---
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
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# 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