mistral-7b-grok / README.md
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metadata
license: apache-2.0
base_model: HuggingFaceH4/mistral-7b-cai
tags:
  - alignment-handbook
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized_fixed
  - HuggingFaceH4/grok-conversation-harmless
model-index:
  - name: mistral-7b-dpo-v21.0grokai.0.3
    results: []

mistral-7b-dpo-v21.0grokai.0.3

This model is a fine-tuned version of HuggingFaceH4/mistral-7b-cai on the HuggingFaceH4/ultrafeedback_binarized_fixed and the HuggingFaceH4/grok-conversation-harmless datasets. It achieves the following results on the evaluation set:

  • Loss: 0.6270
  • Rewards/chosen: -7.6611
  • Rewards/rejected: -12.0970
  • Rewards/accuracies: 0.6925
  • Rewards/margins: 4.4359
  • Logps/rejected: -310.5013
  • Logps/chosen: -278.5390
  • Logits/rejected: -2.1614
  • Logits/chosen: -2.1988

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: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 16
  • total_eval_batch_size: 64
  • 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
0.5994 0.1 400 0.5895 0.3053 -0.0377 0.5950 0.3430 -189.9080 -198.8744 -2.6272 -2.6485
0.5024 0.19 800 0.5112 -0.1278 -1.0425 0.6675 0.9147 -199.9562 -203.2059 -2.5093 -2.5329
0.5728 0.29 1200 0.5324 -0.7435 -1.7880 0.6425 1.0445 -207.4112 -209.3627 -2.4771 -2.5058
0.7378 0.39 1600 0.5213 -1.6390 -2.9308 0.6650 1.2918 -218.8383 -218.3174 -2.4237 -2.4525
0.7467 0.48 2000 0.5788 -2.2099 -3.4247 0.6575 1.2148 -223.7781 -224.0264 -2.4106 -2.4441
0.4646 0.58 2400 0.5309 -1.1360 -2.6997 0.6500 1.5638 -216.5279 -213.2871 -2.3683 -2.3994
0.7454 0.67 2800 0.5290 -1.9997 -3.5594 0.6700 1.5597 -225.1247 -221.9242 -2.4289 -2.4575
0.6092 0.77 3200 0.5124 -1.6120 -3.1452 0.6850 1.5332 -220.9823 -218.0472 -2.4755 -2.5024
0.674 0.87 3600 0.5134 -2.9907 -4.6954 0.6750 1.7046 -236.4846 -231.8350 -2.2564 -2.2885
0.5585 0.96 4000 0.5065 -2.5232 -4.1851 0.6725 1.6619 -231.3815 -227.1594 -2.3968 -2.4273
0.0829 1.06 4400 0.5306 -3.8333 -6.1055 0.6950 2.2723 -250.5862 -240.2602 -2.2149 -2.2565
0.1383 1.16 4800 0.5432 -3.8147 -5.7333 0.6675 1.9186 -246.8635 -240.0743 -2.3301 -2.3643
0.1425 1.25 5200 0.5238 -4.7732 -7.0560 0.6650 2.2827 -260.0906 -249.6600 -2.1705 -2.2021
0.1053 1.35 5600 0.5298 -4.8922 -7.5361 0.6900 2.6439 -264.8917 -250.8497 -2.2597 -2.2978
0.1301 1.44 6000 0.5190 -4.0353 -6.5781 0.6850 2.5428 -255.3118 -242.2802 -2.1606 -2.1992
0.0789 1.54 6400 0.5184 -4.6125 -7.3571 0.6775 2.7446 -263.1015 -248.0527 -2.2220 -2.2593
0.1274 1.64 6800 0.5138 -3.9081 -6.5224 0.6650 2.6143 -254.7549 -241.0087 -2.3238 -2.3653
0.1095 1.73 7200 0.5153 -4.1355 -6.9746 0.6750 2.8392 -259.2772 -243.2823 -2.2983 -2.3396
0.1515 1.83 7600 0.5242 -4.5052 -7.4464 0.6625 2.9412 -263.9946 -246.9796 -2.2513 -2.2896
0.1152 1.93 8000 0.5280 -4.5281 -7.5632 0.6825 3.0351 -265.1628 -247.2084 -2.2822 -2.3185
0.0385 2.02 8400 0.5478 -4.9592 -8.1827 0.6800 3.2235 -271.3580 -251.5196 -2.2850 -2.3214
0.0401 2.12 8800 0.5999 -6.1863 -10.0632 0.6800 3.8769 -290.1624 -263.7904 -2.1925 -2.2326
0.0327 2.21 9200 0.6190 -5.6591 -9.4406 0.6925 3.7815 -283.9365 -258.5182 -2.1369 -2.1748
0.0425 2.31 9600 0.6298 -7.3701 -11.3769 0.6925 4.0068 -303.3002 -275.6286 -2.1410 -2.1775
0.0387 2.41 10000 0.6269 -7.3259 -11.5280 0.6975 4.2020 -304.8104 -275.1870 -2.1791 -2.2169
0.043 2.5 10400 0.6376 -7.2239 -11.5783 0.6925 4.3544 -305.3137 -274.1667 -2.2301 -2.2663
0.0577 2.6 10800 0.6290 -7.6726 -11.9683 0.6925 4.2956 -309.2136 -278.6540 -2.1968 -2.2342
0.019 2.7 11200 0.6260 -7.2301 -11.5298 0.6825 4.2997 -304.8287 -274.2284 -2.1623 -2.2006
0.0328 2.79 11600 0.6325 -7.6096 -12.0115 0.6950 4.4019 -309.6460 -278.0234 -2.1388 -2.1767
0.036 2.89 12000 0.6312 -7.8237 -12.2628 0.6900 4.4391 -312.1590 -280.1643 -2.1641 -2.2011
0.0216 2.98 12400 0.6283 -7.6679 -12.0919 0.6900 4.4240 -310.4496 -278.6061 -2.1613 -2.1986

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0