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lapp0
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distily_bench_obj_cross

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gpt_neo
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1 Parent(s): 5e0d2f0

Training in progress, step 61875

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  1. README.md +32 -32
  2. logs/attn_loss_fn=mse, attn_weight=10.0, hs_loss_fn=raw_mse, hs_weight=10.0, learning_rate=0.004, warmup_ratio=0.1/events.out.tfevents.1723776807.93d6cbb3ad53 +3 -0
  3. logs/attn_loss_fn=mse, attn_weight=10.0, hs_loss_fn=raw_mse, hs_weight=10.0, learning_rate=0.004, warmup_ratio=0/events.out.tfevents.1723776606.93d6cbb3ad53 +2 -2
  4. model.safetensors +1 -1
  5. training_args.bin +1 -1
README.md CHANGED
@@ -15,14 +15,14 @@ This student model is distilled from the teacher model [roneneldan/TinyStories-3
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  The [Distily](https://github.com/lapp0/distily) library was used for this distillation.
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  It achieves the following results on the evaluation set:
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- - eval_enwikippl: 198.0270
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- - eval_frwikippl: 17127.3379
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- - eval_zhwikippl: 63614.1797
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- - eval_tinystoriesppl: 21.7514
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- - eval_loss: 12.7123
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- - eval_runtime: 65.1143
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- - eval_samples_per_second: 76.788
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- - eval_steps_per_second: 9.599
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment.
@@ -47,7 +47,7 @@ More information needed
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  The following hyperparameters were used during training:
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  - distillation_objective: DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl, layer_mapper=None, projector=None), hs_loss_component=LossComponent(label=hs, weight=10.0, loss_fn=raw_mse, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=10.0, loss_fn=mse, layer_mapper=None, projector=None))
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  - train_embeddings: True
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- - learning_rate: 0.001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -62,31 +62,31 @@ Peak GPU Memory: 8.2666 GB
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  | step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | tinystoriesppl | zhwikippl |
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  | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
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  | **teacher eval** | | 169.9865 | 47377.9414 | | | | | 3.9789 | 4998.1294 |
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- | 0 | 0 | 14504.7236 | 73076.2578 | 17.7824 | 65.8473 | 75.933 | 9.492 | 6091.4858 | 69506.0391 |
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- | 3000 | 0.0485 | 198.0270 | 17127.3379 | 12.7127 | 65.1257 | 76.775 | 9.597 | 21.7514 | 63648.1641 |
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- | 6000 | 0.0970 | 197.0935 | 17088.7852 | 12.7124 | 65.0473 | 76.867 | 9.608 | 21.6429 | 63750.0977 |
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- | 9000 | 0.1455 | 198.0270 | 17127.3379 | 12.7123 | 65.1143 | 76.788 | 9.599 | 21.7514 | 63614.1797 |
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- | 12000 | 0.1939 | 197.4985 | 17098.4199 | 12.7128 | 65.0689 | 76.842 | 9.605 | 21.7173 | 63886.3086 |
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- | 15000 | 0.2424 | 197.3838 | 17122.5215 | 12.7128 | 65.1155 | 76.787 | 9.598 | 21.6850 | 63954.5195 |
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- | 18000 | 0.2909 | 197.9733 | 17108.0586 | 12.7130 | 65.0798 | 76.829 | 9.604 | 21.7865 | 63818.1680 |
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- | 21000 | 0.3394 | 197.1698 | 17103.2305 | 12.7134 | 65.0799 | 76.829 | 9.604 | 21.6322 | 64022.8672 |
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- | 24000 | 0.3879 | 197.8507 | 17117.7051 | 12.7131 | 65.1719 | 76.72 | 9.59 | 21.7757 | 63716.1211 |
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- | 27000 | 0.4364 | 197.6975 | 17127.3379 | 12.7131 | 65.1124 | 76.79 | 9.599 | 21.7191 | 63954.5195 |
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- | 30000 | 0.4848 | 197.3150 | 17079.1562 | 12.7131 | 65.1085 | 76.795 | 9.599 | 21.6904 | 63920.4375 |
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- | 33000 | 0.5333 | 197.6209 | 17103.2305 | 12.7129 | 65.2897 | 76.582 | 9.573 | 21.7191 | 63750.0977 |
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- | 36000 | 0.5818 | 198.3110 | 17127.3379 | 12.7122 | 65.5537 | 76.273 | 9.534 | 21.7883 | 63614.1797 |
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- | 39000 | 0.6303 | 198.2802 | 17127.3379 | 12.7128 | 65.2001 | 76.687 | 9.586 | 21.7721 | 63648.1641 |
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- | 42000 | 0.6788 | 197.9580 | 17127.3379 | 12.7130 | 65.4586 | 76.384 | 9.548 | 21.7433 | 63512.4648 |
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- | 45000 | 0.7273 | 198.2802 | 17108.0586 | 12.7129 | 65.2819 | 76.591 | 9.574 | 21.8009 | 63614.1797 |
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- | 48000 | 0.7758 | 197.5979 | 17098.4199 | 12.7125 | 65.1997 | 76.688 | 9.586 | 21.6940 | 63648.1641 |
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- | 51000 | 0.8242 | 198.2802 | 17127.3379 | 12.7120 | 65.5503 | 76.277 | 9.535 | 21.7892 | 63512.4648 |
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- | 54000 | 0.8727 | 198.2189 | 17127.3379 | 12.7129 | 65.3863 | 76.469 | 9.559 | 21.7811 | 63716.1211 |
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- | 57000 | 0.9212 | 199.1886 | 17136.9941 | 12.7133 | 65.1649 | 76.728 | 9.591 | 21.8759 | 63343.2148 |
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- | 60000 | 0.9697 | 197.3226 | 17122.5215 | 12.7127 | 65.2079 | 76.678 | 9.585 | 21.6886 | 63648.1641 |
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- | 61875 | 1.0 | 198.9419 | 17127.3379 | 12.7117 | 65.2766 | 76.597 | 9.575 | 21.8469 | 63648.1641 |
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  ### Framework versions
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  - Distily 0.2.0
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  - Transformers 4.44.0
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  - Pytorch 2.3.0
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- - Datasets 2.21.0
 
