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openhermes-mistral-dpo-gptq

This model is a fine-tuned version of TheBloke/OpenHermes-2-Mistral-7B-GPTQ on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7494
  • Rewards/chosen: -1.3887
  • Rewards/rejected: -1.3727
  • Rewards/accuracies: 0.25
  • Rewards/margins: -0.0160
  • Logps/rejected: -254.9227
  • Logps/chosen: -296.4655
  • Logits/rejected: -3.2845
  • Logits/chosen: -3.3612

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: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2
  • training_steps: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6671 0.01 10 0.7157 -0.0276 -0.0086 0.375 -0.0190 -241.2815 -282.8551 -2.8170 -2.9092
0.7091 0.01 20 0.7164 -0.5539 -0.6101 0.5 0.0562 -247.2965 -288.1179 -3.0463 -3.1341
0.6568 0.01 30 0.7347 -0.7194 -0.7557 0.5 0.0363 -248.7529 -289.7729 -3.1075 -3.1928
0.6534 0.02 40 0.7316 -1.3152 -1.3098 0.25 -0.0054 -254.2937 -295.7312 -3.2685 -3.3467
0.8009 0.03 50 0.7494 -1.3887 -1.3727 0.25 -0.0160 -254.9227 -296.4655 -3.2845 -3.3612

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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