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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: 0.9029
  • Rewards/chosen: -0.1592
  • Rewards/rejected: -0.0751
  • Rewards/accuracies: 0.4375
  • Rewards/margins: -0.0841
  • Logps/rejected: -164.9728
  • Logps/chosen: -207.7616
  • Logits/rejected: -2.4937
  • Logits/chosen: -2.5880

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
0.6777 0.005 10 0.7136 -0.0128 -0.0514 0.5625 0.0386 -164.7356 -206.2971 -2.4991 -2.5809
0.6983 0.01 20 0.7209 -0.0223 -0.1062 0.625 0.0838 -165.2831 -206.3929 -2.4962 -2.5809
0.697 0.015 30 0.7341 -0.0064 -0.0583 0.6875 0.0519 -164.8043 -206.2330 -2.4984 -2.5864
0.6967 0.02 40 0.7473 -0.0052 -0.0485 0.4375 0.0433 -164.7064 -206.2214 -2.4930 -2.5857
0.6666 0.025 50 0.9029 -0.1592 -0.0751 0.4375 -0.0841 -164.9728 -207.7616 -2.4937 -2.5880

Framework versions

  • PEFT 0.12.0
  • Transformers 4.42.4
  • Pytorch 2.0.1+cu117
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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