": 0.7799, + "step": 4766 + }, + { + "epoch": 0.92, + "learning_rate": 3.5390778509001523e-07, + "loss": 1.2161, + "step": 4767 + }, + { + "epoch": 0.92, + "learning_rate": 3.5226570968363237e-07, + "loss": 0.7506, + "step": 4768 + }, + { + "epoch": 0.92, + "learning_rate": 3.506273843211205e-07, + "loss": 0.7443, + "step": 4769 + }, + { + "epoch": 0.92, + "learning_rate": 3.489928096392925e-07, + "loss": 0.7975, + "step": 4770 + }, + { + "epoch": 0.92, + "learning_rate": 3.4736198627350224e-07, + "loss": 0.7475, + "step": 4771 + }, + { + "epoch": 0.92, + "learning_rate": 3.457349148576461e-07, + "loss": 0.7985, + "step": 4772 + }, + { + "epoch": 0.92, + "learning_rate": 3.4411159602416145e-07, + "loss": 0.7988, + "step": 4773 + }, + { + "epoch": 0.92, + "learning_rate": 3.4249203040402577e-07, + "loss": 0.7741, + "step": 4774 + }, + { + "epoch": 0.92, + "learning_rate": 3.4087621862676114e-07, + "loss": 0.7619, + "step": 4775 + }, + { + "epoch": 0.92, + "learning_rate": 3.392641613204295e-07, + "loss": 0.7687, + "step": 4776 + }, + { + "epoch": 0.92, + "learning_rate": 3.3765585911162744e-07, + "loss": 0.7857, + "step": 4777 + }, + { + "epoch": 0.92, + "learning_rate": 3.3605131262550386e-07, + "loss": 0.7377, + "step": 4778 + }, + { + "epoch": 0.92, + "learning_rate": 3.344505224857353e-07, + "loss": 0.7998, + "step": 4779 + }, + { + "epoch": 0.92, + "learning_rate": 3.328534893145463e-07, + "loss": 0.7669, + "step": 4780 + }, + { + "epoch": 0.92, + "learning_rate": 3.312602137326981e-07, + "loss": 0.7633, + "step": 4781 + }, + { + "epoch": 0.92, + "learning_rate": 3.296706963594909e-07, + "loss": 0.6904, + "step": 4782 + }, + { + "epoch": 0.92, + "learning_rate": 3.2808493781276705e-07, + "loss": 0.8073, + "step": 4783 + }, + { + "epoch": 0.92, + "learning_rate": 3.265029387089047e-07, + "loss": 0.7899, + "step": 4784 + }, + { + "epoch": 0.92, + "learning_rate": 3.2492469966282305e-07, + "loss": 0.7862, + "step": 4785 + }, + { + "epoch": 0.92, + "learning_rate": 3.233502212879769e-07, + "loss": 0.8562, + "step": 4786 + }, + { + "epoch": 0.92, + "learning_rate": 3.2177950419636226e-07, + "loss": 0.7456, + "step": 4787 + }, + { + "epoch": 0.92, + "learning_rate": 3.2021254899851194e-07, + "loss": 0.7469, + "step": 4788 + }, + { + "epoch": 0.92, + "learning_rate": 3.1864935630349424e-07, + "loss": 0.7605, + "step": 4789 + }, + { + "epoch": 0.92, + "learning_rate": 3.170899267189209e-07, + "loss": 0.7804, + "step": 4790 + }, + { + "epoch": 0.92, + "learning_rate": 3.1553426085093487e-07, + "loss": 0.7048, + "step": 4791 + }, + { + "epoch": 0.92, + "learning_rate": 3.139823593042191e-07, + "loss": 0.8102, + "step": 4792 + }, + { + "epoch": 0.92, + "learning_rate": 3.124342226819932e-07, + "loss": 0.7944, + "step": 4793 + }, + { + "epoch": 0.92, + "learning_rate": 3.108898515860115e-07, + "loss": 0.8147, + "step": 4794 + }, + { + "epoch": 0.92, + "learning_rate": 3.093492466165693e-07, + "loss": 0.759, + "step": 4795 + }, + { + "epoch": 0.92, + "learning_rate": 3.0781240837249095e-07, + "loss": 0.7334, + "step": 4796 + }, + { + "epoch": 0.92, + "learning_rate": 3.06279337451143e-07, + "loss": 0.7624, + "step": 4797 + }, + { + "epoch": 0.92, + "learning_rate": 3.0475003444842553e-07, + "loss": 0.7868, + "step": 4798 + }, + { + "epoch": 0.92, + "learning_rate": 3.032244999587719e-07, + "loss": 0.759, + "step": 4799 + }, + { + "epoch": 0.92, + "learning_rate": 3.017027345751555e-07, + "loss": 0.7866, + "step": 4800 + }, + { + "epoch": 0.92, + "learning_rate": 3.0018473888907994e-07, + "loss": 0.7725, + "step": 4801 + }, + { + "epoch": 0.92, + "learning_rate": 2.986705134905832e-07, + "loss": 1.1021, + "step": 4802 + }, + { + "epoch": 0.92, + "learning_rate": 2.9716005896824553e-07, + "loss": 0.7627, + "step": 4803 + }, + { + "epoch": 0.92, + "learning_rate": 2.9565337590916953e-07, + "loss": 0.7658, + "step": 4804 + }, + { + "epoch": 0.92, + "learning_rate": 2.9415046489900235e-07, + "loss": 0.7763, + "step": 4805 + }, + { + "epoch": 0.93, + "learning_rate": 2.9265132652191773e-07, + "loss": 0.7744, + "step": 4806 + }, + { + "epoch": 0.93, + "learning_rate": 2.911559613606296e-07, + "loss": 0.7171, + "step": 4807 + }, + { + "epoch": 0.93, + "learning_rate": 2.896643699963797e-07, + "loss": 0.7456, + "step": 4808 + }, + { + "epoch": 0.93, + "learning_rate": 2.881765530089442e-07, + "loss": 0.7241, + "step": 4809 + }, + { + "epoch": 0.93, + "learning_rate": 2.8669251097663384e-07, + "loss": 1.151, + "step": 4810 + }, + { + "epoch": 0.93, + "learning_rate": 2.852122444762917e-07, + "loss": 0.6748, + "step": 4811 + }, + { + "epoch": 0.93, + "learning_rate": 2.837357540832919e-07, + "loss": 0.7198, + "step": 4812 + }, + { + "epoch": 0.93, + "learning_rate": 2.8226304037154206e-07, + "loss": 0.771, + "step": 4813 + }, + { + "epoch": 0.93, + "learning_rate": 2.8079410391347873e-07, + "loss": 1.1713, + "step": 4814 + }, + { + "epoch": 0.93, + "learning_rate": 2.7932894528007625e-07, + "loss": 0.7375, + "step": 4815 + }, + { + "epoch": 0.93, + "learning_rate": 2.7786756504083577e-07, + "loss": 0.7443, + "step": 4816 + }, + { + "epoch": 0.93, + "learning_rate": 2.764099637637918e-07, + "loss": 0.7466, + "step": 4817 + }, + { + "epoch": 0.93, + "learning_rate": 2.749561420155089e-07, + "loss": 0.739, + "step": 4818 + }, + { + "epoch": 0.93, + "learning_rate": 2.7350610036108285e-07, + "loss": 0.7393, + "step": 4819 + }, + { + "epoch": 0.93, + "learning_rate": 2.720598393641416e-07, + "loss": 0.7562, + "step": 4820 + }, + { + "epoch": 