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roberta-base-fake-news-detection – AI Model by mohammadjavadpirhadi | AlphaNeural AI
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mohammadjavadpirhadi
/
roberta-base-fake-news-detection
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transformers
pytorch
roberta
text-classification
generated_from_trainer
en
mohammadjavadpirhadi/fake-news-detection-dataset-english
mit
autotrain_compatible
endpoints_compatible
us
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roberta-base-fake-news-detection
This model is a fine-tuned version of
roberta-base
on the
fake-news-detection-dataset-english
dataset. It achieves the following results on the evaluation set:
Loss: 0.0061
Accuracy: 0.9992
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0073
1.0
4490
0.0087
0.9989
0.0076
2.0
8980
0.0062
0.9992
0.0094
3.0
13470
0.0061
0.9992
Framework versions
Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
