---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: distilbert-base-casedfinetuned-fake-news-detection
  results: []
---

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# distilbert-base-casedfinetuned-fake-news-detection

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the [Fake and Reals News](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0019
- F1: 0.9998
- Accuracy: 0.9998

The [Fake and Reals News](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset) dataset was used. It was stratified split into a train-val-test set (60/20/20).

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| No log        | 1.0   | 1684 | 0.0021          | 0.9998 | 0.9998   |
| No log        | 2.0   | 3368 | 0.0019          | 0.9998 | 0.9998   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6