0.93, + "learning_rate": 2.706173595868389e-07, + "loss": 1.1343, + "step": 4821 + }, + { + "epoch": 0.93, + "learning_rate": 2.6917866158986617e-07, + "loss": 0.7523, + "step": 4822 + }, + { + "epoch": 0.93, + "learning_rate": 2.6774374593243723e-07, + "loss": 0.7859, + "step": 4823 + }, + { + "epoch": 0.93, + "learning_rate": 2.663126131723015e-07, + "loss": 0.7072, + "step": 4824 + }, + { + "epoch": 0.93, + "learning_rate": 2.648852638657362e-07, + "loss": 0.8096, + "step": 4825 + }, + { + "epoch": 0.93, + "learning_rate": 2.6346169856754534e-07, + "loss": 1.1625, + "step": 4826 + }, + { + "epoch": 0.93, + "learning_rate": 2.6204191783106516e-07, + "loss": 0.7901, + "step": 4827 + }, + { + "epoch": 0.93, + "learning_rate": 2.6062592220816195e-07, + "loss": 0.7369, + "step": 4828 + }, + { + "epoch": 0.93, + "learning_rate": 2.5921371224922554e-07, + "loss": 0.7217, + "step": 4829 + }, + { + "epoch": 0.93, + "learning_rate": 2.57805288503179e-07, + "loss": 0.7689, + "step": 4830 + }, + { + "epoch": 0.93, + "learning_rate": 2.564006515174722e-07, + "loss": 0.7791, + "step": 4831 + }, + { + "epoch": 0.93, + "learning_rate": 2.5499980183808284e-07, + "loss": 0.7749, + "step": 4832 + }, + { + "epoch": 0.93, + "learning_rate": 2.5360274000951645e-07, + "loss": 0.7819, + "step": 4833 + }, + { + "epoch": 0.93, + "learning_rate": 2.522094665748087e-07, + "loss": 1.1702, + "step": 4834 + }, + { + "epoch": 0.93, + "learning_rate": 2.508199820755186e-07, + "loss": 0.7431, + "step": 4835 + }, + { + "epoch": 0.93, + "learning_rate": 2.49434287051733e-07, + "loss": 0.7351, + "step": 4836 + }, + { + "epoch": 0.93, + "learning_rate": 2.4805238204207103e-07, + "loss": 0.7562, + "step": 4837 + }, + { + "epoch": 0.93, + "learning_rate": 2.4667426758367197e-07, + "loss": 0.7673, + "step": 4838 + }, + { + "epoch": 0.93, + "learning_rate": 2.4529994421220506e-07, + "loss": 0.7743, + "step": 4839 + }, + { + "epoch": 0.93, + "learning_rate": 2.439294124618652e-07, + "loss": 0.7303, + "step": 4840 + }, + { + "epoch": 0.93, + "learning_rate": 2.4256267286537404e-07, + "loss": 0.7409, + "step": 4841 + }, + { + "epoch": 0.93, + "learning_rate": 2.4119972595398e-07, + "loss": 0.7609, + "step": 4842 + }, + { + "epoch": 0.93, + "learning_rate": 2.3984057225745484e-07, + "loss": 0.772, + "step": 4843 + }, + { + "epoch": 0.93, + "learning_rate": 2.384852123040982e-07, + "loss": 0.7653, + "step": 4844 + }, + { + "epoch": 0.93, + "learning_rate": 2.3713364662073412e-07, + "loss": 0.748, + "step": 4845 + }, + { + "epoch": 0.93, + "learning_rate": 2.3578587573271139e-07, + "loss": 0.7758, + "step": 4846 + }, + { + "epoch": 0.93, + "learning_rate": 2.3444190016390533e-07, + "loss": 1.1148, + "step": 4847 + }, + { + "epoch": 0.93, + "learning_rate": 2.3310172043671254e-07, + "loss": 0.7587, + "step": 4848 + }, + { + "epoch": 0.93, + "learning_rate": 2.3176533707205962e-07, + "loss": 0.8059, + "step": 4849 + }, + { + "epoch": 0.93, + "learning_rate": 2.304327505893933e-07, + "loss": 0.7523, + "step": 4850 + }, + { + "epoch": 0.93, + "learning_rate": 2.291039615066848e-07, + "loss": 0.7386, + "step": 4851 + }, + { + "epoch": 0.93, + "learning_rate": 2.2777897034043206e-07, + "loss": 0.8175, + "step": 4852 + }, + { + "epoch": 0.93, + "learning_rate": 2.2645777760565313e-07, + "loss": 0.7591, + "step": 4853 + }, + { + "epoch": 0.93, + "learning_rate": 2.2514038381589387e-07, + "loss": 0.7447, + "step": 4854 + }, + { + "epoch": 0.93, + "learning_rate": 2.2382678948321801e-07, + "loss": 0.7734, + "step": 4855 + }, + { + "epoch": 0.93, + "learning_rate": 2.2251699511821823e-07, + "loss": 0.7157, + "step": 4856 + }, + { + "epoch": 0.93, + "learning_rate": 2.2121100123000728e-07, + "loss": 0.7759, + "step": 4857 + }, + { + "epoch": 0.94, + "learning_rate": 2.1990880832621796e-07, + "loss": 0.7363, + "step": 4858 + }, + { + "epoch": 0.94, + "learning_rate": 2.18610416913011e-07, + "loss": 0.7647, + "step": 4859 + }, + { + "epoch": 0.94, + "learning_rate": 2.1731582749506709e-07, + "loss": 1.1867, + "step": 4860 + }, + { + "epoch": 0.94, + "learning_rate": 2.1602504057558815e-07, + "loss": 0.7781, + "step": 4861 + }, + { + "epoch": 0.94, + "learning_rate": 2.1473805665630065e-07, + "loss": 1.0813, + "step": 4862 + }, + { + "epoch": 0.94, + "learning_rate": 2.1345487623744888e-07, + "loss": 0.7182, + "step": 4863 + }, + { + "epoch": 0.94, + "learning_rate": 2.1217549981780273e-07, + "loss": 0.7841, + "step": 4864 + }, + { + "epoch": 0.94, + "learning_rate": 2.1089992789464887e-07, + "loss": 0.7731, + "step": 4865 + }, + { + "epoch": 0.94, + "learning_rate": 2.096281609638029e-07, + "loss": 0.7655, + "step": 4866 + }, + { + "epoch": 0.94, + "learning_rate": 2.0836019951959275e-07, + "loss": 0.7437, + "step": 4867 + }, + { + "epoch": 0.94, + "learning_rate": 2.0709604405487192e-07, + "loss": 0.7946, + "step": 4868 + }, + { + "epoch": 0.94, + "learning_rate": 2.058356950610152e-07, + "loss": 0.7469, + "step": 4869 + }, + { + "epoch": 0.94, + "learning_rate": 2.04579153027914e-07, + "loss": 0.7767, + "step": 4870 + }, + { + "epoch": 0.94, + "learning_rate": 2.0332641844398538e-07, + "loss": 0.7914, + "step": 4871 + }, + { + "epoch": 0.94, + "learning_rate": 2.0207749179615877e-07, + "loss": 0.7396, + "step": 4872 + }, + { + "epoch": 0.94, + "learning_rate": 2.0083237356989249e-07, + "loss": 0.7885, + "step": 4873 + }, + { + "epoch": 0.94, + "learning_rate": 1.995910642491572e-07, + "loss": 0.7907, + "step": 4874 + }, + { + "epoch": 0.94, + "learning_rate": 1.983535643164458e-07, + "loss": 