Model save

README.md

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+---
+library_name: transformers
+license: other
+base_model: trl-lib/qwen1.5-0.5b-sft
+tags:
+- trl
+- simpo
+- generated_from_trainer
+model-index:
+- name: qwen_cpo_entropy_0_01
+  results: []
+---
+
+<!-- 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. -->
+
+# qwen_cpo_entropy_0_01
+
+This model is a fine-tuned version of [trl-lib/qwen1.5-0.5b-sft](https://huggingface.co/trl-lib/qwen1.5-0.5b-sft) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5583
+- Sft Loss: 3.4705
+- Rewards/chosen: -3.3285
+- Rewards/rejected: -4.3810
+- Rewards/accuracies: 0.7226
+- Rewards/margins: 1.0525
+- Logps/rejected: -4.3810
+- Logps/chosen: -3.3285
+- Logits/rejected: 0.2811
+- Logits/chosen: 0.1563
+
+## 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: 1e-06
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.7019        | 0.2141 | 400  | 0.6977          | 1.4219   | -1.4375        | -1.6032          | 0.5631             | 0.1657          | -1.6032        | -1.4375      | 0.2993          | 0.2138        |
+| 0.6225        | 0.4282 | 800  | 0.6192          | 2.0573   | -2.0770        | -2.5396          | 0.6669             | 0.4626          | -2.5396        | -2.0770      | 0.3429          | 0.2570        |
+| 0.6242        | 0.6422 | 1200 | 0.5882          | 2.6279   | -2.4850        | -3.1039          | 0.6973             | 0.6190          | -3.1039        | -2.4850      | 0.5237          | 0.4102        |
+| 0.5405        | 0.8563 | 1600 | 0.5781          | 2.5442   | -2.4160        | -3.0202          | 0.7092             | 0.6042          | -3.0202        | -2.4160      | 0.4122          | 0.3042        |
+| 0.6195        | 1.0704 | 2000 | 0.5673          | 2.7121   | -2.5451        | -3.2527          | 0.7129             | 0.7076          | -3.2527        | -2.5451      | 0.4573          | 0.3371        |
+| 0.5895        | 1.2845 | 2400 | 0.5590          | 3.0631   | -2.8962        | -3.7486          | 0.7322             | 0.8524          | -3.7486        | -2.8962      | 0.3362          | 0.2174        |
+| 0.5512        | 1.4986 | 2800 | 0.5563          | 2.9053   | -2.7513        | -3.5751          | 0.7203             | 0.8238          | -3.5751        | -2.7513      | 0.2892          | 0.1750        |
+| 0.5766        | 1.7127 | 3200 | 0.5520          | 2.9643   | -2.8134        | -3.6655          | 0.7263             | 0.8522          | -3.6655        | -2.8134      | 0.2677          | 0.1562        |
+| 0.5625        | 1.9267 | 3600 | 0.5478          | 3.0563   | -2.8597        | -3.7385          | 0.7255             | 0.8788          | -3.7385        | -2.8597      | 0.3670          | 0.2441        |
+| 0.4702        | 2.1408 | 4000 | 0.5592          | 3.5119   | -3.3071        | -4.3285          | 0.7240             | 1.0214          | -4.3285        | -3.3071      | 0.2395          | 0.1198        |
+| 0.4882        | 2.3549 | 4400 | 0.5601          | 3.5201   | -3.3795        | -4.4355          | 0.7270             | 1.0560          | -4.4355        | -3.3795      | 0.2852          | 0.1603        |
+| 0.4952        | 2.5690 | 4800 | 0.5580          | 3.4402   | -3.3065        | -4.3570          | 0.7233             | 1.0505          | -4.3570        | -3.3065      | 0.3210          | 0.1936        |
+| 0.4272        | 2.7831 | 5200 | 0.5579          | 3.4523   | -3.3138        | -4.3619          | 0.7233             | 1.0481          | -4.3619        | -3.3138      | 0.3592          | 0.2281        |
+| 0.459         | 2.9972 | 5600 | 0.5583          | 3.4705   | -3.3285        | -4.3810          | 0.7226             | 1.0525          | -4.3810        | -3.3285      | 0.2811          | 0.1563        |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 2.999297541394882,
+    "total_flos": 0.0,
+    "train_loss": 0.5516859670777903,
+    "train_runtime": 39088.5646,
+    "train_samples": 59790,
+    "train_samples_per_second": 4.589,
+    "train_steps_per_second": 0.143
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.44.2"
+}

train_results.json

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+{
+    "epoch": 2.999297541394882,
+    "total_flos": 0.0,
+    "train_loss": 0.5516859670777903,
+    "train_runtime": 39088.5646,
+    "train_samples": 59790,
+    "train_samples_per_second": 4.589,
+    "train_steps_per_second": 0.143
+}