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metadata
base_model: alignment-handbook/zephyr-7b-sft-full
datasets:
  - generation/GPT4
library_name: peft
license: apache-2.0
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: zephyr-dpo-qlora-gpt4-5e-6
    results: []

zephyr-dpo-qlora-gpt4-5e-6

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the generation/GPT4 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9318
  • Rewards/chosen: -6.0570
  • Rewards/rejected: -7.0161
  • Rewards/accuracies: 0.6430
  • Rewards/margins: 0.9590
  • Rewards/margins Max: 4.7709
  • Rewards/margins Min: -3.0068
  • Rewards/margins Std: 2.6570
  • Logps/rejected: -960.1845
  • Logps/chosen: -890.2942
  • Logits/rejected: -1.4367
  • Logits/chosen: -1.4956

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
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • total_eval_batch_size: 16
  • 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 Rewards/margins Max Rewards/margins Min Rewards/margins Std Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.3843 0.28 100 0.6754 -0.8222 -0.9456 0.6190 0.1235 0.8275 -0.5849 0.4661 -353.1436 -366.8085 -2.4707 -2.5001
0.1345 0.56 200 0.9115 -6.6830 -7.3423 0.6230 0.6594 4.1300 -2.9206 2.3615 -992.8121 -952.8915 -1.3494 -1.4037
0.0467 0.85 300 0.9371 -6.0411 -6.9811 0.6450 0.9400 4.7437 -3.0368 2.6550 -956.6877 -888.7039 -1.4320 -1.4909

Framework versions

  • PEFT 0.7.1
  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2