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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: meditron-7b-dpo-full-wo-live_qa-ep3 |
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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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# meditron-7b-dpo-full-wo-live_qa-ep3 |
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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: 0.5356 |
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- Rewards/chosen: -0.2875 |
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- Rewards/rejected: -0.7751 |
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- Rewards/accuracies: 0.7019 |
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- Rewards/margins: 0.4876 |
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- Logps/rejected: -1205.2603 |
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- Logps/chosen: -986.1399 |
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- Logits/rejected: -0.8883 |
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- Logits/chosen: -0.8904 |
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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: 8 |
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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: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- total_eval_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: 1 |
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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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| 0.583 | 0.49 | 100 | 0.6358 | -0.0392 | -0.1400 | 0.6442 | 0.1009 | -1141.7539 | -961.3083 | -0.8346 | -0.8420 | |
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| 0.3768 | 0.98 | 200 | 0.5356 | -0.2875 | -0.7751 | 0.7019 | 0.4876 | -1205.2603 | -986.1399 | -0.8883 | -0.8904 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.1.2 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
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