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_orpo_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_orpo_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: 0.5590
+- Sft Loss: 3.3163
+- Rewards/chosen: -3.1855
+- Rewards/rejected: -4.1739
+- Rewards/accuracies: 0.7226
+- Rewards/margins: 0.9884
+- Logps/rejected: -4.1739
+- Logps/chosen: -3.1855
+- Logits/rejected: 0.1645
+- Logits/chosen: 0.0521
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.7198        | 0.2141 | 400  | 0.7213          | 1.4421   | -1.5116        | -1.6721          | 0.5556             | 0.1605          | -1.6721        | -1.5116      | 0.3831          | 0.2918        |
+| 0.6256        | 0.4282 | 800  | 0.6211          | 2.0645   | -2.1064        | -2.5196          | 0.6654             | 0.4133          | -2.5196        | -2.1064      | 0.4328          | 0.3408        |
+| 0.6247        | 0.6422 | 1200 | 0.5880          | 2.6367   | -2.5144        | -3.0951          | 0.6966             | 0.5807          | -3.0951        | -2.5144      | 0.4051          | 0.3038        |
+| 0.5355        | 0.8563 | 1600 | 0.5751          | 2.5635   | -2.4305        | -2.9974          | 0.7062             | 0.5669          | -2.9974        | -2.4305      | 0.4192          | 0.3133        |
+| 0.6075        | 1.0704 | 2000 | 0.5675          | 2.6770   | -2.5347        | -3.1956          | 0.7166             | 0.6609          | -3.1956        | -2.5347      | 0.3536          | 0.2455        |
+| 0.5886        | 1.2845 | 2400 | 0.5600          | 2.9406   | -2.8008        | -3.5986          | 0.7292             | 0.7978          | -3.5986        | -2.8008      | 0.2408          | 0.1351        |
+| 0.5549        | 1.4986 | 2800 | 0.5573          | 2.8692   | -2.7229        | -3.5062          | 0.7248             | 0.7833          | -3.5062        | -2.7229      | 0.2546          | 0.1468        |
+| 0.5785        | 1.7127 | 3200 | 0.5549          | 2.8827   | -2.7303        | -3.5085          | 0.7240             | 0.7782          | -3.5085        | -2.7303      | 0.2599          | 0.1531        |
+| 0.5649        | 1.9267 | 3600 | 0.5509          | 2.9742   | -2.8066        | -3.6363          | 0.7240             | 0.8296          | -3.6363        | -2.8066      | 0.2062          | 0.0982        |
+| 0.4683        | 2.1408 | 4000 | 0.5601          | 3.3501   | -3.1588        | -4.1100          | 0.7196             | 0.9512          | -4.1100        | -3.1588      | 0.1350          | 0.0257        |
+| 0.491         | 2.3549 | 4400 | 0.5604          | 3.3569   | -3.2270        | -4.2111          | 0.7203             | 0.9841          | -4.2111        | -3.2270      | 0.2088          | 0.0922        |
+| 0.4967        | 2.5690 | 4800 | 0.5589          | 3.2861   | -3.1626        | -4.1414          | 0.7226             | 0.9787          | -4.1414        | -3.1626      | 0.1660          | 0.0539        |
+| 0.439         | 2.7831 | 5200 | 0.5584          | 3.3040   | -3.1772        | -4.1641          | 0.7211             | 0.9869          | -4.1641        | -3.1772      | 0.1462          | 0.0352        |
+| 0.4704        | 2.9972 | 5600 | 0.5590          | 3.3163   | -3.1855        | -4.1739          | 0.7226             | 0.9884          | -4.1739        | -3.1855      | 0.1645          | 0.0521        |
+
+
+### 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": 0.5562219639746825,
+    "train_runtime": 39292.0664,
+    "train_samples": 59790,
+    "train_samples_per_second": 4.565,
+    "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": 0.5562219639746825,
+    "train_runtime": 39292.0664,
+    "train_samples": 59790,
+    "train_samples_per_second": 4.565,
+    "train_steps_per_second": 0.143
+}