zephyr-7b-dpo-full / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
model-index:
  - name: zephyr-7b-dpo-full
    results: []

zephyr-7b-dpo-full

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5004
  • Rewards/chosen: -1.0684
  • Rewards/rejected: -2.0671
  • Rewards/accuracies: 0.7852
  • Rewards/margins: 0.9987
  • Logps/rejected: -469.3939
  • Logps/chosen: -369.4198
  • Logits/rejected: 0.7735
  • Logits/chosen: -0.2945

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: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • 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
0.5644 0.2092 100 0.5693 -0.4760 -0.9833 0.75 0.5073 -361.0131 -310.1760 -1.6463 -1.8042
0.5482 0.4184 200 0.5285 -0.5789 -1.3324 0.7812 0.7535 -395.9196 -320.4612 -1.1108 -1.6512
0.4952 0.6276 300 0.5067 -1.0198 -1.9482 0.7734 0.9284 -457.5016 -364.5515 0.5574 -0.3940
0.5037 0.8368 400 0.5006 -1.0395 -2.0108 0.7852 0.9713 -463.7658 -366.5239 0.6358 -0.3905

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0a0+f70bd71a48.nv24.06
  • Datasets 2.18.0
  • Tokenizers 0.20.0