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metadata
license: mit
base_model: EleutherAI/gpt-neo-125m
tags:
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: gpt-neo-125m_hh_reward
    results: []

gpt-neo-125m_hh_reward

This model is a DPO fine-tuned version of EleutherAI/gpt-neo-125m on Anthropics HH dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7764
  • Rewards/chosen: -1.0726
  • Rewards/rejected: -1.1588
  • Rewards/accuracies: 0.5592
  • Rewards/margins: 0.0861
  • Logps/rejected: -127.6699
  • Logps/chosen: -107.5507
  • Logits/rejected: -15.9221
  • Logits/chosen: -15.7406

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 150
  • training_steps: 20050

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.7685 0.1 2000 0.7585 -0.6757 -0.7643 0.5066 0.0886 -126.6837 -106.5583 -16.3107 -16.1234
0.795 0.2 4000 0.7531 -0.9330 -1.0793 0.5625 0.1463 -127.4711 -107.2016 -16.6020 -16.4468
0.7366 0.3 6000 0.7961 -1.0751 -1.1163 0.5033 0.0412 -127.5638 -107.5568 -16.3735 -16.2226
0.8288 0.4 8000 0.7860 -1.0546 -1.1457 0.5559 0.0911 -127.6372 -107.5056 -16.4345 -16.2588
0.7272 0.5 10000 0.7767 -1.1017 -1.2133 0.5658 0.1116 -127.8062 -107.6233 -16.2325 -16.0800
0.8404 0.6 12000 0.8029 -1.2133 -1.2948 0.5329 0.0815 -128.0099 -107.9024 -15.9207 -15.7572
0.8224 0.7 14000 0.7702 -1.0578 -1.1817 0.5625 0.1239 -127.7272 -107.5137 -15.9578 -15.7879
0.7267 0.8 16000 0.7929 -1.1534 -1.2255 0.5559 0.0721 -127.8368 -107.7526 -16.0551 -15.8740
0.6329 0.9 18000 0.8052 -1.0222 -1.0692 0.5428 0.0471 -127.4461 -107.4246 -15.8842 -15.7008
0.7247 1.0 20000 0.7764 -1.0726 -1.1588 0.5592 0.0861 -127.6699 -107.5507 -15.9221 -15.7406

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.15.0