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xlm-r-hatespeechdetection-telugu
ramesh070/xlm-r-hatespeechdetection-telugu
xlm-r-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
- xlm-roberta
- Access
- Public
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025
- SHA
- b7a46352
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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. -->
xlm-r-hatespeechdetection-telugu
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1518
- Accuracy: 0.9643
- F1: 0.9722
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 |
|---|---|---|---|---|---|
| 0.6729 | 1.0 | 14 | 0.6153 | 0.6429 | 0.7826 |
| 0.6196 | 2.0 | 28 | 0.5032 | 0.6429 | 0.7826 |
| 0.5297 | 3.0 | 42 | 0.4319 | 0.6429 | 0.7826 |
| 0.4444 | 4.0 | 56 | 0.3296 | 0.9643 | 0.9730 |
| 0.3435 | 5.0 | 70 | 0.1656 | 1.0 | 1.0 |
| 0.2417 | 6.0 | 84 | 0.1390 | 0.9286 | 0.9474 |
| 0.1392 | 7.0 | 98 | 0.0760 | 0.9643 | 0.9722 |
| 0.0815 | 8.0 | 112 | 0.1240 | 0.9643 | 0.9730 |
| 0.1242 | 9.0 | 126 | 0.0870 | 0.9643 | 0.9722 |
| 0.0776 | 10.0 | 140 | 0.2582 | 0.9107 | 0.9333 |
| 0.0444 | 11.0 | 154 | 0.3596 | 0.9107 | 0.9333 |
| 0.0449 | 12.0 | 168 | 0.3502 | 0.9286 | 0.9459 |
| 0.0534 | 13.0 | 182 | 0.1307 | 0.9821 | 0.9859 |
| 0.0205 | 14.0 | 196 | 0.2319 | 0.9464 | 0.9589 |
| 0.0067 | 15.0 | 210 | 0.4442 | 0.9286 | 0.9459 |
| 0.0045 | 16.0 | 224 | 0.2420 | 0.9464 | 0.9589 |
| 0.0132 | 17.0 | 238 | 0.4973 | 0.9286 | 0.9459 |
| 0.0025 | 18.0 | 252 | 0.2707 | 0.9464 | 0.9589 |
| 0.0015 | 19.0 | 266 | 0.1389 | 0.9821 | 0.9859 |
| 0.0029 | 20.0 | 280 | 0.1518 | 0.9643 | 0.9722 |
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
- xlm-roberta
- License
- mit
- Created
- Dec 11, 2025
- Updated
- Dec 11, 2025