zephyr-7b-dpo-full / README.md
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metadata
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
  - trl
  - dpo
  - generated_from_trainer
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 an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5280
  • Rewards/chosen: -0.0160
  • Rewards/rejected: -1.2503
  • Rewards/accuracies: 0.7798
  • Rewards/margins: 1.2343
  • Logps/rejected: -272.7223
  • Logps/chosen: -282.1141
  • Logits/rejected: -2.5362
  • Logits/chosen: -2.5901

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: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • 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
0.5446 0.1047 100 0.5753 1.0111 0.3529 0.7242 0.6581 -256.6898 -271.8434 -2.5161 -2.5743
0.5475 0.2093 200 0.5464 0.4347 -0.4824 0.7639 0.9172 -265.0432 -277.6068 -2.5380 -2.5923
0.5359 0.3140 300 0.5473 0.0697 -1.0170 0.7579 1.0867 -270.3889 -281.2571 -2.5066 -2.5596
0.5228 0.4186 400 0.5321 -0.2311 -1.3065 0.7540 1.0754 -273.2837 -284.2652 -2.5933 -2.6471
0.5217 0.5233 500 0.5260 0.0143 -1.2073 0.7877 1.2216 -272.2919 -281.8111 -2.5195 -2.5773
0.517 0.6279 600 0.5262 -0.2922 -1.4562 0.7698 1.1640 -274.7808 -284.8755 -2.5183 -2.5744
0.4766 0.7326 700 0.5279 -0.0183 -1.2936 0.7798 1.2753 -273.1544 -282.1366 -2.5194 -2.5751
0.4894 0.8373 800 0.5257 -0.0567 -1.2594 0.7778 1.2027 -272.8127 -282.5211 -2.5311 -2.5851
0.4722 0.9419 900 0.5280 -0.0160 -1.2503 0.7798 1.2343 -272.7223 -282.1141 -2.5362 -2.5901

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.1.2
  • Datasets 2.19.1
  • Tokenizers 0.19.1