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--- |
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library_name: transformers |
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license: mit |
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base_model: ai4bharat/indic-bert |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: indic-bert-hate-mr |
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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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# indic-bert-hate-mr |
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This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2408 |
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- Accuracy: 0.9226 |
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- Precision: 0.9270 |
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- Recall: 0.9225 |
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- F1: 0.9224 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.6637 | 1.0 | 61 | 0.6441 | 0.6530 | 0.6780 | 0.6526 | 0.6400 | |
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| 0.678 | 2.0 | 122 | 0.6538 | 0.6386 | 0.6408 | 0.6387 | 0.6372 | |
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| 0.6422 | 3.0 | 183 | 0.6597 | 0.6410 | 0.6607 | 0.6405 | 0.6292 | |
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| 0.6281 | 4.0 | 244 | 0.6202 | 0.6578 | 0.6591 | 0.6579 | 0.6573 | |
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| 0.5374 | 5.0 | 305 | 0.6306 | 0.6723 | 0.6746 | 0.6721 | 0.6711 | |
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| 0.4418 | 6.0 | 366 | 0.7122 | 0.6795 | 0.6991 | 0.6799 | 0.6717 | |
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| 0.3981 | 7.0 | 427 | 0.7183 | 0.6602 | 0.6603 | 0.6602 | 0.6602 | |
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| 0.3054 | 8.0 | 488 | 0.8008 | 0.6867 | 0.6889 | 0.6869 | 0.6859 | |
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| 0.2445 | 9.0 | 549 | 0.9741 | 0.6578 | 0.6587 | 0.6577 | 0.6573 | |
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| 0.1882 | 10.0 | 610 | 0.9924 | 0.6723 | 0.6723 | 0.6723 | 0.6723 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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