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: 0.3183
  • Rewards/chosen: -0.6032
  • Rewards/rejected: -2.1160
  • Rewards/accuracies: 0.8711
  • Rewards/margins: 1.5128
  • Logps/rejected: -584.2130
  • Logps/chosen: -439.6992
  • Logits/rejected: -5.8852
  • Logits/chosen: -5.4031

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
0.5118 0.1151 100 0.5923 -0.1120 -0.4506 0.7070 0.3386 -417.6701 -390.5766 -2.1984 -2.2213
0.4206 0.2303 200 0.5055 -0.2913 -1.0785 0.8008 0.7872 -480.4641 -408.5089 -3.2280 -3.1644
0.4144 0.3454 300 0.4504 -0.3084 -1.2736 0.7773 0.9651 -499.9700 -410.2218 -4.0963 -3.8861
0.4011 0.4606 400 0.4135 -0.4247 -1.5332 0.8086 1.1086 -525.9362 -421.8441 -4.8370 -4.5018
0.3915 0.5757 500 0.3740 -0.3892 -1.7143 0.8516 1.3251 -544.0394 -418.2938 -5.1877 -4.7675
0.3726 0.6908 600 0.3468 -0.4807 -1.8892 0.8438 1.4085 -561.5286 -427.4439 -5.6248 -5.1461
0.3522 0.8060 700 0.3249 -0.5431 -2.0476 0.8789 1.5044 -577.3692 -433.6906 -5.6819 -5.2107
0.3643 0.9211 800 0.3183 -0.6032 -2.1160 0.8711 1.5128 -584.2130 -439.6992 -5.8852 -5.4031

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.1.2+cu118
  • Datasets 2.16.1
  • Tokenizers 0.19.1