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README.md

@@ -1,3 +1,63 @@
----
-license: gemma
----
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# ifable/gemma-2-Ifable-9B
+
+
+It achieves the following results on the evaluation set:
+- Loss: 1.0163
+- Rewards/chosen: -21.6822
+- Rewards/rejected: -47.8754
+- Rewards/accuracies: 0.9167
+- Rewards/margins: 26.1931
+- Logps/rejected: -4.7875
+- Logps/chosen: -2.1682
+- Logits/rejected: -17.0475
+- Logits/chosen: -12.0041
+- Sft Loss: 0.0184
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 8e-07
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
+| 1.4444        | 0.9807 | 35   | 1.0163          | -21.6822       | -47.8754         | 0.9167             | 26.1931         | -4.7875        | -2.1682      | -17.0475        | -12.0041      | 0.0184   |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.3.0a0+ebedce2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

all_results.json

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+    "before_init_mem_gpu": 22016,
+    "epoch": 0.9807355516637478,
+    "eval_logits/chosen": -12.004097938537598,
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+    "eval_logps/chosen": -2.168222427368164,
+    "eval_logps/rejected": -4.787535667419434,
+    "eval_loss": 1.0162526369094849,
+    "eval_mem_cpu_alloc_delta": 466944,
+    "eval_mem_cpu_peaked_delta": 0,
+    "eval_mem_gpu_alloc_delta": 0,
+    "eval_mem_gpu_peaked_delta": 25220711424,
+    "eval_rewards/accuracies": 0.9166666865348816,
+    "eval_rewards/chosen": -21.682226181030273,
+    "eval_rewards/margins": 26.193130493164062,
+    "eval_rewards/rejected": -47.875362396240234,
+    "eval_runtime": 9.9413,
+    "eval_samples_per_second": 9.456,
+    "eval_sft_loss": 0.01844729855656624,
+    "eval_steps_per_second": 1.207,
+    "init_mem_cpu_alloc_delta": 364544,
+    "init_mem_cpu_peaked_delta": 0,
+    "init_mem_gpu_alloc_delta": 0,
+    "init_mem_gpu_peaked_delta": 0,
+    "total_flos": 39867492466688.0,
+    "train_loss": 3.085822834287371,
+    "train_mem_cpu_alloc_delta": 5213659136,
+    "train_mem_cpu_peaked_delta": 22737326080,
+    "train_mem_gpu_alloc_delta": 16267848704,
+    "train_mem_gpu_peaked_delta": 36029468160,
+    "train_runtime": 1628.7465,
+    "train_samples_per_second": 2.805,
+    "train_steps_per_second": 0.021
+}

config.json

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+  "architectures": [
+    "Gemma2ForCausalLM"
+  ],
+  "attention_bias": false,
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+  "final_logit_softcapping": 30.0,
+  "head_dim": 256,
+  "hidden_act": "gelu_pytorch_tanh",
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 3584,
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+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "gemma2",
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+  "rope_theta": 10000.0,
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+  "sliding_window_size": 4096,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.43.4",
+  "use_cache": false,
+  "vocab_size": 256000
+}

eval_results.json

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+    "eval_samples_per_second": 9.456,
+    "eval_sft_loss": 0.01844729855656624,
+    "eval_steps_per_second": 1.207
+}

generation_config.json

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+  },
+  "additional_special_tokens": [
+    "<start_of_turn>",
+    "<end_of_turn>"
+  ],
+  "bos_token": "<bos>",
+  "chat_template": "{{ '<bos>' }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}{% if system_message is defined %}{{ system_message }}{% endif %}{% for message in loop_messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<start_of_turn>user\n' + content + '<end_of_turn>\n<start_of_turn>model\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<end_of_turn>\n' }}{% endif %}{% endfor %}",
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+  "eos_token": "<eos>",
+  "model_max_length": 16000,
+  "pad_token": "<pad>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "split_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

train_results.json

@@ -0,0 +1,18 @@
+{
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+    "before_init_mem_gpu": 22016,
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+    "train_loss": 3.085822834287371,
+    "train_mem_cpu_alloc_delta": 5213659136,
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+    "train_mem_gpu_alloc_delta": 16267848704,
+    "train_mem_gpu_peaked_delta": 36029468160,
+    "train_runtime": 1628.7465,
+    "train_samples_per_second": 2.805,
+    "train_steps_per_second": 0.021
+}

trainer_log.jsonl

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