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--- |
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license: cc-by-4.0 |
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base_model: l3cube-pune/malayalam-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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model-index: |
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- name: malayalam-bert-FakeNews-Dravidian-finalwithPP |
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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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# malayalam-bert-FakeNews-Dravidian-finalwithPP |
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This model is a fine-tuned version of [l3cube-pune/malayalam-bert](https://huggingface.co/l3cube-pune/malayalam-bert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0597 |
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- Accuracy: 0.9890 |
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- Weighted f1 score: 0.9890 |
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- Macro f1 score: 0.9890 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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 | Weighted f1 score | Macro f1 score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------:| |
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| 0.879 | 1.0 | 255 | 0.6737 | 0.8417 | 0.8403 | 0.8403 | |
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| 0.5845 | 2.0 | 510 | 0.4242 | 0.9178 | 0.9178 | 0.9178 | |
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| 0.3641 | 3.0 | 765 | 0.2130 | 0.9656 | 0.9656 | 0.9656 | |
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| 0.2351 | 4.0 | 1020 | 0.1512 | 0.9681 | 0.9681 | 0.9681 | |
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| 0.1702 | 5.0 | 1275 | 0.0936 | 0.9816 | 0.9816 | 0.9816 | |
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| 0.109 | 6.0 | 1530 | 0.0734 | 0.9853 | 0.9853 | 0.9853 | |
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| 0.0904 | 7.0 | 1785 | 0.0670 | 0.9877 | 0.9877 | 0.9877 | |
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| 0.0692 | 8.0 | 2040 | 0.0600 | 0.9877 | 0.9877 | 0.9877 | |
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| 0.0468 | 9.0 | 2295 | 0.0612 | 0.9890 | 0.9890 | 0.9890 | |
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| 0.0471 | 10.0 | 2550 | 0.0597 | 0.9890 | 0.9890 | 0.9890 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.11.0 |
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- Tokenizers 0.14.1 |
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