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sutra-classifier-adv
bhaswata08/sutra-classifier-adv
sutra-classifier-adv is a machine learning model from bhaswata08. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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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Public
Updated Aug 2, 2025
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Aug 2, 2025
- Updated
- Aug 2, 2025
- SHA
- e0f87eda
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. -->
sutra-classifier-adv
This model is a fine-tuned version of ai4bharat/IndicBERTv2-MLM-Sam-TLM on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.9104
- Accuracy: 0.9020
- F1: 0.9020
- Adv Acc: 0.0
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: 8.8e-05
- train_batch_size: 32
- eval_batch_size: 64
- 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
- lr_scheduler_warmup_ratio: 0.079905
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Adv Acc |
|---|---|---|---|---|---|---|
| 0.8968 | 1.0 | 72 | 1.9034 | 0.8078 | 0.8048 | 0.0902 |
| 2.4258 | 2.0 | 144 | 5.0244 | 0.8510 | 0.8503 | 0.1333 |
| 6.9155 | 3.0 | 216 | 8.0457 | 0.8549 | 0.8542 | 0.0 |
| 7.4505 | 4.0 | 288 | 12.3074 | 0.8706 | 0.8706 | 0.0 |
| 10.0671 | 5.0 | 360 | 9.0296 | 0.8353 | 0.8334 | 0.0 |
| 8.9089 | 6.0 | 432 | 10.0976 | 0.8275 | 0.8274 | 0.0353 |
| 6.8576 | 7.0 | 504 | 6.8378 | 0.8824 | 0.8824 | 0.0118 |
| 5.9407 | 8.0 | 576 | 5.4805 | 0.8588 | 0.8583 | 0.0314 |
| 5.1865 | 9.0 | 648 | 4.0087 | 0.8745 | 0.8745 | 0.1412 |
| 3.5606 | 10.0 | 720 | 4.4264 | 0.8549 | 0.8546 | 0.0078 |
| 3.4944 | 11.0 | 792 | 3.9312 | 0.9098 | 0.9098 | 0.0 |
| 3.4093 | 12.0 | 864 | 4.0868 | 0.8902 | 0.8902 | 0.0 |
| 3.3966 | 13.0 | 936 | 3.9650 | 0.8980 | 0.8979 | 0.0 |
| 3.3191 | 14.0 | 1008 | 4.0058 | 0.8824 | 0.8821 | 0.0 |
| 3.3156 | 15.0 | 1080 | 4.0279 | 0.8784 | 0.8784 | 0.0 |
| 3.26 | 16.0 | 1152 | 4.0243 | 0.8902 | 0.8902 | 0.0 |
| 3.264 | 17.0 | 1224 | 3.9404 | 0.8941 | 0.8941 | 0.0 |
| 3.2533 | 18.0 | 1296 | 3.8867 | 0.8941 | 0.8941 | 0.0 |
| 3.2137 | 19.0 | 1368 | 3.8939 | 0.9020 | 0.9020 | 0.0 |
| 3.2148 | 20.0 | 1440 | 3.9104 | 0.9020 | 0.9020 | 0.0 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
- Library
- transformers
- License
- mit
- Created
- Aug 2, 2025
- Updated
- Aug 2, 2025