400STEPS_05beta_1e7rate_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: 0.6864
  • Rewards/chosen: 0.0004
  • Rewards/rejected: -0.0144
  • Rewards/accuracies: 0.4945
  • Rewards/margins: 0.0148
  • Logps/rejected: -27.8226
  • Logps/chosen: -26.4806
  • Logits/rejected: -0.6110
  • Logits/chosen: -0.6109

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: 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: 400

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6941 0.1 50 0.6931 -0.0003 -0.0011 0.4044 0.0008 -27.7959 -26.4820 -0.6106 -0.6104
0.6927 0.2 100 0.6912 -0.0047 -0.0093 0.4769 0.0046 -27.8123 -26.4908 -0.6105 -0.6104
0.6838 0.29 150 0.6896 -0.0023 -0.0105 0.5077 0.0082 -27.8146 -26.4860 -0.6101 -0.6100
0.6906 0.39 200 0.6886 -0.0007 -0.0107 0.4989 0.0100 -27.8151 -26.4828 -0.6109 -0.6108
0.6789 0.49 250 0.6877 -0.0035 -0.0154 0.5121 0.0119 -27.8245 -26.4884 -0.6111 -0.6110
0.6853 0.59 300 0.6852 0.0012 -0.0160 0.5297 0.0172 -27.8257 -26.4791 -0.6112 -0.6111
0.6805 0.68 350 0.6877 -0.0039 -0.0162 0.4725 0.0122 -27.8260 -26.4893 -0.6112 -0.6110
0.6936 0.78 400 0.6864 0.0004 -0.0144 0.4945 0.0148 -27.8226 -26.4806 -0.6110 -0.6109

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.0.0+cu117
  • Datasets 2.17.0
  • Tokenizers 0.15.1
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