---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: BERTUncased_Fake_news_classification
  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. -->

# BERTUncased_Fake_news_classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0027
- Accuracy: 0.9997
- F1: 0.9998
- Percision: 0.9995

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Percision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.0081        | 1.0   | 3865 | 0.0000          | 1.0      | 1.0    | 1.0       |
| 0.0015        | 2.0   | 7730 | 0.0027          | 0.9997   | 0.9998 | 0.9995    |


### Framework versions

- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2