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xlm-r-hatespeechdetection-malayalam
ramesh070/xlm-r-hatespeechdetection-malayalam
xlm-r-hatespeechdetection-malayalam 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 3, 2025
- Updated
- Dec 3, 2025
- SHA
- ea69dd91
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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-malayalam
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: 0.2069
- Accuracy: 0.9773
- F1: 0.9787
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 |
|---|---|---|---|---|---|
| 0.6001 | 1.0 | 23 | 0.4993 | 0.7955 | 0.7692 |
| 0.3838 | 2.0 | 46 | 0.1142 | 0.9659 | 0.9684 |
| 0.2828 | 3.0 | 69 | 0.1073 | 0.9659 | 0.9684 |
| 0.1486 | 4.0 | 92 | 0.1223 | 0.9545 | 0.9565 |
| 0.107 | 5.0 | 115 | 0.1330 | 0.9545 | 0.9574 |
| 0.1015 | 6.0 | 138 | 0.1761 | 0.9659 | 0.9684 |
| 0.0476 | 7.0 | 161 | 0.1340 | 0.9659 | 0.9677 |
| 0.0405 | 8.0 | 184 | 0.2003 | 0.9545 | 0.9565 |
| 0.0276 | 9.0 | 207 | 0.1555 | 0.9773 | 0.9787 |
| 0.0206 | 10.0 | 230 | 0.2129 | 0.9659 | 0.9677 |
| 0.0013 | 11.0 | 253 | 0.1939 | 0.9659 | 0.9684 |
| 0.0037 | 12.0 | 276 | 0.1888 | 0.9773 | 0.9787 |
| 0.0003 | 13.0 | 299 | 0.1851 | 0.9773 | 0.9787 |
| 0.0181 | 14.0 | 322 | 0.2838 | 0.9659 | 0.9684 |
| 0.0011 | 15.0 | 345 | 0.1936 | 0.9773 | 0.9787 |
| 0.0004 | 16.0 | 368 | 0.2084 | 0.9773 | 0.9787 |
| 0.0004 | 17.0 | 391 | 0.2081 | 0.9773 | 0.9787 |
| 0.0002 | 18.0 | 414 | 0.2062 | 0.9773 | 0.9787 |
| 0.0002 | 19.0 | 437 | 0.2072 | 0.9773 | 0.9787 |
| 0.0002 | 20.0 | 460 | 0.2069 | 0.9773 | 0.9787 |
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 3, 2025
- Updated
- Dec 3, 2025