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case-analysis-legal-bert-base-uncased

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metadata
license: cc-by-sa-4.0
tags:
  - generated_from_trainer
base_model: nlpaueb/legal-bert-base-uncased
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: case-analysis-legal-bert-base-uncased
    results: []

Metrics

  • loss: 1.0628
  • accuracy: 0.8708
  • precision: 0.8661
  • recall: 0.8708
  • precision_macro: 0.8180
  • recall_macro: 0.6890
  • macro_fpr: 0.0681
  • weighted_fpr: 0.0471
  • weighted_specificity: 0.8788
  • macro_specificity: 0.9374
  • weighted_sensitivity: 0.8708
  • macro_sensitivity: 0.6890
  • f1_micro: 0.8708
  • f1_macro: 0.7165
  • f1_weighted: 0.8586
  • runtime: 13.9241
  • samples_per_second: 32.2460
  • steps_per_second: 4.0940

case-analysis-legal-bert-base-uncased

This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3822
  • Accuracy: 0.8263
  • Precision: 0.8205
  • Recall: 0.8263
  • Precision Macro: 0.6455
  • Recall Macro: 0.6413
  • Macro Fpr: 0.0910
  • Weighted Fpr: 0.0732
  • Weighted Specificity: 0.8622
  • Macro Specificity: 0.9177
  • Weighted Sensitivity: 0.8085
  • Macro Sensitivity: 0.6413
  • F1 Micro: 0.8085
  • F1 Macro: 0.6429
  • F1 Weighted: 0.8061

