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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-profanity-mr
    results: []

indic-bert-profanity-mr

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: 0.3187
  • Accuracy: 0.9035
  • Precision: 0.4517
  • Recall: 0.5
  • F1: 0.4746

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: 2
  • total_train_batch_size: 64
  • 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
0.3272 0.9836 30 0.3721 0.8819 0.4410 0.5 0.4686
0.3332 2.0 61 0.3677 0.8819 0.4410 0.5 0.4686
0.3293 2.9836 91 0.3768 0.8819 0.4410 0.5 0.4686
0.3275 4.0 122 0.3612 0.8819 0.4410 0.5 0.4686
0.2919 4.9836 152 0.3752 0.8819 0.4410 0.5 0.4686
0.291 6.0 183 0.3618 0.8819 0.4410 0.5 0.4686
0.281 6.9836 213 0.3793 0.8819 0.4410 0.5 0.4686
0.2399 8.0 244 0.3854 0.8819 0.4410 0.5 0.4686
0.1822 8.9836 274 0.4216 0.8819 0.4410 0.5 0.4686
0.1354 9.8361 300 0.4200 0.8819 0.6938 0.5265 0.5229

Framework versions

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