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--- |
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library_name: transformers |
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license: other |
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base_model: trl-lib/qwen1.5-0.5b-sft |
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tags: |
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- alignment-handbook |
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- trl |
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- simpo |
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- generated_from_trainer |
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- trl |
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- simpo |
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- generated_from_trainer |
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datasets: |
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- yakazimir/ultrafeedback_binarized |
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model-index: |
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- name: qwen_orpo_entropy_0_01 |
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results: [] |
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--- |
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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. --> |
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# qwen_orpo_entropy_0_01 |
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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 the yakazimir/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5589 |
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- Sft Loss: 3.3163 |
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- Rewards/chosen: -3.1855 |
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- Rewards/rejected: -4.1739 |
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- Rewards/accuracies: 0.7226 |
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- Rewards/margins: 0.9884 |
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- Logps/rejected: -4.1739 |
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- Logps/chosen: -3.1855 |
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- Logits/rejected: 0.1645 |
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- Logits/chosen: 0.0521 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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