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model_shp3_dpo1

This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0149
  • Rewards/chosen: -10.1791
  • Rewards/rejected: -11.7765
  • Rewards/accuracies: 0.5700
  • Rewards/margins: 1.5974
  • Logps/rejected: -384.5022
  • Logps/chosen: -344.3792
  • Logits/rejected: -0.9104
  • Logits/chosen: -0.9161

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: 0.0005
  • train_batch_size: 4
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.0698 2.67 100 1.0791 -4.0199 -4.9604 0.5900 0.9405 -316.3408 -282.7867 -0.9293 -0.9672
0.0004 5.33 200 1.5283 -7.2654 -8.3476 0.5800 1.0822 -350.2130 -315.2426 -0.9409 -0.9510
0.0001 8.0 300 1.9265 -9.7069 -11.2491 0.5700 1.5421 -379.2276 -339.6573 -0.9224 -0.9298
0.0001 10.67 400 1.9667 -9.9054 -11.4492 0.5700 1.5439 -381.2295 -341.6420 -0.9181 -0.9248
0.0001 13.33 500 1.9959 -10.0523 -11.6165 0.5700 1.5642 -382.9025 -343.1115 -0.9137 -0.9198
0.0 16.0 600 2.0035 -10.1182 -11.7116 0.5700 1.5934 -383.8533 -343.7699 -0.9121 -0.9185
0.0001 18.67 700 2.0159 -10.1627 -11.7547 0.5700 1.5920 -384.2843 -344.2155 -0.9115 -0.9169
0.0 21.33 800 2.0163 -10.1740 -11.7677 0.5700 1.5937 -384.4142 -344.3281 -0.9103 -0.9160
0.0 24.0 900 2.0220 -10.1842 -11.7817 0.5700 1.5976 -384.5541 -344.4297 -0.9106 -0.9160
0.0001 26.67 1000 2.0149 -10.1791 -11.7765 0.5700 1.5974 -384.5022 -344.3792 -0.9104 -0.9161

Framework versions

  • PEFT 0.10.0
  • Transformers 4.39.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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