Hugging Face's logo

cite-text-analysis
/
case-analysis-bert-base-uncased

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
case-analysis-bert-base-uncased / README.md
cite-text-analysis's picture
cite-text-analysis
Upload README.md with huggingface_hub
0e8c745 verified
preview code
|
raw
history blame contribute delete
10.5 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
base_model: google-bert/bert-base-uncased
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: case-analysis-bert-base-uncased
    results: []

Metrics

  • loss: 1.7243
  • accuracy: 0.7996
  • precision: 0.7969
  • recall: 0.7996
  • precision_macro: 0.6535
  • recall_macro: 0.6526
  • macro_fpr: 0.0942
  • weighted_fpr: 0.0771
  • weighted_specificity: 0.8638
  • macro_specificity: 0.9158
  • weighted_sensitivity: 0.7996
  • macro_sensitivity: 0.6526
  • f1_micro: 0.7996
  • f1_macro: 0.6529
  • f1_weighted: 0.7982
  • runtime: 351.9249
  • samples_per_second: 1.2760
  • steps_per_second: 0.1620

case-analysis-bert-base-uncased

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

  • Loss: 1.7243
  • Accuracy: 0.7996
  • Precision: 0.7969
  • Recall: 0.7996
  • Precision Macro: 0.6427
  • Recall Macro: 0.6184
  • Macro Fpr: 0.0946
  • Weighted Fpr: 0.0712
  • Weighted Specificity: 0.8449
  • Macro Specificity: 0.9145
  • Weighted Sensitivity: 0.8129
  • Macro Sensitivity: 0.6184
  • F1 Micro: 0.8129
  • F1 Macro: 0.6284
  • F1 Weighted: 0.8035

