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MedQA_L3_450steps_1e7rate_03beta_CSFTDPO

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MedQA_L3_450steps_1e7rate_03beta_CSFTDPO / README.md
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metadata
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: MedQA_L3_450steps_1e7rate_03beta_CSFTDPO
    results: []

MedQA_L3_450steps_1e7rate_03beta_CSFTDPO

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6479
  • Rewards/chosen: 0.1876
  • Rewards/rejected: 0.0690
  • Rewards/accuracies: 0.6637
  • Rewards/margins: 0.1186
  • Logps/rejected: -21.0864
  • Logps/chosen: -17.5973
  • Logits/rejected: -0.9362
  • Logits/chosen: -0.9357

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-07
  • train_batch_size: 2
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 450

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6938 0.0489 50 0.6934 0.0041 0.0042 0.5099 -0.0000 -21.3026 -18.2088 -0.9262 -0.9257
0.6807 0.0977 100 0.6781 0.1130 0.0788 0.6110 0.0343 -21.0540 -17.8459 -0.9280 -0.9275
0.6689 0.1466 150 0.6622 0.1706 0.0922 0.6286 0.0784 -21.0091 -17.6540 -0.9313 -0.9308
0.6589 0.1954 200 0.6569 0.1748 0.0827 0.6462 0.0921 -21.0408 -17.6401 -0.9339 -0.9334
0.6798 0.2443 250 0.6507 0.1854 0.0751 0.6505 0.1103 -21.0663 -17.6047 -0.9352 -0.9347
0.6402 0.2931 300 0.6482 0.1927 0.0761 0.6725 0.1166 -21.0627 -17.5802 -0.9358 -0.9352
0.7088 0.3420 350 0.6481 0.1883 0.0698 0.6637 0.1185 -21.0838 -17.5951 -0.9357 -0.9352
0.6301 0.3908 400 0.6487 0.1878 0.0712 0.6549 0.1166 -21.0792 -17.5965 -0.9361 -0.9356
0.6454 0.4397 450 0.6479 0.1876 0.0690 0.6637 0.1186 -21.0864 -17.5973 -0.9362 -0.9357

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.0.0+cu117
  • Datasets 2.19.1
  • Tokenizers 0.19.1