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  The [Distily](https://github.com/lapp0/distily) library was used for this distillation.
16
 
17
  It achieves the following results on the evaluation set:
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+ - eval_enwikippl: 149.5442
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+ - eval_frwikippl: 28142.1230
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+ - eval_zhwikippl: 243104.3594
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+ - eval_tinystoriesppl: 11.2706
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+ - eval_loss: 7.4452
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+ - eval_runtime: 66.0052
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+ - eval_samples_per_second: 75.752
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+ - eval_steps_per_second: 9.469
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27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
28
  should probably proofread and complete it, then remove this comment.
 
47
  The following hyperparameters were used during training:
48
  - distillation_objective: DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl, layer_mapper=None, projector=None), hs_loss_component=LossComponent(label=hs, weight=10.0, loss_fn=raw_mse, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=10.0, loss_fn=mse, layer_mapper=None, projector=None))
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  - train_embeddings: True
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+ - learning_rate: 0.004
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | tinystoriesppl | zhwikippl |
63
  | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
64
  | **teacher eval** | | 169.9865 | 47377.9414 | | | | | 3.9789 | 4998.1294 |
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+ | 0 | 0 | 58069.8203 | 77442.5625 | 18.5372 | 65.9335 | 75.834 | 9.479 | 46072.8867 | 100550.5078 |
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+ | 3000 | 0.0485 | 145.3919 | 28068.8965 | 7.4450 | 66.1007 | 75.642 | 9.455 | 10.8792 | 239563.0469 |
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+ | 6000 | 0.0970 | 143.8738 | 27934.7852 | 7.4443 | 65.9587 | 75.805 | 9.476 | 10.7017 | 239818.8281 |
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+ | 9000 | 0.1455 | 149.5442 | 28142.1230 | 7.4452 | 66.0052 | 75.752 | 9.469 | 11.2706 | 243104.3594 |
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+ | 12000 | 0.1939 | 141.4481 | 28096.5879 | 7.4447 | 66.228 | 75.497 | 9.437 | 10.4616 | 242650.5938 |
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+ | 15000 | 0.2424 | 141.9365 | 27532.4258 | 7.4447 | 66.1198 | 75.62 | 9.453 | 10.5402 | 235884.5 |
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+ | 18000 | 0.2909 | 150.4271 | 28453.0332 | 7.4452 | 65.9158 | 75.854 | 9.482 | 11.3604 | 248415.0781 |
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+ | 21000 | 0.3394 | 148.4649 | 27337.2715 | 7.4450 | 65.7078 | 76.094 | 9.512 | 11.2888 | 229674.3125 |
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+ | 24000 | 0.3879 | 149.7760 | 28039.2520 | 7.4446 | 65.7891 | 76.0 | 9.5 | 11.2827 | 240716.3594 |
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+ | 27000 | 0.4364 | 141.8706 | 28049.1211 | 7.4454 | 65.831 | 75.952 | 9.494 | 10.5280 | 235255.9062 |
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+ | 30000 | 0.4848 | 144.7906 | 28084.7207 | 7.4449 | 65.9422 | 75.824 | 9.478 | 10.7119 | 240716.3594 |
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+ | 33000 | 0.5333 | 149.6832 | 28237.4258 | 7.4454 | 65.807 | 75.98 | 9.497 | 11.2524 | 244013.9531 |
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+ | 36000 | 0.5818 | 148.6030 | 27445.3125 | 7.4453 | 65.6651 | 76.144 | 9.518 | 11.2729 | 236893.5625 |
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+ | 39000 | 0.6303 | 142.9683 | 27676.2949 | 7.4447 | 65.6729 | 76.135 | 9.517 | 10.6589 | 235381.5781 |
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+ | 42000 | 0.6788 | 146.5510 | 27895.4648 | 7.4449 | 65.6881 | 76.117 | 9.515 | 10.9904 | 239690.7812 |
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+ | 45000 | 0.7273 | 149.2144 | 28023.4531 | 7.4454 | 65.9058 | 75.866 | 9.483 | 11.2701 | 240716.3594 |
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+ | 48000 | 0.7758 | 144.2086 | 28243.4043 | 7.4449 | 65.873 | 75.904 | 9.488 | 10.7022 | 244339.7188 |
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+ | 51000 | 0.8242 | 141.9915 | 27781.7559 | 7.4450 | 65.9256 | 75.843 | 9.48 | 10.5589 | 239563.0469 |
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+ | 54000 | 0.8727 | 145.6399 | 28219.5234 | 7.4451 | 65.6892 | 76.116 | 9.515 | 10.8693 | 238542.6094 |
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+ | 57000 | 0.9212 | 144.2365 | 27040.4609 | 7.4445 | 65.6838 | 76.122 | 9.515 | 10.8312 | 227175.6875 |
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+ | 60000 | 0.9697 | 144.3482 | 26979.5938 | 7.4447 | 65.623 | 76.193 | 9.524 | 10.9257 | 232138.6562 |
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+ | 61875 | 1.0 | 146.9147 | 28084.7207 | 7.4450 | 65.6082 | 76.21 | 9.526 | 10.9569 | 237146.5 |
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  ### Framework versions
89
  - Distily 0.2.0
90
  - Transformers 4.44.0
91
  - Pytorch 2.3.0
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+ - Datasets 2.20.0
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