0.8036, + "step": 4875 + }, + { + "epoch": 0.94, + "learning_rate": 1.9711987425277356e-07, + "loss": 0.8085, + "step": 4876 + }, + { + "epoch": 0.94, + "learning_rate": 1.958899945376691e-07, + "loss": 0.7248, + "step": 4877 + }, + { + "epoch": 0.94, + "learning_rate": 1.9466392564918336e-07, + "loss": 0.7341, + "step": 4878 + }, + { + "epoch": 0.94, + "learning_rate": 1.934416680638873e-07, + "loss": 0.7935, + "step": 4879 + }, + { + "epoch": 0.94, + "learning_rate": 1.922232222568654e-07, + "loss": 0.7398, + "step": 4880 + }, + { + "epoch": 0.94, + "learning_rate": 1.9100858870172545e-07, + "loss": 0.7824, + "step": 4881 + }, + { + "epoch": 0.94, + "learning_rate": 1.89797767870592e-07, + "loss": 0.7413, + "step": 4882 + }, + { + "epoch": 0.94, + "learning_rate": 1.8859076023410638e-07, + "loss": 1.215, + "step": 4883 + }, + { + "epoch": 0.94, + "learning_rate": 1.8738756626142997e-07, + "loss": 0.776, + "step": 4884 + }, + { + "epoch": 0.94, + "learning_rate": 1.8618818642023863e-07, + "loss": 0.7816, + "step": 4885 + }, + { + "epoch": 0.94, + "learning_rate": 1.8499262117672945e-07, + "loss": 0.8018, + "step": 4886 + }, + { + "epoch": 0.94, + "learning_rate": 1.8380087099561295e-07, + "loss": 0.782, + "step": 4887 + }, + { + "epoch": 0.94, + "learning_rate": 1.826129363401208e-07, + "loss": 0.766, + "step": 4888 + }, + { + "epoch": 0.94, + "learning_rate": 1.8142881767199804e-07, + "loss": 0.7759, + "step": 4889 + }, + { + "epoch": 0.94, + "learning_rate": 1.8024851545150769e-07, + "loss": 0.7352, + "step": 4890 + }, + { + "epoch": 0.94, + "learning_rate": 1.7907203013742936e-07, + "loss": 0.7157, + "step": 4891 + }, + { + "epoch": 0.94, + "learning_rate": 1.7789936218706062e-07, + "loss": 0.707, + "step": 4892 + }, + { + "epoch": 0.94, + "learning_rate": 1.767305120562124e-07, + "loss": 1.1378, + "step": 4893 + }, + { + "epoch": 0.94, + "learning_rate": 1.755654801992146e-07, + "loss": 0.7109, + "step": 4894 + }, + { + "epoch": 0.94, + "learning_rate": 1.7440426706890835e-07, + "loss": 0.75, + "step": 4895 + }, + { + "epoch": 0.94, + "learning_rate": 1.7324687311665812e-07, + "loss": 1.1441, + "step": 4896 + }, + { + "epoch": 0.94, + "learning_rate": 1.7209329879233516e-07, + "loss": 0.772, + "step": 4897 + }, + { + "epoch": 0.94, + "learning_rate": 1.7094354454433303e-07, + "loss": 0.763, + "step": 4898 + }, + { + "epoch": 0.94, + "learning_rate": 1.6979761081955537e-07, + "loss": 0.6992, + "step": 4899 + }, + { + "epoch": 0.94, + "learning_rate": 1.6865549806342363e-07, + "loss": 0.8053, + "step": 4900 + }, + { + "epoch": 0.94, + "learning_rate": 1.675172067198738e-07, + "loss": 0.7559, + "step": 4901 + }, + { + "epoch": 0.94, + "learning_rate": 1.6638273723135645e-07, + "loss": 0.7539, + "step": 4902 + }, + { + "epoch": 0.94, + "learning_rate": 1.6525209003883658e-07, + "loss": 0.7714, + "step": 4903 + }, + { + "epoch": 0.94, + "learning_rate": 1.6412526558179155e-07, + "loss": 0.7901, + "step": 4904 + }, + { + "epoch": 0.94, + "learning_rate": 1.6300226429821653e-07, + "loss": 1.2077, + "step": 4905 + }, + { + "epoch": 0.94, + "learning_rate": 1.6188308662461683e-07, + "loss": 0.7359, + "step": 4906 + }, + { + "epoch": 0.94, + "learning_rate": 1.6076773299601335e-07, + "loss": 0.734, + "step": 4907 + }, + { + "epoch": 0.94, + "learning_rate": 1.596562038459415e-07, + "loss": 0.7314, + "step": 4908 + }, + { + "epoch": 0.94, + "learning_rate": 1.585484996064479e-07, + "loss": 0.7022, + "step": 4909 + }, + { + "epoch": 0.95, + "learning_rate": 1.5744462070809598e-07, + "loss": 0.764, + "step": 4910 + }, + { + "epoch": 0.95, + "learning_rate": 1.5634456757995907e-07, + "loss": 0.783, + "step": 4911 + }, + { + "epoch": 0.95, + "learning_rate": 1.5524834064962192e-07, + "loss": 0.7769, + "step": 4912 + }, + { + "epoch": 0.95, + "learning_rate": 1.5415594034318804e-07, + "loss": 0.7804, + "step": 4913 + }, + { + "epoch": 0.95, + "learning_rate": 1.5306736708526783e-07, + "loss": 0.7414, + "step": 4914 + }, + { + "epoch": 0.95, + "learning_rate": 1.519826212989861e-07, + "loss": 0.7515, + "step": 4915 + }, + { + "epoch": 0.95, + "learning_rate": 1.509017034059823e-07, + "loss": 0.7346, + "step": 4916 + }, + { + "epoch": 0.95, + "learning_rate": 1.4982461382640257e-07, + "loss": 0.8114, + "step": 4917 + }, + { + "epoch": 0.95, + "learning_rate": 1.4875135297891085e-07, + "loss": 0.7644, + "step": 4918 + }, + { + "epoch": 0.95, + "learning_rate": 1.4768192128067905e-07, + "loss": 0.7329, + "step": 4919 + }, + { + "epoch": 0.95, + "learning_rate": 1.4661631914739238e-07, + "loss": 0.742, + "step": 4920 + }, + { + "epoch": 0.95, + "learning_rate": 1.4555454699324733e-07, + "loss": 0.7797, + "step": 4921 + }, + { + "epoch": 0.95, + "learning_rate": 1.4449660523095155e-07, + "loss": 0.7375, + "step": 4922 + }, + { + "epoch": 0.95, + "learning_rate": 1.4344249427172164e-07, + "loss": 0.8273, + "step": 4923 + }, + { + "epoch": 0.95, + "learning_rate": 1.4239221452528873e-07, + "loss": 0.7514, + "step": 4924 + }, + { + "epoch": 0.95, + "learning_rate": 1.4134576639989294e-07, + "loss": 0.7651, + "step": 4925 + }, + { + "epoch": 0.95, + "learning_rate": 1.403031503022867e-07, + "loss": 0.7789, + "step": 4926 + }, + { + "epoch": 0.95, + "learning_rate": 1.3926436663772912e-07, + "loss": 0.7442, + "step": 4927 + }, + { + "epoch": 0.95, + "learning_rate": 1.3822941580999393e-07, + "loss": 1.1092, + "step": 4928 + }, + { + "epoch": 0.95, + "learning_rate": 1.3719829822136267e-07, + "loss": 0.736, + "step": 4929 + }, + { + "epoch": 