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--- |
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library_name: peft |
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tags: |
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- trl |
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- dpo |
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- DPO |
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- WeniGPT |
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- generated_from_trainer |
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base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged |
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model-index: |
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- name: WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.8-DPO |
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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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# WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.8-DPO |
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This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged](https://huggingface.co/Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2005 |
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- Rewards/chosen: 1.7621 |
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- Rewards/rejected: -0.7248 |
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- Rewards/accuracies: 1.0 |
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- Rewards/margins: 2.4869 |
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- Logps/rejected: -271.5133 |
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- Logps/chosen: -102.9727 |
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- Logits/rejected: -1.8958 |
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- Logits/chosen: -1.8013 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 4 |
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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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- lr_scheduler_warmup_ratio: 0.03 |
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- training_steps: 180 |
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- mixed_precision_training: Native AMP |
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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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| 0.5477 | 0.97 | 30 | 0.4843 | 0.4718 | -0.1109 | 0.8571 | 0.5827 | -269.4668 | -107.2735 | -1.8863 | -1.7949 | |
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| 0.3542 | 1.94 | 60 | 0.3440 | 0.9609 | -0.2516 | 1.0 | 1.2125 | -269.9360 | -105.6431 | -1.8903 | -1.7979 | |
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| 0.2892 | 2.9 | 90 | 0.2756 | 1.3199 | -0.4182 | 1.0 | 1.7381 | -270.4914 | -104.4467 | -1.8928 | -1.7995 | |
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| 0.1858 | 3.87 | 120 | 0.2327 | 1.6010 | -0.5696 | 1.0 | 2.1706 | -270.9958 | -103.5094 | -1.8947 | -1.8008 | |
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| 0.1811 | 4.84 | 150 | 0.2076 | 1.7245 | -0.6925 | 1.0 | 2.4170 | -271.4054 | -103.0979 | -1.8954 | -1.8010 | |
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| 0.2065 | 5.81 | 180 | 0.2005 | 1.7621 | -0.7248 | 1.0 | 2.4869 | -271.5133 | -102.9727 | -1.8958 | -1.8013 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
