zephyr-7b-gemma-dpo / README.md
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metadata
base_model: HuggingFaceH4/zephyr-7b-gemma-sft-v0.1
datasets:
  - argilla/dpo-mix-7k
  - RedaAlami/PKU-SafeRLHF-Processed
library_name: peft
license: other
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
model-index:
  - name: zephyr-7b-gemma-dpo
    results: []

zephyr-7b-gemma-dpo

This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-gemma-sft-v0.1 on the argilla/dpo-mix-7k and the RedaAlami/PKU-SafeRLHF-Processed datasets. It achieves the following results on the evaluation set:

  • Loss: 0.6478
  • Rewards/chosen: -0.3452
  • Rewards/rejected: -0.5788
  • Rewards/accuracies: 0.6169
  • Rewards/margins: 0.2336
  • Logps/rejected: -334.5554
  • Logps/chosen: -295.9647
  • Logits/rejected: 436.0139
  • Logits/chosen: 452.6414

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: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • 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: 2

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.7052 0.2602 100 0.7032 0.1828 0.1374 0.5148 0.0454 -320.2303 -285.4035 437.8931 454.4476
0.6851 0.5205 200 0.6794 0.1534 0.0240 0.5991 0.1294 -322.4987 -285.9917 436.5674 453.2177
0.6545 0.7807 300 0.6632 -0.0335 -0.2290 0.5962 0.1955 -327.5587 -289.7299 435.9517 452.6035
0.6428 1.0410 400 0.6532 -0.3583 -0.5844 0.6154 0.2261 -334.6671 -296.2265 436.0371 452.6768
0.6366 1.3012 500 0.6521 -0.3063 -0.5602 0.6124 0.2539 -334.1831 -295.1856 436.1843 452.8112
0.6058 1.5615 600 0.6497 -0.3389 -0.5751 0.6139 0.2362 -334.4804 -295.8380 436.0276 452.6521
0.6368 1.8217 700 0.6449 -0.3403 -0.5854 0.6065 0.2451 -334.6864 -295.8665 436.0117 452.6395

Framework versions

  • PEFT 0.12.0
  • Transformers 4.43.3
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1