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update model card README.md
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: indic-bert-finetuned-code-mixed-DS
    results: []

indic-bert-finetuned-code-mixed-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: 0.8647
  • Accuracy: 0.5795
  • Precision: 0.5485
  • Recall: 0.5287
  • F1: 0.4391

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-06
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 43
  • 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 Precision Recall F1
1.0937 2.0 497 1.0813 0.3602 0.3587 0.4257 0.2834
1.0189 3.99 994 0.9482 0.5493 0.3887 0.5246 0.4080
0.9208 5.99 1491 0.9002 0.5714 0.3813 0.5292 0.4170
0.8803 7.98 1988 0.8758 0.5654 0.3889 0.5300 0.4159
0.8482 9.98 2485 0.8657 0.5795 0.3867 0.5365 0.4228
0.8293 11.98 2982 0.8734 0.5835 0.3796 0.5298 0.4214
0.8131 13.97 3479 0.8567 0.5835 0.5018 0.5414 0.4350
0.8 15.97 3976 0.8547 0.5835 0.5610 0.5460 0.4361
0.7933 17.96 4473 0.8650 0.5775 0.5317 0.5252 0.4373
0.7835 19.96 4970 0.8647 0.5795 0.5485 0.5287 0.4391

Framework versions

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