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--- |
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base_model: Qwen/Qwen2-0.5B-Instruct |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: dpo-model-lora |
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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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# dpo-model-lora |
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This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6534 |
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- Rewards/chosen: -0.7320 |
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- Rewards/rejected: -0.8303 |
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- Rewards/accuracies: 0.6172 |
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- Rewards/margins: 0.0983 |
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- Logps/rejected: -359.0921 |
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- Logps/chosen: -378.4928 |
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- Logits/rejected: -2.2715 |
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- Logits/chosen: -2.3471 |
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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: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation 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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| 0.6884 | 0.1030 | 50 | 0.6879 | -0.0543 | -0.0734 | 0.6484 | 0.0191 | -351.5229 | -371.7161 | -2.2877 | -2.3628 | |
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| 0.6787 | 0.2060 | 100 | 0.6770 | -0.1811 | -0.2114 | 0.6016 | 0.0303 | -352.9030 | -372.9836 | -2.2815 | -2.3565 | |
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| 0.6721 | 0.3090 | 150 | 0.6721 | -0.2679 | -0.3094 | 0.6562 | 0.0415 | -353.8831 | -373.8524 | -2.2782 | -2.3536 | |
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| 0.6668 | 0.4119 | 200 | 0.6665 | -0.4037 | -0.4625 | 0.6016 | 0.0588 | -355.4139 | -375.2100 | -2.2758 | -2.3515 | |
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| 0.6597 | 0.5149 | 250 | 0.6612 | -0.4907 | -0.5505 | 0.6172 | 0.0598 | -356.2946 | -376.0805 | -2.2757 | -2.3510 | |
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| 0.6581 | 0.6179 | 300 | 0.6578 | -0.6137 | -0.6975 | 0.625 | 0.0838 | -357.7639 | -377.3098 | -2.2736 | -2.3491 | |
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| 0.6536 | 0.7209 | 350 | 0.6556 | -0.6458 | -0.7367 | 0.6328 | 0.0909 | -358.1565 | -377.6311 | -2.2732 | -2.3489 | |
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| 0.6486 | 0.8239 | 400 | 0.6556 | -0.7025 | -0.7958 | 0.6328 | 0.0933 | -358.7473 | -378.1981 | -2.2737 | -2.3493 | |
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| 0.649 | 0.9269 | 450 | 0.6556 | -0.7432 | -0.8327 | 0.6484 | 0.0896 | -359.1166 | -378.6048 | -2.2726 | -2.3482 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