0.95, + "learning_rate": 1.3617101427262913e-07, + "loss": 0.6856, + "step": 4930 + }, + { + "epoch": 0.95, + "learning_rate": 1.3514756436309173e-07, + "loss": 0.7439, + "step": 4931 + }, + { + "epoch": 0.95, + "learning_rate": 1.3412794889056445e-07, + "loss": 0.7714, + "step": 4932 + }, + { + "epoch": 0.95, + "learning_rate": 1.3311216825136919e-07, + "loss": 0.7706, + "step": 4933 + }, + { + "epoch": 0.95, + "learning_rate": 1.3210022284033563e-07, + "loss": 0.7619, + "step": 4934 + }, + { + "epoch": 0.95, + "learning_rate": 1.3109211305080361e-07, + "loss": 0.7509, + "step": 4935 + }, + { + "epoch": 0.95, + "learning_rate": 1.300878392746241e-07, + "loss": 0.6701, + "step": 4936 + }, + { + "epoch": 0.95, + "learning_rate": 1.2908740190215152e-07, + "loss": 0.7258, + "step": 4937 + }, + { + "epoch": 0.95, + "learning_rate": 1.2809080132225704e-07, + "loss": 0.7529, + "step": 4938 + }, + { + "epoch": 0.95, + "learning_rate": 1.2709803792231302e-07, + "loss": 0.7512, + "step": 4939 + }, + { + "epoch": 0.95, + "learning_rate": 1.261091120882041e-07, + "loss": 0.7753, + "step": 4940 + }, + { + "epoch": 0.95, + "learning_rate": 1.251240242043239e-07, + "loss": 0.7266, + "step": 4941 + }, + { + "epoch": 0.95, + "learning_rate": 1.241427746535717e-07, + "loss": 0.7664, + "step": 4942 + }, + { + "epoch": 0.95, + "learning_rate": 1.2316536381735577e-07, + "loss": 0.7617, + "step": 4943 + }, + { + "epoch": 0.95, + "learning_rate": 1.221917920755933e-07, + "loss": 0.786, + "step": 4944 + }, + { + "epoch": 0.95, + "learning_rate": 1.2122205980671042e-07, + "loss": 0.7614, + "step": 4945 + }, + { + "epoch": 0.95, + "learning_rate": 1.202561673876357e-07, + "loss": 0.796, + "step": 4946 + }, + { + "epoch": 0.95, + "learning_rate": 1.1929411519380985e-07, + "loss": 0.7744, + "step": 4947 + }, + { + "epoch": 0.95, + "learning_rate": 1.1833590359918045e-07, + "loss": 0.7524, + "step": 4948 + }, + { + "epoch": 0.95, + "learning_rate": 1.1738153297619959e-07, + "loss": 0.7542, + "step": 4949 + }, + { + "epoch": 0.95, + "learning_rate": 1.1643100369582938e-07, + "loss": 0.7964, + "step": 4950 + }, + { + "epoch": 0.95, + "learning_rate": 1.1548431612753652e-07, + "loss": 0.764, + "step": 4951 + }, + { + "epoch": 0.95, + "learning_rate": 1.1454147063929776e-07, + "loss": 0.793, + "step": 4952 + }, + { + "epoch": 0.95, + "learning_rate": 1.1360246759759108e-07, + "loss": 0.7901, + "step": 4953 + }, + { + "epoch": 0.95, + "learning_rate": 1.1266730736740561e-07, + "loss": 0.7746, + "step": 4954 + }, + { + "epoch": 0.95, + "learning_rate": 1.1173599031223614e-07, + "loss": 0.7802, + "step": 4955 + }, + { + "epoch": 0.95, + "learning_rate": 1.108085167940809e-07, + "loss": 0.7984, + "step": 4956 + }, + { + "epoch": 0.95, + "learning_rate": 1.0988488717344593e-07, + "loss": 0.7557, + "step": 4957 + }, + { + "epoch": 0.95, + "learning_rate": 1.0896510180934405e-07, + "loss": 0.7667, + "step": 4958 + }, + { + "epoch": 0.95, + "learning_rate": 1.0804916105929375e-07, + "loss": 0.6998, + "step": 4959 + }, + { + "epoch": 0.95, + "learning_rate": 1.0713706527931688e-07, + "loss": 0.7649, + "step": 4960 + }, + { + "epoch": 0.95, + "learning_rate": 1.0622881482394098e-07, + "loss": 0.772, + "step": 4961 + }, + { + "epoch": 0.96, + "learning_rate": 1.0532441004620364e-07, + "loss": 0.7675, + "step": 4962 + }, + { + "epoch": 0.96, + "learning_rate": 1.0442385129764143e-07, + "loss": 0.8122, + "step": 4963 + }, + { + "epoch": 0.96, + "learning_rate": 1.035271389282999e-07, + "loss": 0.724, + "step": 4964 + }, + { + "epoch": 0.96, + "learning_rate": 1.0263427328672693e-07, + "loss": 0.7611, + "step": 4965 + }, + { + "epoch": 0.96, + "learning_rate": 1.017452547199782e-07, + "loss": 0.7678, + "step": 4966 + }, + { + "epoch": 0.96, + "learning_rate": 1.0086008357361177e-07, + "loss": 0.7605, + "step": 4967 + }, + { + "epoch": 0.96, + "learning_rate": 9.997876019169017e-08, + "loss": 0.7659, + "step": 4968 + }, + { + "epoch": 0.96, + "learning_rate": 9.910128491678273e-08, + "loss": 0.763, + "step": 4969 + }, + { + "epoch": 0.96, + "learning_rate": 9.822765808995993e-08, + "loss": 0.7883, + "step": 4970 + }, + { + "epoch": 0.96, + "learning_rate": 9.735788005079793e-08, + "loss": 0.7382, + "step": 4971 + }, + { + "epoch": 0.96, + "learning_rate": 9.649195113737741e-08, + "loss": 0.7565, + "step": 4972 + }, + { + "epoch": 0.96, + "learning_rate": 9.562987168628135e-08, + "loss": 0.6611, + "step": 4973 + }, + { + "epoch": 0.96, + "learning_rate": 9.477164203259725e-08, + "loss": 0.7645, + "step": 4974 + }, + { + "epoch": 0.96, + "learning_rate": 9.391726250991717e-08, + "loss": 0.7298, + "step": 4975 + }, + { + "epoch": 0.96, + "learning_rate": 9.306673345033546e-08, + "loss": 0.8122, + "step": 4976 + }, + { + "epoch": 0.96, + "learning_rate": 9.222005518444876e-08, + "loss": 0.778, + "step": 4977 + }, + { + "epoch": 0.96, + "learning_rate": 9.13772280413605e-08, + "loss": 0.7563, + "step": 4978 + }, + { + "epoch": 0.96, + "learning_rate": 9.053825234867308e-08, + "loss": 0.7842, + "step": 4979 + }, + { + "epoch": 0.96, + "learning_rate": 8.970312843249563e-08, + "loss": 0.8144, + "step": 4980 + }, + { + "epoch": 0.96, + "learning_rate": 8.887185661743625e-08, + "loss": 0.781, + "step": 4981 + }, + { + "epoch": 0.96, + "learning_rate": 8.80444372266076e-08, + "loss": 0.7158, + "step": 4982 + }, + { + "epoch": 0.96, + "learning_rate": 8.722087058162576e-08, + "loss": 0.7941, + "step": 4983 + }, + { + "epoch": 0.96, + "learning_rate": 8.64011570026102e-08, + "loss": 