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indicbert-hatespeechdetection-telugu
ramesh070/indicbert-hatespeechdetection-telugu
indicbert-hatespeechdetection-telugu is a text classification model from ramesh070. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025
- SHA
- ae492278
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
indicbert-hatespeechdetection-telugu
This model is a fine-tuned version of ai4bharat/IndicBERTv2-MLM-only on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2457
- Accuracy: 0.9464
- F1: 0.9600
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6426 | 1.0 | 14 | 0.5502 | 0.6429 | 0.7826 |
| 0.5289 | 2.0 | 28 | 0.4144 | 0.8393 | 0.8889 |
| 0.4047 | 3.0 | 42 | 0.2915 | 0.875 | 0.9067 |
| 0.2643 | 4.0 | 56 | 0.2390 | 0.8929 | 0.9211 |
| 0.1543 | 5.0 | 70 | 0.1751 | 0.9286 | 0.9444 |
| 0.1073 | 6.0 | 84 | 0.1605 | 0.9464 | 0.9589 |
| 0.0604 | 7.0 | 98 | 0.2654 | 0.8929 | 0.9211 |
| 0.0335 | 8.0 | 112 | 0.1993 | 0.9464 | 0.9589 |
| 0.0199 | 9.0 | 126 | 0.2162 | 0.9464 | 0.9589 |
| 0.0171 | 10.0 | 140 | 0.3126 | 0.9286 | 0.9474 |
| 0.0121 | 11.0 | 154 | 0.2454 | 0.9286 | 0.9459 |
| 0.0106 | 12.0 | 168 | 0.2090 | 0.9464 | 0.9600 |
| 0.0115 | 13.0 | 182 | 0.1994 | 0.9464 | 0.9600 |
| 0.0084 | 14.0 | 196 | 0.2142 | 0.9464 | 0.9600 |
| 0.0065 | 15.0 | 210 | 0.2245 | 0.9464 | 0.9600 |
| 0.0066 | 16.0 | 224 | 0.2728 | 0.9286 | 0.9474 |
| 0.0027 | 17.0 | 238 | 0.2297 | 0.9464 | 0.9600 |
| 0.002 | 18.0 | 252 | 0.2121 | 0.9464 | 0.9600 |
| 0.0053 | 19.0 | 266 | 0.2454 | 0.9464 | 0.9600 |
| 0.0017 | 20.0 | 280 | 0.2457 | 0.9464 | 0.9600 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025