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 the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6824
  • Rewards/chosen: -4.2277
  • Rewards/rejected: -7.2864
  • Rewards/accuracies: 0.7773
  • Rewards/margins: 3.0587
  • Logps/rejected: -408.3961
  • Logps/chosen: -347.1476
  • Logits/rejected: -0.8310
  • Logits/chosen: -1.2135

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: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • 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 Logits/chosen Logits/rejected Logps/chosen Logps/rejected Validation Loss Rewards/accuracies Rewards/chosen Rewards/margins Rewards/rejected
0.582 0.21 100 -2.5812 -2.5431 -254.2386 -263.2876 0.5878 0.7188 0.4177 0.4488 -0.0310
0.558 0.42 200 -2.3893 -2.3398 -261.4734 -280.4191 0.5196 0.7773 0.0560 0.9436 -0.8876
0.4914 0.63 300 -2.3653 -2.3039 -264.2936 -286.6201 0.5110 0.7656 -0.0850 1.1126 -1.1976
0.4922 0.84 400 -2.3145 -2.2570 -263.2854 -285.4248 0.5095 0.7852 -0.0346 1.1033 -1.1379
0.1908 1.05 500 -2.2442 -2.1660 -269.8426 -300.6474 0.5179 0.7852 -0.3625 1.5366 -1.8990
0.1675 1.26 600 -2.2220 -2.1249 -287.2300 -324.0812 0.5377 0.8008 -1.2318 1.8389 -3.0707
0.1567 1.46 700 -2.0453 -1.9285 -298.7820 -333.3354 0.5348 0.7891 -1.8094 1.7240 -3.5334
0.1475 1.67 800 -2.2409 -2.1202 -296.3533 -332.4951 0.5382 0.8008 -1.6880 1.8034 -3.4914
0.1422 1.88 900 -2.1980 -2.0630 -296.0324 -335.6016 0.5518 0.7852 -1.6719 1.9748 -3.6467
0.044 2.09 1000 -1.7406 -1.4629 -316.4520 -365.4959 0.6058 0.7891 -2.6929 2.4485 -5.1414
0.0307 2.3 1100 -1.3310 -0.9162 -337.0383 -397.1617 0.6700 0.7695 -3.7222 3.0025 -6.7247
0.0317 2.51 1200 0.6711 -3.9616 -6.9639 0.7773 3.0023 -401.9448 -341.8261 -0.9227 -1.2927
0.0264 2.72 1300 0.6778 -4.2314 -7.2584 0.7773 3.0270 -407.8352 -347.2216 -0.8370 -1.2190
0.0343 2.93 1400 0.6824 -4.2277 -7.2864 0.7773 3.0587 -408.3961 -347.1476 -0.8310 -1.2135

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2+cu118
  • Datasets 2.16.1
  • Tokenizers 0.15.2