---
tags:
- generated_from_trainer
model-index:
- name: Fake_News_Classifier
  results: []
metrics:
- f1
- accuracy
- roc_auc
pipeline_tag: text-classification
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# NELA-GT_Classifier

This model was Fine-Tuned on a Fake News dataset.

## Model description

This is a pretrained distilbert-uncased model finetuned for Fake News classification.

## 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: 5e-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
- lr_scheduler_warmup_steps: 1500
- num_epochs: 5

### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3