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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: 0.6697
  • Rewards/chosen: 0.0061
  • Rewards/rejected: -0.0288
  • Rewards/accuracies: 0.625
  • Rewards/margins: 0.0350
  • Logps/rejected: -127.8806
  • Logps/chosen: -193.3892
  • Logits/rejected: -2.4394
  • Logits/chosen: -2.6044

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: 20
  • 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
0.6762 0.01 10 0.6833 -0.0083 -0.0216 0.625 0.0133 -127.8089 -193.5340 -2.4411 -2.6076
0.7039 0.01 20 0.6697 0.0061 -0.0288 0.625 0.0350 -127.8806 -193.3892 -2.4394 -2.6044

Framework versions

  • PEFT 0.9.0
  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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