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zephyr-dpo-qlora-gpt4-5e-6-epoch3

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the generation/GPT4 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8389
  • Rewards/chosen: -16.6323
  • Rewards/rejected: -19.5704
  • Rewards/accuracies: 0.6905
  • Rewards/margins: 2.9381
  • Rewards/margins Max: 11.9980
  • Rewards/margins Min: -5.2949
  • Rewards/margins Std: 7.7821
  • Logps/rejected: -2216.2207
  • Logps/chosen: -1948.4508
  • Logits/rejected: -1.4331
  • Logits/chosen: -1.5188

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-06
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 16
  • 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: 3

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Rewards/margins Max Rewards/margins Min Rewards/margins Std Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.4777 0.28 100 0.6755 -0.3600 -0.4244 0.6032 0.0644 0.3559 -0.2210 0.2529 -301.6254 -321.2222 -2.6312 -2.6710
0.1416 0.56 200 0.9053 -6.7040 -7.2161 0.6270 0.5121 2.7698 -1.7984 2.0239 -980.7882 -955.6170 -1.4055 -1.4608
0.0426 0.85 300 0.9213 -7.5636 -8.6200 0.6786 1.0563 4.2652 -2.1614 2.8565 -1121.1776 -1041.5824 -1.6508 -1.7101
0.0537 1.13 400 1.1419 -12.1996 -13.1820 0.6468 0.9824 5.4879 -3.0621 3.7889 -1577.3877 -1505.1829 -1.5926 -1.6576
0.0197 1.41 500 1.6844 -17.1495 -18.8730 0.6667 1.7235 9.4195 -5.1462 6.5774 -2146.4797 -2000.1663 -1.4330 -1.5026
0.0029 1.69 600 1.9743 -14.5461 -17.4661 0.6865 2.9200 12.4008 -5.7167 8.1643 -2005.7900 -1739.8331 -1.4547 -1.5331
0.018 1.97 700 1.8030 -16.5306 -19.1782 0.6786 2.6476 11.2308 -5.2715 7.4338 -2177.0017 -1938.2783 -1.4133 -1.4978
0.0014 2.25 800 1.8519 -16.7236 -19.4930 0.6746 2.7694 11.6630 -5.3047 7.6237 -2208.4844 -1957.5789 -1.4433 -1.5266
0.0034 2.54 900 1.6799 -16.1476 -18.7797 0.6865 2.6322 10.7631 -4.8758 7.0339 -2137.1570 -1899.9781 -1.4489 -1.5324
0.0118 2.82 1000 1.8351 -16.6710 -19.6029 0.6825 2.9319 11.9629 -5.2899 7.7662 -2219.4746 -1952.3245 -1.4296 -1.5156

Framework versions

  • PEFT 0.7.1
  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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