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zephyr-7b-dpo-lora

This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-beta on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6843
  • Rewards/chosen: 0.0440
  • Rewards/rejected: 0.0071
  • Rewards/accuracies: 0.5
  • Rewards/margins: 0.0369
  • Logps/rejected: -132.8740
  • Logps/chosen: -190.5722
  • Logits/rejected: -2.2999
  • Logits/chosen: -2.2747

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: 5e-07
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 512
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6931 0.55 1 0.6931 0.0 0.0 0.0 0.0 -132.9451 -191.0126 -2.3015 -2.2762
0.6931 1.66 3 0.6928 0.0185 -0.0111 0.5 0.0296 -133.0566 -190.8279 -2.3016 -2.2755
0.6931 2.76 5 0.6843 0.0440 0.0071 0.5 0.0369 -132.8740 -190.5722 -2.2999 -2.2747

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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