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End of training

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README.md ADDED
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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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+
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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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+
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+ # malayalam-bert-FakeNews-Dravidian-finalwithPP
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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