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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: 0.6183
  • Rewards/chosen: 0.0311
  • Rewards/rejected: -0.0695
  • Rewards/accuracies: 0.625
  • Rewards/margins: 0.1006
  • Logps/rejected: -143.5769
  • Logps/chosen: -125.5347
  • Logits/rejected: -2.7201
  • Logits/chosen: -2.8454

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
0.6852 0.01 10 0.6765 0.0305 0.0058 0.5625 0.0247 -142.8238 -125.5402 -2.7089 -2.8446
0.7058 0.01 20 0.6604 0.0370 -0.0005 0.5625 0.0375 -142.8867 -125.4757 -2.7121 -2.8454
0.6407 0.01 30 0.6319 0.0537 -0.0265 0.6875 0.0802 -143.1462 -125.3082 -2.7146 -2.8457
0.6445 0.02 40 0.6210 0.0345 -0.0659 0.625 0.1004 -143.5407 -125.5005 -2.7173 -2.8463
0.6847 0.03 50 0.6183 0.0311 -0.0695 0.625 0.1006 -143.5769 -125.5347 -2.7201 -2.8454

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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