zephyr-7b-dpo-full / README.md
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metadata
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: zephyr-7b-dpo-full
    results: []

zephyr-7b-dpo-full

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8979
  • Rewards/chosen: -6.9869
  • Rewards/rejected: -8.4701
  • Rewards/accuracies: 0.6094
  • Rewards/margins: 1.4832
  • Logps/rejected: -1164.5387
  • Logps/chosen: -1010.4669
  • Logits/rejected: -0.5643
  • Logits/chosen: -0.7199

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
0.2555 0.1 100 1.4172 -4.8884 -5.6701 0.5898 0.7817 -884.5335 -800.6121 -1.3358 -1.3942
0.1854 0.21 200 1.6754 -6.1508 -7.3259 0.6211 1.1752 -1050.1200 -926.8517 -1.1088 -1.1853
0.1799 0.31 300 1.5590 -5.9157 -6.9794 0.5977 1.0637 -1015.4615 -903.3419 -1.0193 -1.1110
0.1679 0.42 400 2.1030 -7.8503 -9.2060 0.6094 1.3557 -1238.1252 -1096.8108 -0.5753 -0.7096
0.1693 0.52 500 1.6563 -6.3408 -7.6718 0.625 1.3310 -1084.7078 -945.8611 -0.8598 -0.9873
0.1609 0.63 600 1.6818 -6.4795 -7.7992 0.6211 1.3198 -1097.4480 -959.7227 -0.4515 -0.6164
0.1559 0.73 700 1.9278 -7.3485 -8.7955 0.6133 1.4470 -1197.0731 -1046.6217 -0.4166 -0.5852
0.1433 0.84 800 1.9050 -7.1496 -8.6252 0.6172 1.4756 -1180.0403 -1026.7318 -0.5141 -0.6745
0.1479 0.94 900 1.8979 -6.9869 -8.4701 0.6094 1.4832 -1164.5387 -1010.4669 -0.5643 -0.7199

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2+cu118
  • Datasets 2.16.1
  • Tokenizers 0.15.2