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 0.7283 0.7862 0.7487 0.7862 0.5848 0.5572 0.1142 0.0831 0.8036 0.8974 0.7862 0.5572 0.7862 0.5606 0.7597
No log 2.0 448 0.8160 0.7996 0.7603 0.7996 0.5770 0.6065 0.0997 0.0771 0.8417 0.9103 0.7996 0.6065 0.7996 0.5914 0.7794
0.6512 3.0 672 0.8588 0.7906 0.7598 0.7906 0.5770 0.5989 0.1005 0.0811 0.8512 0.9105 0.7906 0.5989 0.7906 0.5840 0.7720
0.6512 4.0 896 1.0821 0.7817 0.7819 0.7817 0.6214 0.6429 0.0996 0.0851 0.8679 0.9124 0.7817 0.6429 0.7817 0.6299 0.7805
0.3466 5.0 1120 1.0612 0.8085 0.7999 0.8085 0.7129 0.6263 0.0948 0.0732 0.8470 0.9139 0.8085 0.6263 0.8085 0.6195 0.7928
0.3466 6.0 1344 1.2559 0.7929 0.7877 0.7929 0.6206 0.6362 0.0951 0.0801 0.8717 0.9161 0.7929 0.6362 0.7929 0.6273 0.7897
0.1715 7.0 1568 1.3701 0.7929 0.7889 0.7929 0.6345 0.6179 0.0991 0.0801 0.8558 0.9122 0.7929 0.6179 0.7929 0.6237 0.7893
0.1715 8.0 1792 1.4005 0.8107 0.8035 0.8107 0.6578 0.6370 0.0922 0.0722 0.8607 0.9179 0.8107 0.6370 0.8107 0.6464 0.8064
0.0636 9.0 2016 1.4737 0.8018 0.7881 0.8018 0.6583 0.6149 0.1026 0.0761 0.8271 0.9072 0.8018 0.6149 0.8018 0.6263 0.7896
0.0636 10.0 2240 1.7569 0.7884 0.7962 0.7884 0.6275 0.6428 0.0960 0.0821 0.8750 0.9158 0.7884 0.6428 0.7884 0.6332 0.7909
0.0636 11.0 2464 1.7141 0.7906 0.7824 0.7906 0.6166 0.6083 0.1035 0.0811 0.8424 0.9083 0.7906 0.6083 0.7906 0.6101 0.7845
0.0159 12.0 2688 1.7144 0.7951 0.7914 0.7951 0.6393 0.6413 0.0969 0.0791 0.8610 0.9140 0.7951 0.6413 0.7951 0.6373 0.7917
0.0159 13.0 2912 1.7243 0.7996 0.7969 0.7996 0.6535 0.6526 0.0942 0.0771 0.8638 0.9158 0.7996 0.6526 0.7996 0.6529 0.7982
0.0043 14.0 3136 1.8551 0.7973 0.7948 0.7973 0.6576 0.6189 0.1041 0.0781 0.8314 0.9072 0.7973 0.6189 0.7973 0.6335 0.7912
0.0043 15.0 3360 1.8841 0.7929 0.7869 0.7929 0.6154 0.6162 0.1008 0.0801 0.8511 0.9110 0.7929 0.6162 0.7929 0.6104 0.7861
0.0029 16.0 3584 2.0853 0.7550 0.7837 0.7550 0.6010 0.6119 0.1100 0.0976 0.8698 0.9062 0.7550 0.6119 0.7550 0.6015 0.7661
0.0029 17.0 3808 1.9722 0.7840 0.7783 0.7840 0.6018 0.5839 0.1076 0.0841 0.8394 0.9059 0.7840 0.5839 0.7840 0.5917 0.7797
0.0071 18.0 4032 1.8735 0.7996 0.7783 0.7996 0.6086 0.5917 0.1053 0.0771 0.8193 0.9047 0.7996 0.5917 0.7996 0.5960 0.7840
0.0071 19.0 4256 1.8294 0.8018 0.7840 0.8018 0.6114 0.5943 0.1025 0.0761 0.8308 0.9082 0.8018 0.5943 0.8018 0.6001 0.7895
0.0071 20.0 4480 1.8578 0.7973 0.7939 0.7973 0.6367 0.6232 0.0990 0.0781 0.8497 0.9118 0.7973 0.6232 0.7973 0.6285 0.7942
0.0049 21.0 4704 1.8770 0.7973 0.7939 0.7973 0.6367 0.6232 0.0990 0.0781 0.8497 0.9118 0.7973 0.6232 0.7973 0.6285 0.7942
0.0049 22.0 4928 1.8932 0.7951 0.7876 0.7951 0.6219 0.6119 0.1007 0.0791 0.8461 0.9103 0.7951 0.6119 0.7951 0.6155 0.7900
0.0015 23.0 5152 1.9834 0.7996 0.7965 0.7996 0.6441 0.6389 0.0960 0.0771 0.8599 0.9149 0.7996 0.6389 0.7996 0.6403 0.7971
0.0015 24.0 5376 1.9926 0.8018 0.7984 0.8018 0.6468 0.6399 0.0952 0.0761 0.8603 0.9155 0.8018 0.6399 0.8018 0.6422 0.7991
0.0001 25.0 5600 1.9771 0.7973 0.7790 0.7973 0.6025 0.6024 0.1011 0.0781 0.8420 0.9098 0.7973 0.6024 0.7973 0.6017 0.7871
0.0001 26.0 5824 1.9871 0.7951 0.7770 0.7951 0.5996 0.6015 0.1020 0.0791 0.8416 0.9092 0.7951 0.6015 0.7951 0.5997 0.7850
0.0 27.0 6048 1.8756 0.8129 0.7961 0.8129 0.6440 0.6200 0.0939 0.0712 0.8462 0.9148 0.8129 0.6200 0.8129 0.6293 0.8029
0.0 28.0 6272 1.8473 0.8151 0.7998 0.8151 0.6463 0.6194 0.0937 0.0703 0.8453 0.9151 0.8151 0.6194 0.8151 0.6305 0.8056
0.0 29.0 6496 1.8525 0.8129 0.7975 0.8129 0.6427 0.6184 0.0946 0.0712 0.8449 0.9145 0.8129 0.6184 0.8129 0.6284 0.8035
0.0001 30.0 6720 1.8540 0.8129 0.7975 0.8129 0.6427 0.6184 0.0946 0.0712 0.8449 0.9145 0.8129 0.6184 0.8129 0.6284 0.8035

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1