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--- |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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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: bert-base-multilingual-cased-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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# bert-base-multilingual-cased-FakeNews-Dravidian-finalwithPP |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0037 |
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- Accuracy: 0.9988 |
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- Weighted f1 score: 0.9988 |
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- Macro f1 score: 0.9988 |
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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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| 0.5233 | 1.0 | 255 | 0.2997 | 0.8675 | 0.8658 | 0.8657 | |
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| 0.3129 | 2.0 | 510 | 0.1543 | 0.9595 | 0.9595 | 0.9595 | |
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| 0.2039 | 3.0 | 765 | 0.0733 | 0.9840 | 0.9840 | 0.9840 | |
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| 0.1254 | 4.0 | 1020 | 0.0608 | 0.9853 | 0.9853 | 0.9853 | |
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| 0.0885 | 5.0 | 1275 | 0.0419 | 0.9902 | 0.9902 | 0.9902 | |
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| 0.0607 | 6.0 | 1530 | 0.0267 | 0.9914 | 0.9914 | 0.9914 | |
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| 0.031 | 7.0 | 1785 | 0.0098 | 0.9975 | 0.9975 | 0.9975 | |
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| 0.0245 | 8.0 | 2040 | 0.0061 | 0.9975 | 0.9975 | 0.9975 | |
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| 0.0176 | 9.0 | 2295 | 0.0044 | 0.9988 | 0.9988 | 0.9988 | |
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| 0.012 | 10.0 | 2550 | 0.0037 | 0.9988 | 0.9988 | 0.9988 | |
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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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