zephyr-7b-dpo-full / README.md
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metadata
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
  - alignment-handbook
  - 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: 0.5026
  • Rewards/chosen: -1.0472
  • Rewards/rejected: -1.9901
  • Rewards/accuracies: 0.7619
  • Rewards/margins: 0.9430
  • Logps/rejected: -460.7913
  • Logps/chosen: -388.8264
  • Logits/rejected: 1.7625
  • Logits/chosen: 1.0392

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: 615
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 32
  • 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
0.5736 0.21 100 0.5842 -0.3837 -0.8468 0.7242 0.4632 -346.4596 -322.4754 -2.3510 -2.4330
0.5116 0.42 200 0.5308 -0.9042 -1.7331 0.7520 0.8289 -435.0859 -374.5288 0.5012 0.0459
0.5027 0.63 300 0.5084 -0.8877 -1.7467 0.7639 0.8590 -436.4478 -372.8834 1.8224 1.1385
0.4823 0.84 400 0.5037 -1.1953 -2.1521 0.7619 0.9568 -476.9852 -403.6375 1.9978 1.3075

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.0