500STEPS_1e6rate_01beta_DPO_Meditron7B
This model is a fine-tuned version of epfl-llm/meditron-7b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6302
- Rewards/chosen: 0.0115
- Rewards/rejected: -0.1672
- Rewards/accuracies: 0.5868
- Rewards/margins: 0.1788
- Logps/rejected: -29.4661
- Logps/chosen: -26.3659
- Logits/rejected: -0.7645
- Logits/chosen: -0.7643
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6902 | 0.1 | 50 | 0.6903 | 0.0090 | 0.0031 | 0.5121 | 0.0058 | -27.7623 | -26.3918 | -0.6125 | -0.6124 |
| 0.6766 | 0.2 | 100 | 0.6792 | -0.1559 | -0.1907 | 0.5099 | 0.0349 | -29.7009 | -28.0399 | -0.6382 | -0.6380 |
| 0.6667 | 0.29 | 150 | 0.6567 | -0.0224 | -0.1102 | 0.5714 | 0.0879 | -28.8959 | -26.7051 | -0.6559 | -0.6557 |
| 0.6656 | 0.39 | 200 | 0.6495 | -0.0303 | -0.1387 | 0.5802 | 0.1084 | -29.1808 | -26.7847 | -0.7108 | -0.7106 |
| 0.5939 | 0.49 | 250 | 0.6388 | -0.0202 | -0.1629 | 0.5890 | 0.1426 | -29.4223 | -26.6837 | -0.7329 | -0.7327 |
| 0.6328 | 0.59 | 300 | 0.6349 | -0.0421 | -0.2022 | 0.5758 | 0.1601 | -29.8158 | -26.9024 | -0.7492 | -0.7490 |
| 0.6231 | 0.68 | 350 | 0.6313 | -0.0004 | -0.1725 | 0.5758 | 0.1721 | -29.5189 | -26.4852 | -0.7571 | -0.7569 |
| 0.6419 | 0.78 | 400 | 0.6303 | 0.0123 | -0.1660 | 0.5868 | 0.1783 | -29.4536 | -26.3585 | -0.7639 | -0.7637 |
| 0.6045 | 0.88 | 450 | 0.6304 | 0.0120 | -0.1662 | 0.5846 | 0.1783 | -29.4560 | -26.3611 | -0.7645 | -0.7643 |
| 0.5984 | 0.98 | 500 | 0.6302 | 0.0115 | -0.1672 | 0.5868 | 0.1788 | -29.4661 | -26.3659 | -0.7645 | -0.7643 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.0+cu117
- Datasets 2.17.0
- Tokenizers 0.15.1
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