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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 |
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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 |
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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: 0.7928 |
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- Accuracy: 0.7840 |
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- Weighted f1 score: 0.7819 |
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- Macro f1 score: 0.7818 |
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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-06 |
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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: 15 |
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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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| 1.0681 | 1.0 | 204 | 1.0238 | 0.4982 | 0.3313 | 0.3325 | |
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| 1.0077 | 2.0 | 408 | 0.9829 | 0.5031 | 0.3421 | 0.3433 | |
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| 0.9738 | 3.0 | 612 | 0.9529 | 0.5877 | 0.5499 | 0.5503 | |
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| 0.946 | 4.0 | 816 | 0.9267 | 0.6466 | 0.6401 | 0.6399 | |
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| 0.9204 | 5.0 | 1020 | 0.9019 | 0.7006 | 0.6877 | 0.6875 | |
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| 0.8961 | 6.0 | 1224 | 0.8754 | 0.7644 | 0.7629 | 0.7628 | |
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| 0.8715 | 7.0 | 1428 | 0.8540 | 0.7607 | 0.7544 | 0.7543 | |
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| 0.8485 | 8.0 | 1632 | 0.8362 | 0.7828 | 0.7789 | 0.7788 | |
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| 0.8323 | 9.0 | 1836 | 0.8244 | 0.7791 | 0.7749 | 0.7748 | |
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| 0.8182 | 10.0 | 2040 | 0.8151 | 0.7816 | 0.7773 | 0.7772 | |
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| 0.8063 | 11.0 | 2244 | 0.8069 | 0.7816 | 0.7792 | 0.7791 | |
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| 0.7973 | 12.0 | 2448 | 0.8011 | 0.7828 | 0.7799 | 0.7798 | |
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| 0.791 | 13.0 | 2652 | 0.7950 | 0.7853 | 0.7840 | 0.7839 | |
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| 0.7857 | 14.0 | 2856 | 0.7939 | 0.7816 | 0.7793 | 0.7792 | |
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| 0.7826 | 15.0 | 3060 | 0.7928 | 0.7840 | 0.7819 | 0.7818 | |
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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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