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metadata
library_name: transformers
license: mit
base_model: ai4bharat/indic-bert
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: indic-bert-roman-urdu-binary
    results: []

indic-bert-roman-urdu-binary

This model is a fine-tuned version of ai4bharat/indic-bert on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5183
  • Accuracy: 0.8847
  • Precision: 0.8851
  • Recall: 0.8831
  • F1: 0.8839

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: 32
  • eval_batch_size: 128
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.6103 0.9912 56 0.5319 0.7366 0.7534 0.7445 0.7355
0.3576 2.0 113 0.3626 0.8427 0.8418 0.8428 0.8422
0.2913 2.9912 169 0.3478 0.8589 0.8582 0.8585 0.8583
0.2351 4.0 226 0.3812 0.8564 0.8755 0.8486 0.8520
0.1342 4.9912 282 0.4025 0.8652 0.8678 0.8619 0.8636
0.0733 6.0 339 0.4448 0.8639 0.8638 0.8625 0.8630
0.0325 6.9912 395 0.5974 0.8589 0.8657 0.8540 0.8565
0.0308 8.0 452 0.6238 0.8589 0.8588 0.8575 0.8580
0.01 8.9912 508 0.6391 0.8664 0.8693 0.8631 0.8649
0.0091 9.9115 560 0.6417 0.8552 0.8548 0.8540 0.8543

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0