scotus-v10 / README.md
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End of training
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metadata
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-small-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: scotus-v10
    results: []

scotus-v10

This model is a fine-tuned version of nlpaueb/legal-bert-small-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7971
  • Accuracy: 0.8842

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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.67 1.0 1219 1.3781 0.5718
1.1539 2.0 2438 0.9619 0.7077
0.6736 3.0 3657 0.7837 0.7668
0.4265 4.0 4876 0.5882 0.8309
0.2477 5.0 6095 0.5624 0.8446
0.1636 6.0 7314 0.5701 0.8542
0.0938 7.0 8533 0.6322 0.8603
0.0523 8.0 9752 0.6717 0.8606
0.0397 9.0 10971 0.6626 0.8738
0.0236 10.0 12190 0.6729 0.8811
0.0129 11.0 13409 0.7164 0.876
0.0098 12.0 14628 0.8041 0.8723
0.0066 13.0 15847 0.7792 0.8794
0.0055 14.0 17066 0.7704 0.8792
0.0032 15.0 18285 0.8369 0.8768
0.0023 16.0 19504 0.8685 0.8737
0.0012 17.0 20723 0.7631 0.888
0.0026 18.0 21942 0.8220 0.8808
0.0011 19.0 23161 0.7897 0.8845
0.0003 20.0 24380 0.7971 0.8842

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3