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MedQA_L3_300steps_1e7rate_05beta_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: 0.2870
  • Rewards/rejected: 0.1538
  • Rewards/accuracies: 0.6374
  • Rewards/margins: 0.1332
  • Logps/rejected: -21.0089
  • Logps/chosen: -17.6487
  • Logits/rejected: -0.9327
  • Logits/chosen: -0.9321

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: 300

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.7034 0.0489 50 0.6908 0.0092 0.0030 0.5187 0.0061 -21.3104 -18.2043 -0.9262 -0.9257
0.6841 0.0977 100 0.6705 0.1777 0.1221 0.6088 0.0556 -21.0723 -17.8673 -0.9278 -0.9273
0.6636 0.1466 150 0.6536 0.2698 0.1543 0.6505 0.1155 -21.0080 -17.6830 -0.9307 -0.9302
0.6483 0.1954 200 0.6488 0.2862 0.1570 0.6330 0.1291 -21.0025 -17.6503 -0.9322 -0.9317
0.683 0.2443 250 0.6472 0.2913 0.1569 0.6396 0.1344 -21.0027 -17.6400 -0.9325 -0.9320
0.6269 0.2931 300 0.6479 0.2870 0.1538 0.6374 0.1332 -21.0089 -17.6487 -0.9327 -0.9321

Framework versions

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