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metadata
license: llama2
base_model: epfl-llm/meditron-7b
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: 500STEPS_1e6rate_01beta_DPO_Meditron7B
    results: []

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