---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Fake-News-Detector
  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. -->

# Fake-News-Detector

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0

## 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0           | 0.09  | 100  | 0.0000          | 1.0      |
| 0.0           | 0.19  | 200  | 0.0000          | 1.0      |
| 0.0           | 0.28  | 300  | 0.0000          | 1.0      |
| 0.0           | 0.37  | 400  | 0.0000          | 1.0      |
| 0.0           | 0.47  | 500  | 0.0000          | 1.0      |
| 0.0           | 0.56  | 600  | 0.0000          | 1.0      |
| 0.0           | 0.65  | 700  | 0.0000          | 1.0      |
| 0.0           | 0.75  | 800  | 0.0000          | 1.0      |
| 0.0           | 0.84  | 900  | 0.0000          | 1.0      |
| 0.0           | 0.93  | 1000 | 0.0000          | 1.0      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1