0.7615, + "step": 4984 + }, + { + "epoch": 0.96, + "learning_rate": 8.558529680817829e-08, + "loss": 0.7395, + "step": 4985 + }, + { + "epoch": 0.96, + "learning_rate": 8.477329031545301e-08, + "loss": 0.8054, + "step": 4986 + }, + { + "epoch": 0.96, + "learning_rate": 8.396513784005855e-08, + "loss": 0.7383, + "step": 4987 + }, + { + "epoch": 0.96, + "learning_rate": 8.316083969612254e-08, + "loss": 0.7754, + "step": 4988 + }, + { + "epoch": 0.96, + "learning_rate": 8.236039619627267e-08, + "loss": 0.8049, + "step": 4989 + }, + { + "epoch": 0.96, + "learning_rate": 8.156380765163785e-08, + "loss": 0.8112, + "step": 4990 + }, + { + "epoch": 0.96, + "learning_rate": 8.07710743718504e-08, + "loss": 0.7303, + "step": 4991 + }, + { + "epoch": 0.96, + "learning_rate": 7.99821966650427e-08, + "loss": 0.6409, + "step": 4992 + }, + { + "epoch": 0.96, + "learning_rate": 7.919717483784838e-08, + "loss": 0.748, + "step": 4993 + }, + { + "epoch": 0.96, + "learning_rate": 7.841600919540449e-08, + "loss": 0.7293, + "step": 4994 + }, + { + "epoch": 0.96, + "learning_rate": 7.763870004134811e-08, + "loss": 0.7471, + "step": 4995 + }, + { + "epoch": 0.96, + "learning_rate": 7.686524767781423e-08, + "loss": 0.7423, + "step": 4996 + }, + { + "epoch": 0.96, + "learning_rate": 7.609565240544459e-08, + "loss": 0.7617, + "step": 4997 + }, + { + "epoch": 0.96, + "learning_rate": 7.532991452337435e-08, + "loss": 0.7406, + "step": 4998 + }, + { + "epoch": 0.96, + "learning_rate": 7.456803432924764e-08, + "loss": 0.738, + "step": 4999 + }, + { + "epoch": 0.96, + "learning_rate": 7.381001211920202e-08, + "loss": 0.7343, + "step": 5000 + }, + { + "epoch": 0.96, + "learning_rate": 7.305584818787959e-08, + "loss": 0.7614, + "step": 5001 + }, + { + "epoch": 0.96, + "learning_rate": 7.23055428284225e-08, + "loss": 0.792, + "step": 5002 + }, + { + "epoch": 0.96, + "learning_rate": 7.15590963324686e-08, + "loss": 0.7312, + "step": 5003 + }, + { + "epoch": 0.96, + "learning_rate": 7.081650899016246e-08, + "loss": 0.7303, + "step": 5004 + }, + { + "epoch": 0.96, + "learning_rate": 7.007778109014429e-08, + "loss": 0.6681, + "step": 5005 + }, + { + "epoch": 0.96, + "learning_rate": 6.934291291955664e-08, + "loss": 0.8121, + "step": 5006 + }, + { + "epoch": 0.96, + "learning_rate": 6.861190476403767e-08, + "loss": 0.7581, + "step": 5007 + }, + { + "epoch": 0.96, + "learning_rate": 6.788475690773123e-08, + "loss": 0.7296, + "step": 5008 + }, + { + "epoch": 0.96, + "learning_rate": 6.716146963327452e-08, + "loss": 0.7386, + "step": 5009 + }, + { + "epoch": 0.96, + "learning_rate": 6.644204322180825e-08, + "loss": 0.802, + "step": 5010 + }, + { + "epoch": 0.96, + "learning_rate": 6.572647795297205e-08, + "loss": 0.7552, + "step": 5011 + }, + { + "epoch": 0.96, + "learning_rate": 6.501477410490231e-08, + "loss": 0.775, + "step": 5012 + }, + { + "epoch": 0.96, + "learning_rate": 6.430693195423665e-08, + "loss": 0.7562, + "step": 5013 + }, + { + "epoch": 0.97, + "learning_rate": 6.360295177611164e-08, + "loss": 0.736, + "step": 5014 + }, + { + "epoch": 0.97, + "learning_rate": 6.290283384416063e-08, + "loss": 0.8221, + "step": 5015 + }, + { + "epoch": 0.97, + "learning_rate": 6.220657843051925e-08, + "loss": 0.7855, + "step": 5016 + }, + { + "epoch": 0.97, + "learning_rate": 6.15141858058188e-08, + "loss": 0.7374, + "step": 5017 + }, + { + "epoch": 0.97, + "learning_rate": 6.082565623918957e-08, + "loss": 0.8099, + "step": 5018 + }, + { + "epoch": 0.97, + "learning_rate": 6.014098999826301e-08, + "loss": 1.1987, + "step": 5019 + }, + { + "epoch": 0.97, + "learning_rate": 5.9460187349162923e-08, + "loss": 0.7369, + "step": 5020 + }, + { + "epoch": 0.97, + "learning_rate": 5.8783248556518736e-08, + "loss": 0.7591, + "step": 5021 + }, + { + "epoch": 0.97, + "learning_rate": 5.81101738834533e-08, + "loss": 0.7444, + "step": 5022 + }, + { + "epoch": 0.97, + "learning_rate": 5.744096359158846e-08, + "loss": 0.7401, + "step": 5023 + }, + { + "epoch": 0.97, + "learning_rate": 5.6775617941042803e-08, + "loss": 0.7683, + "step": 5024 + }, + { + "epoch": 0.97, + "learning_rate": 5.6114137190436124e-08, + "loss": 0.7349, + "step": 5025 + }, + { + "epoch": 0.97, + "learning_rate": 5.545652159688275e-08, + "loss": 0.8028, + "step": 5026 + }, + { + "epoch": 0.97, + "learning_rate": 5.480277141599599e-08, + "loss": 0.7562, + "step": 5027 + }, + { + "epoch": 0.97, + "learning_rate": 5.4152886901888136e-08, + "loss": 0.7417, + "step": 5028 + }, + { + "epoch": 0.97, + "learning_rate": 5.350686830716378e-08, + "loss": 1.1915, + "step": 5029 + }, + { + "epoch": 0.97, + "learning_rate": 5.286471588293096e-08, + "loss": 0.7543, + "step": 5030 + }, + { + "epoch": 0.97, + "learning_rate": 5.2226429878793336e-08, + "loss": 0.7666, + "step": 5031 + }, + { + "epoch": 0.97, + "learning_rate": 5.1592010542846905e-08, + "loss": 0.7587, + "step": 5032 + }, + { + "epoch": 0.97, + "learning_rate": 5.096145812169106e-08, + "loss": 0.7902, + "step": 5033 + }, + { + "epoch": 0.97, + "learning_rate": 5.0334772860418656e-08, + "loss": 0.79, + "step": 5034 + }, + { + "epoch": 0.97, + "learning_rate": 4.971195500262038e-08, + "loss": 0.7097, + "step": 5035 + }, + { + "epoch": 0.97, + "learning_rate": 4.9093004790384816e-08, + "loss": 0.7, + "step": 5036 + }, + { + "epoch": 0.97, + "learning_rate": 4.8477922464293944e-08, + "loss": 0.7177, + "step": 5037 + }, + { + "epoch": 0.97, + "learning_rate": 4.7866708263429874e-08, + "loss": 0.7796, + "step": 5038 + }, + { + "epoch": 0.97, + "learning_rate": 