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metadata
license: apache-2.0
library_name: peft
tags:
  - alignment-handbook
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
base_model: alignment-handbook/zephyr-7b-sft-full
model-index:
  - name: zephyr-7b-dpo-lora-pubmedqa-selfgen-ultrafeedback2
    results: []

zephyr-7b-dpo-lora-pubmedqa-selfgen-ultrafeedback2

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

  • Loss: 0.5869
  • Rewards/chosen: -0.2480
  • Rewards/rejected: -0.5522
  • Rewards/accuracies: 0.7090
  • Rewards/margins: 0.3042
  • Logps/rejected: -306.5199
  • Logps/chosen: -309.5233
  • Logits/rejected: -2.5197
  • Logits/chosen: -2.5501

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: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • total_eval_batch_size: 4
  • 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
0.5526 0.39 3000 0.6013 -0.1508 -0.4054 0.7040 0.2546 -291.8378 -299.8007 -2.5651 -2.5923
0.5814 0.79 6000 0.5867 -0.2418 -0.5459 0.7080 0.3040 -305.8824 -308.9029 -2.5202 -2.5505

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2