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--- |
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license: llama2 |
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base_model: epfl-llm/meditron-7b |
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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: 400STEPS_5e7rate_03beta_DPO_Meditron7B |
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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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# 400STEPS_5e7rate_03beta_DPO_Meditron7B |
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This model is a fine-tuned version of [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6439 |
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- Rewards/chosen: -0.0166 |
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- Rewards/rejected: -0.1472 |
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- Rewards/accuracies: 0.5714 |
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- Rewards/margins: 0.1306 |
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- Logps/rejected: -28.2845 |
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- Logps/chosen: -26.5367 |
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- Logits/rejected: -0.6342 |
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- Logits/chosen: -0.6341 |
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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-07 |
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- train_batch_size: 4 |
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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: 8 |
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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: 400 |
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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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| 0.6896 | 0.1 | 50 | 0.6916 | 0.0067 | 0.0033 | 0.4637 | 0.0034 | -27.7828 | -26.4590 | -0.6113 | -0.6111 | |
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| 0.6783 | 0.2 | 100 | 0.6771 | -0.0693 | -0.1071 | 0.5319 | 0.0378 | -28.1508 | -26.7125 | -0.6173 | -0.6171 | |
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| 0.6697 | 0.29 | 150 | 0.6571 | -0.0107 | -0.1001 | 0.5626 | 0.0893 | -28.1273 | -26.5172 | -0.6171 | -0.6170 | |
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| 0.6463 | 0.39 | 200 | 0.6496 | 0.0037 | -0.1067 | 0.5692 | 0.1104 | -28.1493 | -26.4691 | -0.6288 | -0.6286 | |
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| 0.6124 | 0.49 | 250 | 0.6449 | -0.0073 | -0.1329 | 0.5648 | 0.1257 | -28.2368 | -26.5056 | -0.6318 | -0.6317 | |
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| 0.641 | 0.59 | 300 | 0.6440 | -0.0156 | -0.1460 | 0.5758 | 0.1304 | -28.2803 | -26.5333 | -0.6340 | -0.6339 | |
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| 0.643 | 0.68 | 350 | 0.6430 | -0.0150 | -0.1479 | 0.5780 | 0.1328 | -28.2866 | -26.5315 | -0.6343 | -0.6341 | |
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| 0.6632 | 0.78 | 400 | 0.6439 | -0.0166 | -0.1472 | 0.5714 | 0.1306 | -28.2845 | -26.5367 | -0.6342 | -0.6341 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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