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jpodivin/distilbert-base-cased-logdetective-extraction-retrained

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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distilbert-base-cased-logdetective-extraction-retrained

This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 2.3047

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: 2e-05
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 20

Training results

Training LossEpochStepValidation Loss
No log1.095.4981
No log2.0184.7485
No log3.0274.2960
No log4.0364.0269
No log5.0453.0733
No log6.0542.9759
No log7.0632.5961
No log8.0722.3365
No log9.0812.4470
No log10.0902.3994
No log11.0992.3914
No log12.01082.3324
No log13.01172.2978
No log14.01262.2797
No log15.01352.2886
No log16.01442.2969
No log17.01532.3091
No log18.01622.2597
No log19.01712.3080
No log20.01802.3047

Framework versions

  • —Transformers 4.35.2
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.16.1
  • —Tokenizers 0.15.1