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zephyr-7b-dpo-full

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3377
  • Rewards/chosen: -14.5626
  • Rewards/rejected: -18.1281
  • Rewards/accuracies: 0.6389
  • Rewards/margins: 3.5654
  • Logps/rejected: -2073.0146
  • Logps/chosen: -1738.2311
  • Logits/rejected: -0.6819
  • Logits/chosen: -1.0035

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
4.5854 0.1047 100 4.3811 -0.2719 -0.4992 0.6488 0.2273 -310.1242 -309.1552 -2.1923 -2.2813
2.6464 0.2093 200 2.6063 -9.6247 -11.6315 0.625 2.0068 -1423.3580 -1244.4360 0.6982 -0.3562
1.9069 0.3140 300 2.2624 -9.8468 -11.9256 0.6329 2.0788 -1452.7675 -1266.6490 1.5569 0.4590
1.6642 0.4186 400 1.6421 -14.4918 -17.8494 0.625 3.3576 -2045.1493 -1731.1526 -0.0875 -0.7751
1.6328 0.5233 500 1.5120 -13.0737 -16.3036 0.6389 3.2299 -1890.5623 -1589.3370 -0.0918 -0.6590
1.6032 0.6279 600 1.4752 -17.3374 -21.4238 0.6230 4.0864 -2402.5845 -2015.7072 0.6402 0.0190
1.5039 0.7326 700 1.3853 -14.1299 -17.5624 0.6528 3.4325 -2016.4491 -1694.9624 -0.4968 -0.8898
1.3527 0.8373 800 1.3663 -13.9016 -17.2583 0.6448 3.3567 -1986.0359 -1672.1306 -0.6750 -1.0375
1.5137 0.9419 900 1.3374 -14.5395 -18.1313 0.6409 3.5918 -2073.3389 -1735.9152 -0.6740 -1.0018

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.1.2+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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