distillBERT-misinformation-classifier

This model is a fine-tuned version of distilbert-base-uncased on the Kaggle Fake News dataset. It achieves the following results on the evaluation set:

• Loss: 0.0094
• Accuracy: 0.9978

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1411	1.0	800	0.0104	0.9974
0.0101	2.0	1600	0.0094	0.9978

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.13.3