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zephyr-7b-dpo-full-debug-regression

This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7240
  • Rewards/chosen: -4.3843
  • Rewards/rejected: -7.9101
  • Rewards/accuracies: 0.7640
  • Rewards/margins: 3.5258
  • Logps/rejected: -311.4621
  • Logps/chosen: -319.5667
  • Logits/rejected: -2.4790
  • Logits/chosen: -2.5088

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: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 32
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • 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 Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.533 0.26 500 0.5084 -0.1902 -1.3680 0.7780 1.1778 -246.0413 -277.6251 -2.9319 -2.9487
0.4907 0.52 1000 0.5234 -0.3346 -1.8153 0.7620 1.4807 -250.5139 -279.0693 -2.8401 -2.8442
0.4388 0.77 1500 0.5202 -0.7856 -2.2720 0.7920 1.4864 -255.0812 -283.5798 -2.7420 -2.7444
0.0651 1.03 2000 0.5049 -1.0044 -2.8702 0.7860 1.8658 -261.0635 -285.7675 -2.7335 -2.7412
0.0887 1.29 2500 0.5946 -1.9888 -3.9256 0.7480 1.9368 -271.6175 -295.6113 -2.5940 -2.6173
0.0747 1.55 3000 0.5748 -1.9590 -4.0271 0.7560 2.0681 -272.6327 -295.3135 -2.4969 -2.5205
0.101 1.81 3500 0.5783 -1.9521 -4.1853 0.7680 2.2332 -274.2144 -295.2442 -2.5069 -2.5278
0.0195 2.07 4000 0.6253 -2.9322 -5.7633 0.7600 2.8310 -289.9938 -305.0455 -2.4935 -2.5158
0.0191 2.32 4500 0.7215 -4.2183 -7.6216 0.7620 3.4034 -308.5774 -317.9060 -2.4756 -2.5036
0.0105 2.58 5000 0.7341 -4.2607 -7.7440 0.7600 3.4833 -309.8016 -318.3306 -2.5156 -2.5437
0.0092 2.84 5500 0.7330 -4.3756 -7.9435 0.7600 3.5679 -311.7966 -319.4794 -2.4856 -2.5149

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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