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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Fake-News-Detector
results: []
widget:
- text: >-
In a shocking turn of events, reports have surfaced suggesting that a
clandestine meeting of world leaders took place on Mars to discuss plans for
the colonization of the Red Planet. According to anonymous sources within
the highest echelons of government, the summit was organized by a coalition
of space agencies and private corporations aiming to expedite humanity's
expansion beyond Earth. The meeting purportedly took place in a hidden
underground facility on Mars, accessible only to a select few individuals
privy to the ambitious project.
example_title: Mars Meeting
- text: >-
In a groundbreaking revelation that has sent shockwaves through the
scientific community, Dr. Rachel Bennett, a renowned researcher at the
prestigious Cambridge Institute of Biotechnology, claims to have unlocked
the elusive secret to eternal youth. According to Dr. Bennett, years of
tireless research have culminated in the discovery of a revolutionary
anti-aging compound derived from a rare Amazonian plant known only to
indigenous tribes. Initial trials on laboratory mice have yielded
astonishing results, with subjects exhibiting signs of reversed aging and
enhanced vitality.
example_title: Dr. Bennett
- text: Apples are orange
example_title: Oranges are Apples
- text: Donald Trump is the 45th president of the United States.
example_title: True News
datasets:
- AlexanderHolmes0/true-fake-news
language:
- en
pipeline_tag: text-classification
---
<!-- 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 [true-fake-news](https://huggingface.co/datasets/AlexanderHolmes0/true-fake-news) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0096
- Accuracy: 0.9976
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1809 | 0.09 | 100 | 0.0608 | 0.9840 |
| 0.0433 | 0.18 | 200 | 0.0222 | 0.9933 |
| 0.0248 | 0.27 | 300 | 0.0631 | 0.9834 |
| 0.0246 | 0.36 | 400 | 0.0363 | 0.9903 |
| 0.0223 | 0.45 | 500 | 0.0378 | 0.9906 |
| 0.0172 | 0.53 | 600 | 0.0129 | 0.9969 |
| 0.0133 | 0.62 | 700 | 0.0208 | 0.9947 |
| 0.0188 | 0.71 | 800 | 0.0118 | 0.9971 |
| 0.0134 | 0.8 | 900 | 0.0109 | 0.9971 |
| 0.0055 | 0.89 | 1000 | 0.0096 | 0.9976 |
| 0.0055 | 0.98 | 1100 | 0.0096 | 0.9976 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1 |