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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-abusive-comments-ta |
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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-abusive-comments-ta |
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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: 1.1108 |
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- Accuracy: 0.6896 |
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- Precision: 0.2983 |
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- Recall: 0.2872 |
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- F1: 0.2740 |
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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: 32 |
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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: 64 |
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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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| 1.1508 | 1.0 | 93 | 1.2143 | 0.6216 | 0.1373 | 0.1440 | 0.1253 | |
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| 1.1999 | 2.0 | 186 | 1.1389 | 0.6337 | 0.1632 | 0.1656 | 0.1545 | |
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| 1.0445 | 3.0 | 279 | 1.0623 | 0.6815 | 0.2057 | 0.2219 | 0.2109 | |
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| 0.882 | 4.0 | 372 | 1.0181 | 0.6996 | 0.3264 | 0.3092 | 0.2976 | |
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| 0.7892 | 5.0 | 465 | 1.0408 | 0.7036 | 0.3327 | 0.3097 | 0.3011 | |
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| 0.7381 | 6.0 | 558 | 1.1007 | 0.7103 | 0.3317 | 0.3060 | 0.3057 | |
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| 0.6175 | 7.0 | 651 | 1.2323 | 0.7070 | 0.3241 | 0.3014 | 0.3037 | |
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| 0.49 | 8.0 | 744 | 1.2686 | 0.6956 | 0.4590 | 0.3093 | 0.3164 | |
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| 0.4576 | 9.0 | 837 | 1.3347 | 0.6761 | 0.3285 | 0.3200 | 0.3199 | |
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| 0.3436 | 10.0 | 930 | 1.3501 | 0.6673 | 0.3363 | 0.3167 | 0.3204 | |
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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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