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
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall Precision Macro Recall Macro Macro Fpr Weighted Fpr Weighted Specificity Macro Specificity Weighted Sensitivity Macro Sensitivity F1 Micro F1 Macro F1 Weighted
No log 1.0 224 1.0114 0.6570 0.6179 0.6570 0.4664 0.4075 0.1948 0.1482 0.6727 0.8324 0.6570 0.4075 0.6570 0.4081 0.6166
No log 2.0 448 0.7650 0.7751 0.7425 0.7751 0.5566 0.5806 0.1094 0.0882 0.8406 0.9039 0.7751 0.5806 0.7751 0.5659 0.7564
0.7677 3.0 672 0.7342 0.7817 0.7695 0.7817 0.5674 0.5967 0.1041 0.0851 0.8515 0.9083 0.7817 0.5967 0.7817 0.5707 0.7678
0.7677 4.0 896 0.7968 0.8174 0.7766 0.8174 0.6036 0.5893 0.0965 0.0693 0.8368 0.9136 0.8174 0.5893 0.8174 0.5904 0.7921
0.482 5.0 1120 0.8171 0.8085 0.7853 0.8085 0.6366 0.6038 0.0990 0.0732 0.8346 0.9108 0.8085 0.6038 0.8085 0.6141 0.7940
0.482 6.0 1344 0.8910 0.8241 0.8028 0.8241 0.6660 0.6359 0.0875 0.0664 0.8606 0.9212 0.8241 0.6359 0.8241 0.6315 0.8084
0.2993 7.0 1568 1.0094 0.8040 0.8109 0.8040 0.6742 0.6774 0.0891 0.0751 0.8829 0.9217 0.8040 0.6774 0.8040 0.6742 0.8067
0.2993 8.0 1792 1.1504 0.8107 0.7968 0.8107 0.6228 0.6330 0.0897 0.0722 0.8708 0.9204 0.8107 0.6330 0.8107 0.6229 0.8016
0.1367 9.0 2016 1.2533 0.8062 0.8059 0.8062 0.6537 0.6225 0.0948 0.0742 0.8595 0.9164 0.8062 0.6225 0.8062 0.6360 0.8045
0.1367 10.0 2240 1.2516 0.8174 0.8107 0.8174 0.6621 0.6499 0.0873 0.0693 0.8701 0.9219 0.8174 0.6499 0.8174 0.6554 0.8137
0.1367 11.0 2464 1.3822 0.8263 0.8205 0.8263 0.7085 0.6696 0.0833 0.0655 0.8711 0.9243 0.8263 0.6696 0.8263 0.6764 0.8195
0.055 12.0 2688 1.4574 0.8018 0.8127 0.8018 0.6369 0.6443 0.0883 0.0761 0.8844 0.9216 0.8018 0.6443 0.8018 0.6399 0.8068
0.055 13.0 2912 1.6634 0.7884 0.7810 0.7884 0.6090 0.6042 0.1002 0.0821 0.8619 0.9126 0.7884 0.6042 0.7884 0.6042 0.7831
0.0431 14.0 3136 1.5085 0.8285 0.8077 0.8285 0.6476 0.6367 0.0850 0.0645 0.8633 0.9229 0.8285 0.6367 0.8285 0.6382 0.8166
0.0431 15.0 3360 1.6411 0.8107 0.7936 0.8107 0.6243 0.6262 0.0914 0.0722 0.8626 0.9183 0.8107 0.6262 0.8107 0.6229 0.8014
0.0135 16.0 3584 1.7483 0.8062 0.7925 0.8062 0.6201 0.6271 0.0923 0.0742 0.8647 0.9177 0.8062 0.6271 0.8062 0.6221 0.7988
0.0135 17.0 3808 1.7233 0.7973 0.7897 0.7973 0.6148 0.6263 0.0942 0.0781 0.8682 0.9164 0.7973 0.6263 0.7973 0.6201 0.7933
0.0066 18.0 4032 1.6457 0.8241 0.8042 0.8241 0.6515 0.6388 0.0879 0.0664 0.8522 0.9191 0.8241 0.6388 0.8241 0.6391 0.8115
0.0066 19.0 4256 1.6614 0.8174 0.7976 0.8174 0.6324 0.6420 0.0865 0.0693 0.8703 0.9219 0.8174 0.6420 0.8174 0.6318 0.8061
0.0066 20.0 4480 1.6997 0.8129 0.8023 0.8129 0.6435 0.6576 0.0860 0.0712 0.8759 0.9222 0.8129 0.6576 0.8129 0.6462 0.8061
0.0067 21.0 4704 1.6540 0.8218 0.8000 0.8218 0.6473 0.6380 0.0880 0.0674 0.8560 0.9195 0.8218 0.6380 0.8218 0.6356 0.8088
0.0067 22.0 4928 1.7329 0.8085 0.7945 0.8085 0.6313 0.6267 0.0930 0.0732 0.8548 0.9158 0.8085 0.6267 0.8085 0.6282 0.8011
0.0028 23.0 5152 1.7949 0.8062 0.8004 0.8062 0.6365 0.6419 0.0902 0.0742 0.8708 0.9193 0.8062 0.6419 0.8062 0.6389 0.8032
0.0028 24.0 5376 1.8086 0.8085 0.8026 0.8085 0.6387 0.6429 0.0893 0.0732 0.8715 0.9200 0.8085 0.6429 0.8085 0.6405 0.8054
0.0001 25.0 5600 1.8326 0.8085 0.7988 0.8085 0.6343 0.6251 0.0934 0.0732 0.8537 0.9155 0.8085 0.6251 0.8085 0.6287 0.8028
0.0001 26.0 5824 1.8395 0.8085 0.7988 0.8085 0.6343 0.6251 0.0934 0.0732 0.8537 0.9155 0.8085 0.6251 0.8085 0.6287 0.8028
0.0003 27.0 6048 1.8816 0.8062 0.8039 0.8062 0.6439 0.6388 0.0920 0.0742 0.8621 0.9171 0.8062 0.6388 0.8062 0.6408 0.8046
0.0003 28.0 6272 1.8956 0.8062 0.8039 0.8062 0.6439 0.6388 0.0920 0.0742 0.8621 0.9171 0.8062 0.6388 0.8062 0.6408 0.8046
0.0003 29.0 6496 1.8986 0.8062 0.8039 0.8062 0.6439 0.6388 0.0920 0.0742 0.8621 0.9171 0.8062 0.6388 0.8062 0.6408 0.8046
0.0 30.0 6720 1.8999 0.8085 0.8045 0.8085 0.6455 0.6413 0.0910 0.0732 0.8622 0.9177 0.8085 0.6413 0.8085 0.6429 0.8061

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1