4.7259362425369215e-08, + "loss": 0.8006, + "step": 5039 + }, + { + "epoch": 0.97, + "learning_rate": 4.6655885186185357e-08, + "loss": 0.8165, + "step": 5040 + }, + { + "epoch": 0.97, + "learning_rate": 4.605627678044733e-08, + "loss": 0.7865, + "step": 5041 + }, + { + "epoch": 0.97, + "learning_rate": 4.546053744122203e-08, + "loss": 0.7299, + "step": 5042 + }, + { + "epoch": 0.97, + "learning_rate": 4.48686674000709e-08, + "loss": 0.7515, + "step": 5043 + }, + { + "epoch": 0.97, + "learning_rate": 4.4280666887051016e-08, + "loss": 0.7359, + "step": 5044 + }, + { + "epoch": 0.97, + "learning_rate": 4.369653613071845e-08, + "loss": 0.7298, + "step": 5045 + }, + { + "epoch": 0.97, + "learning_rate": 4.311627535812157e-08, + "loss": 1.2002, + "step": 5046 + }, + { + "epoch": 0.97, + "learning_rate": 4.253988479480664e-08, + "loss": 0.763, + "step": 5047 + }, + { + "epoch": 0.97, + "learning_rate": 4.1967364664814433e-08, + "loss": 0.7567, + "step": 5048 + }, + { + "epoch": 0.97, + "learning_rate": 4.1398715190681394e-08, + "loss": 0.7519, + "step": 5049 + }, + { + "epoch": 0.97, + "learning_rate": 4.0833936593439594e-08, + "loss": 0.8025, + "step": 5050 + }, + { + "epoch": 0.97, + "learning_rate": 4.0273029092617877e-08, + "loss": 0.7294, + "step": 5051 + }, + { + "epoch": 0.97, + "learning_rate": 3.971599290623851e-08, + "loss": 0.7354, + "step": 5052 + }, + { + "epoch": 0.97, + "learning_rate": 3.916282825081941e-08, + "loss": 0.7579, + "step": 5053 + }, + { + "epoch": 0.97, + "learning_rate": 3.861353534137524e-08, + "loss": 0.7925, + "step": 5054 + }, + { + "epoch": 0.97, + "learning_rate": 3.806811439141189e-08, + "loss": 0.7644, + "step": 5055 + }, + { + "epoch": 0.97, + "learning_rate": 3.752656561293644e-08, + "loss": 0.8024, + "step": 5056 + }, + { + "epoch": 0.97, + "learning_rate": 3.6988889216443833e-08, + "loss": 0.7555, + "step": 5057 + }, + { + "epoch": 0.97, + "learning_rate": 3.645508541092802e-08, + "loss": 1.1831, + "step": 5058 + }, + { + "epoch": 0.97, + "learning_rate": 3.592515440387745e-08, + "loss": 0.7767, + "step": 5059 + }, + { + "epoch": 0.97, + "learning_rate": 3.5399096401275144e-08, + "loss": 0.7541, + "step": 5060 + }, + { + "epoch": 0.97, + "learning_rate": 3.487691160759643e-08, + "loss": 0.7744, + "step": 5061 + }, + { + "epoch": 0.97, + "learning_rate": 3.43586002258145e-08, + "loss": 0.7295, + "step": 5062 + }, + { + "epoch": 0.97, + "learning_rate": 3.384416245739486e-08, + "loss": 0.7802, + "step": 5063 + }, + { + "epoch": 0.97, + "learning_rate": 3.333359850229756e-08, + "loss": 0.7537, + "step": 5064 + }, + { + "epoch": 0.97, + "learning_rate": 3.28269085589783e-08, + "loss": 0.7715, + "step": 5065 + }, + { + "epoch": 0.98, + "learning_rate": 3.2324092824383976e-08, + "loss": 0.7468, + "step": 5066 + }, + { + "epoch": 0.98, + "learning_rate": 3.1825151493959374e-08, + "loss": 0.7589, + "step": 5067 + }, + { + "epoch": 0.98, + "learning_rate": 3.1330084761639344e-08, + "loss": 0.804, + "step": 5068 + }, + { + "epoch": 0.98, + "learning_rate": 3.083889281985664e-08, + "loss": 0.7823, + "step": 5069 + }, + { + "epoch": 0.98, + "learning_rate": 3.0351575859535186e-08, + "loss": 0.7323, + "step": 5070 + }, + { + "epoch": 0.98, + "learning_rate": 2.986813407009459e-08, + "loss": 0.8072, + "step": 5071 + }, + { + "epoch": 0.98, + "learning_rate": 2.938856763944453e-08, + "loss": 0.7528, + "step": 5072 + }, + { + "epoch": 0.98, + "learning_rate": 2.891287675399368e-08, + "loss": 0.7573, + "step": 5073 + }, + { + "epoch": 0.98, + "learning_rate": 2.8441061598640796e-08, + "loss": 0.7532, + "step": 5074 + }, + { + "epoch": 0.98, + "learning_rate": 2.797312235677807e-08, + "loss": 0.7551, + "step": 5075 + }, + { + "epoch": 0.98, + "learning_rate": 2.7509059210293344e-08, + "loss": 0.8166, + "step": 5076 + }, + { + "epoch": 0.98, + "learning_rate": 2.7048872339565657e-08, + "loss": 0.7165, + "step": 5077 + }, + { + "epoch": 0.98, + "learning_rate": 2.6592561923468596e-08, + "loss": 0.7243, + "step": 5078 + }, + { + "epoch": 0.98, + "learning_rate": 2.614012813936695e-08, + "loss": 0.759, + "step": 5079 + }, + { + "epoch": 0.98, + "learning_rate": 2.5691571163123373e-08, + "loss": 0.8111, + "step": 5080 + }, + { + "epoch": 0.98, + "learning_rate": 2.5246891169088406e-08, + "loss": 0.7545, + "step": 5081 + }, + { + "epoch": 0.98, + "learning_rate": 2.4806088330108223e-08, + "loss": 1.1517, + "step": 5082 + }, + { + "epoch": 0.98, + "learning_rate": 2.436916281752133e-08, + "loss": 0.7372, + "step": 5083 + }, + { + "epoch": 0.98, + "learning_rate": 2.393611480115854e-08, + "loss": 0.7285, + "step": 5084 + }, + { + "epoch": 0.98, + "learning_rate": 2.3506944449346315e-08, + "loss": 1.1966, + "step": 5085 + }, + { + "epoch": 0.98, + "learning_rate": 2.3081651928900107e-08, + "loss": 1.2066, + "step": 5086 + }, + { + "epoch": 0.98, + "learning_rate": 2.2660237405131013e-08, + "loss": 0.8117, + "step": 5087 + }, + { + "epoch": 0.98, + "learning_rate": 2.224270104184134e-08, + "loss": 0.8087, + "step": 5088 + }, + { + "epoch": 0.98, + "learning_rate": 2.18290430013246e-08, + "loss": 0.7718, + "step": 5089 + }, + { + "epoch": 0.98, + "learning_rate": 2.1419263444369954e-08, + "loss": 1.1358, + "step": 5090 + }, + { + "epoch": 0.98, + "learning_rate": 2.1013362530256655e-08, + "loss": 0.7715, + "step": 5091 + }, + { + "epoch": 0.98, + "learning_rate": 2.0611340416757387e-08, + "loss": 0.7936, + "step": 5092 + }, + { + "epoch": 0.98, + "learning_rate": 2.021319726013604e-08, + "loss": 1.1225, + "step": 5093 + }, + { + "epoch": 0.98, + "learning_rate": 1.981893321515105e-08, + "loss": 0.7992, + "step": 5094 + }, + { + "epoch": 0.98, + "learning_rate": 1.9428548435052043e-08, + "loss": 0.7349, + "step": 5095 + }, + { + "epoch": 0.98, + "learning_rate": 1.9042043071577642e-08, + "loss": 0.7987, + "step": 5096 + }, + { + "epoch": 0.98, + "learning_rate": 1.865941727496434e-08, + "loss": 0.719, + "step": 5097 + }, + { + "epoch": 0.98, + "learning_rate": 1.8280671193935394e-08, + "loss": 0.7152, + "step": 5098 + }, + { + "epoch": 0.98, + "learning_rate": 1.7905804975708596e-08, + "loss": 0.7938, + "step": 5099 + }, + { + "epoch": 0.98, + "learning_rate": 1.7534818765994055e-08, + "loss": 0.8135, + "step": 5100 + }, + { + "epoch": 0.98, + "learning_rate": 1.716771270899198e-08, + "loss": 0.8098, + "step": 5101 + }, + { + "epoch": 0.98, + "learning_rate": 1.6804486947397112e-08, + "loss": 0.7619, + "step": 5102 + }, + { + "epoch": 0.98, + "learning_rate": 1.6445141622392082e-08, + "loss": 0.7428, + "step": 5103 + }, + { + "epoch": 0.98, + "learning_rate": 1.6089676873654038e-08, + "loss": 0.7349, + "step": 5104 + }, + { + "epoch": 0.98, + "learning_rate": 1.573809283935135e-08, + "loss": 0.7189, + "step": 5105 + }, + { + "epoch": 0.98, + "learning_rate": 1.5390389656142478e-08, + "loss": 0.723, + "step": 5106 + }, + { + "epoch": 0.98, + "learning_rate": 1.5046567459181537e-08, + "loss": 0.7431, + "step": 5107 + }, + { + "epoch": 0.98, + "learning_rate": 1.470662638210718e-08, + "loss": 1.1355, + "step": 5108 + }, + { + "epoch": 0.98, + "learning_rate": 1.4370566557055932e-08, + "loss": 0.759, + "step": 5109 + }, + { + "epoch": 0.98, + "learning_rate": 1.403838811465219e-08, + "loss": 0.7652, + "step": 5110 + }, + { + "epoch": 0.98, + "learning_rate": 1.3710091184012674e-08, + "loss": 0.7237, + "step": 5111 + }, + { + "epoch": 0.98, + "learning_rate": 1.338567589274642e-08, + "loss": 0.7665, + "step": 5112 + }, + { + "epoch": 0.98, + "learning_rate": 1.3065142366951445e-08, + "loss": 0.7995, + "step": 5113 + }, + { + "epoch": 0.98, + "learning_rate": 1.2748490731219198e-08, + "loss": 0.7983, + "step": 5114 + }, + { + "epoch": 0.98, + "learning_rate": 1.2435721108630116e-08, + "loss": 1.2223, + "step": 5115 + }, + { + "epoch": 0.98, + "learning_rate": 1.2126833620756951e-08, + "loss": 0.7749, + "step": 5116 + }, + { + "epoch": 0.98, + "learning_rate": 1.1821828387663658e-08, + "loss": 0.7648, + "step": 5117 + }, + { + "epoch": 0.99, + "learning_rate": 1.1520705527904298e-08, + "loss": 0.7749, + "step": 5118 + }, + { + "epoch": 0.99, + "learning_rate": 1.1223465158526347e-08, + "loss": 0.7707, + "step": 5119 + }, + { + "epoch": 0.99, + "learning_rate": 1.093010739506295e-08, + "loss": 0.6572, + "step": 5120 + }, + { + "epoch": 0.99, + "learning_rate": 1.0640632351544e-08, + "loss": 0.7411, + "step": 5121 + }, + { + "epoch": 0.99, + "learning_rate": 1.0355040140486162e-08, + "loss": 0.7263, + "step": 5122 + }, + { + "epoch": 0.99, + "learning_rate": 1.0073330872898413e-08, + "loss": 0.7994, + "step": 5123 + }, + { + "epoch": 0.99, + "learning_rate": 9.79550465828094e-09, + "loss": 0.7904, + "step": 5124 + }, + { + "epoch": 0.99, + "learning_rate": 9.52156160462292e-09, + "loss": 0.7247, + "step": 5125 + }, + { + "epoch": 0.99, + "learning_rate": 9.25150181840584e-09, + "loss": 0.7436, + "step": 5126 + }, + { + "epoch": 0.99, + "learning_rate": 8.985325404601287e-09, + "loss": 0.6991, + "step": 5127 + }, + { + "epoch": 0.99, + "learning_rate": 8.723032466669834e-09, + "loss": 0.7339, + "step": 5128 + }, + { + "epoch": 0.99, + "learning_rate": 8.464623106565484e-09, + "loss": 0.784, + "step": 5129 + }, + { + "epoch": 0.99, + "learning_rate": 8.210097424731223e-09, + "loss": 0.7535, + "step": 5130 + }, + { + "epoch": 0.99, + "learning_rate": 7.959455520099025e-09, + "loss": 0.7687, + "step": 5131 + }, + { + "epoch": 0.99, + "learning_rate": 7.71269749009318e-09, + "loss": 0.7762, + "step": 5132 + }, + { + "epoch": 0.99, + "learning_rate": 7.469823430628076e-09, + "loss": 0.7878, + "step": 5133 + }, + { + "epoch": 0.99, + "learning_rate": 7.230833436107087e-09, + "loss": 0.7439, + "step": 5134 + }, + { + "epoch": 0.99, + "learning_rate": 6.9957275994270156e-09, + "loss": 0.7438, + "step": 5135 + }, + { + "epoch": 0.99, + "learning_rate": 6.764506011970318e-09, + "loss": 0.7562, + "step": 5136 + }, + { + "epoch": 0.99, + "learning_rate": 6.537168763613988e-09, + "loss": 0.679, + "step": 5137 + }, + { + "epoch": 0.99, + "learning_rate": 6.3137159427217874e-09, + "loss": 0.7077, + "step": 5138 + }, + { + "epoch": 0.99, + "learning_rate": 6.094147636150904e-09, + "loss": 1.1772, + "step": 5139 + }, + { + "epoch": 0.99, + "learning_rate": 5.878463929245293e-09, + "loss": 0.7644, + "step": 5140 + }, + { + "epoch": 0.99, + "learning_rate": 5.666664905840114e-09, + "loss": 0.8001, + "step": 5141 + }, + { + "epoch": 0.99, + "learning_rate": 5.458750648262845e-09, + "loss": 0.7552, + "step": 5142 + }, + { + "epoch": 0.99, + "learning_rate": 5.254721237327731e-09, + "loss": 0.7357, + "step": 5143 + }, + { + "epoch": 0.99, + "learning_rate": 5.054576752341333e-09, + "loss": 0.7615, + "step": 5144 + }, + { + "epoch": 0.99, + "learning_rate": 4.85831727109809e-09, + "loss": 0.844, + "step": 5145 + }, + { + "epoch": 0.99, + "learning_rate": 4.665942869884755e-09, + "loss": 1.0962, + "step": 5146 + }, + { + "epoch": 0.99, + "learning_rate": 4.477453623474848e-09, + "loss": 0.7545, + "step": 5147 + }, + { + "epoch": 0.99, + "learning_rate": 4.292849605134208e-09, + "loss": 