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indic-bert-finetuned-ours-DS

Text Classification
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PyTorch
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albert
Generated from Trainer
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: indic-bert-finetuned-ours-DS
    results: []

indic-bert-finetuned-ours-DS

This model is a fine-tuned version of ai4bharat/indic-bert on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1832
  • Accuracy: 0.655
  • Precision: 0.6023
  • Recall: 0.6027
  • F1: 0.6025

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 43
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
1.0681 0.99 99 1.0180 0.365 0.3435 0.4038 0.2773
0.9384 1.98 198 0.8475 0.62 0.6235 0.5610 0.4821
0.8201 2.97 297 0.8187 0.68 0.6839 0.6086 0.5812
0.7178 3.96 396 0.7717 0.7 0.7117 0.6670 0.6470
0.62 4.95 495 0.7839 0.66 0.6165 0.6244 0.6174
0.5135 5.94 594 0.8392 0.675 0.6270 0.6234 0.6246
0.4073 6.93 693 0.8930 0.665 0.6251 0.6254 0.6240
0.3365 7.92 792 0.9362 0.675 0.6298 0.6276 0.6242
0.2719 8.91 891 1.0108 0.685 0.6388 0.6293 0.6326
0.2007 9.9 990 1.1214 0.675 0.6300 0.6299 0.6290
0.1567 10.89 1089 1.1367 0.67 0.6193 0.6212 0.6178
0.1074 11.88 1188 1.3157 0.65 0.6292 0.6317 0.6227
0.0821 12.87 1287 1.5412 0.665 0.6415 0.6330 0.6259
0.0588 13.86 1386 1.7215 0.64 0.5862 0.5869 0.5865
0.0337 14.85 1485 1.7556 0.64 0.6078 0.6082 0.6032
0.0244 15.84 1584 1.8713 0.66 0.6173 0.6186 0.6158
0.0166 16.83 1683 1.9666 0.66 0.5995 0.5973 0.5973
0.0124 17.82 1782 1.9245 0.66 0.6165 0.6194 0.6163
0.0079 18.81 1881 2.0814 0.65 0.6026 0.6023 0.6012
0.0051 19.8 1980 2.1029 0.645 0.6014 0.5986 0.5975
0.0031 20.79 2079 2.1155 0.655 0.6029 0.6027 0.6023
0.0029 21.78 2178 2.1221 0.655 0.6 0.6000 0.5999
0.0021 22.77 2277 2.2065 0.65 0.5917 0.5898 0.5905
0.0017 23.76 2376 2.1903 0.65 0.5910 0.5898 0.5902
0.0016 24.75 2475 2.1832 0.655 0.6023 0.6027 0.6025

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.10.1+cu111
  • Datasets 2.3.2
  • Tokenizers 0.12.1