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Intent-classification-BERT-Large-Ashu

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metadata
license: apache-2.0
base_model: google-bert/bert-large-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: Intent-classification-BERT-Large-Ashu
    results: []

Intent-classification-BERT-Large-Ashu

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

  • Loss: 0.6944
  • Accuracy: 0.8730
  • F1: 0.7885
  • Precision: 0.7819
  • Recall: 0.7981

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: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
1.5058 0.62 10 1.4327 0.4839 0.3327 0.31 0.4444
1.256 1.25 20 1.3362 0.5 0.3477 0.3129 0.4630
1.1161 1.88 30 1.2563 0.5323 0.4083 0.3988 0.5121
0.9064 2.5 40 1.1297 0.6613 0.5365 0.4832 0.6219
0.8284 3.12 50 1.0384 0.6935 0.5968 0.6653 0.6608
0.7162 3.75 60 0.9845 0.7419 0.6827 0.7087 0.7196
0.6173 4.38 70 0.8139 0.7419 0.6978 0.7040 0.7323
0.5229 5.0 80 0.7709 0.7742 0.7368 0.7158 0.7799
0.3564 5.62 90 0.7867 0.7742 0.7360 0.7109 0.7799
0.2924 6.25 100 0.6311 0.8065 0.7716 0.7489 0.8148
0.2573 6.88 110 0.6294 0.7742 0.7520 0.7264 0.7926
0.1957 7.5 120 0.6557 0.7742 0.7520 0.7264 0.7926
0.1624 8.12 130 0.7556 0.8065 0.7716 0.7489 0.8148
0.1594 8.75 140 0.5861 0.7903 0.7663 0.7461 0.8037
0.1699 9.38 150 0.8326 0.8065 0.7716 0.7489 0.8148
0.1817 10.0 160 0.6722 0.7419 0.7487 0.7361 0.7704
0.1366 10.62 170 0.8913 0.7581 0.7549 0.7397 0.7815
0.1584 11.25 180 0.8597 0.7742 0.7607 0.7431 0.7926
0.139 11.88 190 0.9325 0.7742 0.7607 0.7431 0.7926
0.0953 12.5 200 0.9940 0.7419 0.7487 0.7361 0.7704
0.1752 13.12 210 0.9987 0.7419 0.7487 0.7361 0.7704
0.1289 13.75 220 0.9073 0.7419 0.7487 0.7361 0.7704
0.1174 14.38 230 1.0821 0.7742 0.7607 0.7431 0.7926
0.1009 15.0 240 1.1234 0.7742 0.7607 0.7431 0.7926
0.1161 15.62 250 1.1751 0.7581 0.7549 0.7397 0.7815
0.1026 16.25 260 1.0199 0.7419 0.7487 0.7361 0.7704
0.1161 16.88 270 1.1464 0.7419 0.7487 0.7361 0.7704
0.0833 17.5 280 1.3141 0.7581 0.7549 0.7397 0.7815
0.1129 18.12 290 1.2621 0.7419 0.7487 0.7361 0.7704
0.1009 18.75 300 1.2209 0.7419 0.7487 0.7361 0.7704
0.1035 19.38 310 1.2660 0.7419 0.7487 0.7361 0.7704
0.1111 20.0 320 1.3104 0.7419 0.7487 0.7361 0.7704
0.1019 20.62 330 1.1838 0.7419 0.7487 0.7361 0.7704
0.0878 21.25 340 1.3183 0.7581 0.7549 0.7397 0.7815
0.1061 21.88 350 1.3650 0.7742 0.7607 0.7431 0.7926
0.1002 22.5 360 1.3588 0.7742 0.7607 0.7431 0.7926
0.1241 23.12 370 1.3529 0.7581 0.7549 0.7397 0.7815
0.1201 23.75 380 1.3213 0.7419 0.7487 0.7361 0.7704
0.084 24.38 390 1.3139 0.7419 0.7487 0.7361 0.7704
0.0988 25.0 400 1.3140 0.7581 0.7549 0.7397 0.7815
0.1049 25.62 410 1.3251 0.7581 0.7549 0.7397 0.7815
0.1168 26.25 420 1.3551 0.7581 0.7549 0.7397 0.7815
0.0931 26.88 430 1.3606 0.7581 0.7549 0.7397 0.7815
0.0872 27.5 440 1.3645 0.7581 0.7549 0.7397 0.7815
0.0942 28.12 450 1.3630 0.7581 0.7549 0.7397 0.7815
0.0941 28.75 460 1.3679 0.7581 0.7549 0.7397 0.7815
0.07 29.38 470 1.3761 0.7581 0.7549 0.7397 0.7815
0.112 30.0 480 1.3795 0.7581 0.7549 0.7397 0.7815

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2