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--- |
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license: llama3 |
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base_model: tsavage68/MedQA_L3_1000steps_1e6rate_SFT |
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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: MedQA_L3_300steps_1e6rate_01beta_CSFTDPO |
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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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# MedQA_L3_300steps_1e6rate_01beta_CSFTDPO |
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This model is a fine-tuned version of [tsavage68/MedQA_L3_1000steps_1e6rate_SFT](https://huggingface.co/tsavage68/MedQA_L3_1000steps_1e6rate_SFT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4661 |
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- Rewards/chosen: 0.6273 |
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- Rewards/rejected: -0.3771 |
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- Rewards/accuracies: 0.7604 |
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- Rewards/margins: 1.0045 |
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- Logps/rejected: -37.6261 |
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- Logps/chosen: -25.0552 |
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- Logits/rejected: -0.8801 |
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- Logits/chosen: -0.8780 |
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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: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_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: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 300 |
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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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| 0.6869 | 0.0489 | 50 | 0.6696 | -0.2211 | -0.2710 | 0.7253 | 0.0498 | -36.5645 | -33.5400 | -0.7298 | -0.7290 | |
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| 0.4779 | 0.0977 | 100 | 0.5887 | 1.4526 | 1.0417 | 0.6945 | 0.4109 | -23.4374 | -16.8024 | -0.8047 | -0.8036 | |
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| 0.5155 | 0.1466 | 150 | 0.4976 | 0.6394 | -0.2000 | 0.7363 | 0.8394 | -35.8551 | -24.9343 | -0.8636 | -0.8617 | |
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| 0.4245 | 0.1954 | 200 | 0.4924 | 0.0477 | -0.9077 | 0.7648 | 0.9554 | -42.9321 | -30.8513 | -0.8783 | -0.8762 | |
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| 0.4563 | 0.2443 | 250 | 0.4675 | 0.6549 | -0.3364 | 0.7560 | 0.9913 | -37.2189 | -24.7791 | -0.8807 | -0.8786 | |
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| 0.3066 | 0.2931 | 300 | 0.4661 | 0.6273 | -0.3771 | 0.7604 | 1.0045 | -37.6261 | -25.0552 | -0.8801 | -0.8780 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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