albert-base-v2-fakenews-discriminator

The dataset: Fake and real news dataset https://www.kaggle.com/clmentbisaillon/fake-and-real-news-dataset

I use title and label to train the classifier

label_0 : Fake news label_1 : Real news

This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0910
• Accuracy: 0.9758

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: 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: 500
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0452	1.0	1768	0.0910	0.9758

Framework versions

• Transformers 4.12.3
• Pytorch 1.10.0+cu111
• Datasets 1.15.1
• Tokenizers 0.10.3