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metadata
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
tags:
  - generated_from_trainer
model-index:
  - name: zephyr-7b-dpo-full-beta-0.2
    results: []

zephyr-7b-dpo-full-beta-0.2

This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7903
  • Rewards/chosen: -3.2220
  • Rewards/rejected: -7.3367
  • Rewards/accuracies: 0.7659
  • Rewards/margins: 4.1147
  • Logps/rejected: -282.6258
  • Logps/chosen: -314.5996
  • Logits/rejected: -2.6943
  • Logits/chosen: -2.6970

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: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 32
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.5631 0.26 500 0.5260 0.0288 -1.2082 0.75 1.2371 -251.9833 -298.3453 -2.9467 -2.9577
0.5432 0.52 1000 0.5888 -0.0335 -1.8482 0.7540 1.8147 -255.1831 -298.6568 -2.8465 -2.8476
0.5368 0.77 1500 0.5860 -0.4836 -2.3300 0.7619 1.8464 -257.5920 -300.9073 -2.8455 -2.8445
0.0615 1.03 2000 0.6024 -0.5971 -2.6919 0.7778 2.0948 -259.4018 -301.4749 -2.8687 -2.8639
0.0817 1.29 2500 0.6655 -1.3554 -3.8426 0.7738 2.4872 -265.1552 -305.2667 -2.8257 -2.8254
0.0617 1.55 3000 0.6421 -1.2552 -3.7613 0.75 2.5062 -264.7488 -304.7651 -2.7744 -2.7683
0.0765 1.81 3500 0.6582 -1.1492 -4.0394 0.7659 2.8902 -266.1391 -304.2354 -2.7403 -2.7389
0.0178 2.07 4000 0.6797 -1.8485 -5.2549 0.7619 3.4064 -272.2166 -307.7317 -2.7310 -2.7273
0.0165 2.32 4500 0.7359 -2.2096 -6.0498 0.7817 3.8401 -276.1910 -309.5376 -2.7006 -2.7001
0.0094 2.58 5000 0.7864 -2.8828 -6.8542 0.7738 3.9713 -280.2130 -312.9036 -2.7185 -2.7196
0.0094 2.84 5500 0.7953 -3.1897 -7.3009 0.7579 4.1112 -282.4464 -314.4378 -2.6987 -2.7012

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1