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---
license: cc-by-4.0
base_model: l3cube-pune/malayalam-bert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: malayalam-bert-FakeNews-Dravidian-finalwithPP
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# malayalam-bert-FakeNews-Dravidian-finalwithPP
This model is a fine-tuned version of [l3cube-pune/malayalam-bert](https://huggingface.co/l3cube-pune/malayalam-bert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0597
- Accuracy: 0.9890
- Weighted f1 score: 0.9890
- Macro f1 score: 0.9890
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 score | Macro f1 score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------:|
| 0.879 | 1.0 | 255 | 0.6737 | 0.8417 | 0.8403 | 0.8403 |
| 0.5845 | 2.0 | 510 | 0.4242 | 0.9178 | 0.9178 | 0.9178 |
| 0.3641 | 3.0 | 765 | 0.2130 | 0.9656 | 0.9656 | 0.9656 |
| 0.2351 | 4.0 | 1020 | 0.1512 | 0.9681 | 0.9681 | 0.9681 |
| 0.1702 | 5.0 | 1275 | 0.0936 | 0.9816 | 0.9816 | 0.9816 |
| 0.109 | 6.0 | 1530 | 0.0734 | 0.9853 | 0.9853 | 0.9853 |
| 0.0904 | 7.0 | 1785 | 0.0670 | 0.9877 | 0.9877 | 0.9877 |
| 0.0692 | 8.0 | 2040 | 0.0600 | 0.9877 | 0.9877 | 0.9877 |
| 0.0468 | 9.0 | 2295 | 0.0612 | 0.9890 | 0.9890 | 0.9890 |
| 0.0471 | 10.0 | 2550 | 0.0597 | 0.9890 | 0.9890 | 0.9890 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.14.1
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