mmosko
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Bert_Fake_News_Classification

Text Classification

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Bert_Fake_News_Classification

This model is a fine-tuned version of bert-base-cased on ErfanMoosaviMonazzah/fake-news-detection-dataset-English dataset.

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: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.03
num_epochs: 3.0

Training results

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.0
Tokenizers 0.21.0

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Safetensors

Model size

0.1B params

Tensor type

F32

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Dataset used to train mmosko/Bert_Fake_News_Classification