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--- |
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library_name: transformers |
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license: mit |
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base_model: ai4bharat/IndicBERTv2-MLM-Sam-TLM |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: sutra-classifier-adv |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# sutra-classifier-adv |
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This model is a fine-tuned version of [ai4bharat/IndicBERTv2-MLM-Sam-TLM](https://huggingface.co/ai4bharat/IndicBERTv2-MLM-Sam-TLM) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.9104 |
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- Accuracy: 0.9020 |
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- F1: 0.9020 |
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- Adv Acc: 0.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 8.8e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.079905 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Adv Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:| |
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| 0.8968 | 1.0 | 72 | 1.9034 | 0.8078 | 0.8048 | 0.0902 | |
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| 2.4258 | 2.0 | 144 | 5.0244 | 0.8510 | 0.8503 | 0.1333 | |
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| 6.9155 | 3.0 | 216 | 8.0457 | 0.8549 | 0.8542 | 0.0 | |
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| 7.4505 | 4.0 | 288 | 12.3074 | 0.8706 | 0.8706 | 0.0 | |
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| 10.0671 | 5.0 | 360 | 9.0296 | 0.8353 | 0.8334 | 0.0 | |
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| 8.9089 | 6.0 | 432 | 10.0976 | 0.8275 | 0.8274 | 0.0353 | |
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| 6.8576 | 7.0 | 504 | 6.8378 | 0.8824 | 0.8824 | 0.0118 | |
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| 5.9407 | 8.0 | 576 | 5.4805 | 0.8588 | 0.8583 | 0.0314 | |
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| 5.1865 | 9.0 | 648 | 4.0087 | 0.8745 | 0.8745 | 0.1412 | |
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| 3.5606 | 10.0 | 720 | 4.4264 | 0.8549 | 0.8546 | 0.0078 | |
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| 3.4944 | 11.0 | 792 | 3.9312 | 0.9098 | 0.9098 | 0.0 | |
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| 3.4093 | 12.0 | 864 | 4.0868 | 0.8902 | 0.8902 | 0.0 | |
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| 3.3966 | 13.0 | 936 | 3.9650 | 0.8980 | 0.8979 | 0.0 | |
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| 3.3191 | 14.0 | 1008 | 4.0058 | 0.8824 | 0.8821 | 0.0 | |
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| 3.3156 | 15.0 | 1080 | 4.0279 | 0.8784 | 0.8784 | 0.0 | |
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| 3.26 | 16.0 | 1152 | 4.0243 | 0.8902 | 0.8902 | 0.0 | |
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| 3.264 | 17.0 | 1224 | 3.9404 | 0.8941 | 0.8941 | 0.0 | |
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| 3.2533 | 18.0 | 1296 | 3.8867 | 0.8941 | 0.8941 | 0.0 | |
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| 3.2137 | 19.0 | 1368 | 3.8939 | 0.9020 | 0.9020 | 0.0 | |
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| 3.2148 | 20.0 | 1440 | 3.9104 | 0.9020 | 0.9020 | 0.0 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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