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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: 0.6671
  • Rewards/chosen: -0.4223
  • Rewards/rejected: -1.9854
  • Rewards/accuracies: 0.4375
  • Rewards/margins: 1.5631
  • Logps/rejected: -350.5416
  • Logps/chosen: -220.8451
  • Logits/rejected: -1.7880
  • Logits/chosen: -1.7651

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
0.6968 0.01 10 0.6686 -0.0503 -0.0549 0.5625 0.0046 -331.2371 -217.1252 -1.8320 -1.8255
0.6793 0.01 20 1.7619 0.2100 3.0956 0.3125 -2.8856 -299.7324 -214.5222 -1.9578 -1.9436
0.6789 0.01 30 0.6364 -0.2040 -1.0884 0.4375 0.8843 -341.5715 -218.6622 -1.8060 -1.7894
0.6966 0.02 40 0.6716 -0.2823 -1.4572 0.4375 1.1749 -345.2603 -219.4454 -1.7994 -1.7786
0.8051 0.03 50 0.6671 -0.4223 -1.9854 0.4375 1.5631 -350.5416 -220.8451 -1.7880 -1.7651

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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