0.7679, + "step": 5148 + }, + { + "epoch": 0.99, + "learning_rate": 4.112130886619881e-09, + "loss": 0.7403, + "step": 5149 + }, + { + "epoch": 0.99, + "learning_rate": 3.9352975381734546e-09, + "loss": 0.7395, + "step": 5150 + }, + { + "epoch": 0.99, + "learning_rate": 3.762349628532169e-09, + "loss": 0.8117, + "step": 5151 + }, + { + "epoch": 0.99, + "learning_rate": 3.5932872249178077e-09, + "loss": 0.7709, + "step": 5152 + }, + { + "epoch": 0.99, + "learning_rate": 3.4281103930466906e-09, + "loss": 0.734, + "step": 5153 + }, + { + "epoch": 0.99, + "learning_rate": 3.2668191971207963e-09, + "loss": 0.7531, + "step": 5154 + }, + { + "epoch": 0.99, + "learning_rate": 3.1094136998355286e-09, + "loss": 0.7323, + "step": 5155 + }, + { + "epoch": 0.99, + "learning_rate": 2.9558939623719475e-09, + "loss": 0.7568, + "step": 5156 + }, + { + "epoch": 0.99, + "learning_rate": 2.8062600444034306e-09, + "loss": 0.7825, + "step": 5157 + }, + { + "epoch": 0.99, + "learning_rate": 2.6605120040923414e-09, + "loss": 0.8128, + "step": 5158 + }, + { + "epoch": 0.99, + "learning_rate": 2.518649898090031e-09, + "loss": 0.7974, + "step": 5159 + }, + { + "epoch": 0.99, + "learning_rate": 2.3806737815379456e-09, + "loss": 0.8189, + "step": 5160 + }, + { + "epoch": 0.99, + "learning_rate": 2.246583708067629e-09, + "loss": 0.7463, + "step": 5161 + }, + { + "epoch": 0.99, + "learning_rate": 2.1163797297996113e-09, + "loss": 0.7655, + "step": 5162 + }, + { + "epoch": 0.99, + "learning_rate": 1.990061897342299e-09, + "loss": 1.0577, + "step": 5163 + }, + { + "epoch": 0.99, + "learning_rate": 1.867630259796416e-09, + "loss": 0.8006, + "step": 5164 + }, + { + "epoch": 0.99, + "learning_rate": 1.7490848647494507e-09, + "loss": 0.7563, + "step": 5165 + }, + { + "epoch": 0.99, + "learning_rate": 1.6344257582812105e-09, + "loss": 0.7537, + "step": 5166 + }, + { + "epoch": 0.99, + "learning_rate": 1.5236529849582683e-09, + "loss": 0.7642, + "step": 5167 + }, + { + "epoch": 0.99, + "learning_rate": 1.416766587838403e-09, + "loss": 0.7086, + "step": 5168 + }, + { + "epoch": 0.99, + "learning_rate": 1.3137666084672706e-09, + "loss": 0.7314, + "step": 5169 + }, + { + "epoch": 1.0, + "learning_rate": 1.2146530868806238e-09, + "loss": 0.7448, + "step": 5170 + }, + { + "epoch": 1.0, + "learning_rate": 1.1194260616043118e-09, + "loss": 0.776, + "step": 5171 + }, + { + "epoch": 1.0, + "learning_rate": 1.0280855696520597e-09, + "loss": 0.7263, + "step": 5172 + }, + { + "epoch": 1.0, + "learning_rate": 9.4063164652769e-10, + "loss": 0.7817, + "step": 5173 + }, + { + "epoch": 1.0, + "learning_rate": 8.57064326225121e-10, + "loss": 0.7847, + "step": 5174 + }, + { + "epoch": 1.0, + "learning_rate": 7.77383641225038e-10, + "loss": 0.7585, + "step": 5175 + }, + { + "epoch": 1.0, + "learning_rate": 7.015896225004426e-10, + "loss": 0.7045, + "step": 5176 + }, + { + "epoch": 1.0, + "learning_rate": 6.296822995122132e-10, + "loss": 0.7477, + "step": 5177 + }, + { + "epoch": 1.0, + "learning_rate": 5.616617002102142e-10, + "loss": 0.7809, + "step": 5178 + }, + { + "epoch": 1.0, + "learning_rate": 4.97527851033297e-10, + "loss": 0.8178, + "step": 5179 + }, + { + "epoch": 1.0, + "learning_rate": 4.372807769115195e-10, + "loss": 0.6968, + "step": 5180 + }, + { + "epoch": 1.0, + "learning_rate": 3.809205012605954e-10, + "loss": 0.753, + "step": 5181 + }, + { + "epoch": 1.0, + "learning_rate": 3.2844704598966603e-10, + "loss": 0.7941, + "step": 5182 + }, + { + "epoch": 1.0, + "learning_rate": 2.798604314946385e-10, + "loss": 0.7378, + "step": 5183 + }, + { + "epoch": 1.0, + "learning_rate": 2.351606766592962e-10, + "loss": 0.7361, + "step": 5184 + }, + { + "epoch": 1.0, + "learning_rate": 1.9434779885973975e-10, + "loss": 0.7918, + "step": 5185 + }, + { + "epoch": 1.0, + "learning_rate": 1.5742181395994594e-10, + "loss": 0.7757, + "step": 5186 + }, + { + "epoch": 1.0, + "learning_rate": 1.2438273631176778e-10, + "loss": 0.7909, + "step": 5187 + }, + { + "epoch": 1.0, + "learning_rate": 9.523057875826525e-11, + "loss": 0.8029, + "step": 5188 + }, + { + "epoch": 1.0, + "learning_rate": 6.996535263148473e-11, + "loss": 0.8089, + "step": 5189 + }, + { + "epoch": 1.0, + "learning_rate": 4.858706775023869e-11, + "loss": 0.7925, + "step": 5190 + }, + { + "epoch": 1.0, + "learning_rate": 3.109573242565667e-11, + "loss": 0.7691, + "step": 5191 + }, + { + "epoch": 1.0, + "learning_rate": 1.749135345563424e-11, + "loss": 0.7688, + "step": 5192 + }, + { + "epoch": 1.0, + "learning_rate": 7.773936128163684e-12, + "loss": 0.7788, + "step": 5193 + }, + { + "epoch": 1.0, + "learning_rate": 1.9434842213339466e-12, + "loss": 0.6648, + "step": 5194 + }, + { + "epoch": 1.0, + "learning_rate": 0.0, + "loss": 1.0699, + "step": 5195 + }, + { + "epoch": 1.0, + "step": 5195, + "total_flos": 9123588792123392.0, + "train_loss": 0.8619271928123606, + "train_runtime": 48756.4895, + "train_samples_per_second": 13.638, + "train_steps_per_second": 0.107 + } + ], + "logging_steps": 1.0, + "max_steps": 5195, + "num_input_tokens_seen": 0, + "num_train_epochs": 1, + "save_steps": 50000, + "total_flos": 9123588792123392.0, + "train_batch_size": 8, + "trial_name": null, + "trial_params": null +} diff --git a/training_args.bin b/training_args.bin new file mode 100644 index 0000000000000000000000000000000000000000..e050dbfa2cb6960a55487a98df47468d3ad0f147 --- /dev/null +++ b/training_args.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bfd659973b0b2a125146d288ce2386a283dd4e1fb31bf823496261c7469df80e +size 6776