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yassinechaouch/doplhin-dpo-mnlp

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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doplhin-dpo-mnlp

This model is a fine-tuned version of cognitivecomputations/dolphin-2.1-mistral-7b on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0533
  • —Rewards/chosen: 1.5359
  • —Rewards/rejected: -19.2198
  • —Rewards/accuracies: 0.9859
  • —Rewards/margins: 20.7558
  • —Logps/rejected: -297.6228
  • —Logps/chosen: -116.0773
  • —Logits/rejected: -2.0080
  • —Logits/chosen: -2.2270

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-05
  • —trainbatchsize: 6
  • —evalbatchsize: 6
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 1

Training results

Training LossEpochStepValidation LossRewards/chosenRewards/rejectedRewards/accuraciesRewards/marginsLogps/rejectedLogps/chosenLogits/rejectedLogits/chosen
0.18340.2313650.0205-4.0635-21.55160.988317.4881-320.9407-172.0718-2.2051-2.5538
0.31730.46261300.0478-3.7133-20.73650.981217.0232-312.7894-168.5696-1.7985-2.0459
0.04810.69401950.03921.3063-18.00620.988319.3124-285.4860-118.3736-1.8805-2.1378
0.00790.92532600.05331.5359-19.21980.985920.7558-297.6228-116.0773-2.0080-2.2270

Framework versions

  • —PEFT 0.11.1
  • —Transformers 4.41.1
  • —Pytorch 2.1.2+cu121
  • —Datasets 2.19.1
  • —Tokenizers 0.19.1