zephyr-7b-dpo-lora-pubmedqa-ultrafeedback

This model is a fine-tuned version of EllieS/zephyr-7b-dpo-lora-pubmedqa on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5835
  • Rewards/chosen: -0.1486
  • Rewards/rejected: -0.4853
  • Rewards/accuracies: 0.7105
  • Rewards/margins: 0.3368
  • Logps/rejected: -314.4243
  • Logps/chosen: -302.0460
  • Logits/rejected: -2.5375
  • Logits/chosen: -2.5889

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-06
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.5703 0.92 7000 0.5835 -0.1500 -0.4872 0.7140 0.3372 -314.6089 -302.1864 -2.5236 -2.5765

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.0
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