covid-augment-tweet-bert-large-e2-v2

This model is a fine-tuned version of digitalepidemiologylab/covid-twitter-bert on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2513
• Accuracy: 0.9639
• F1: 0.9051
• Precision: 0.8870
• Recall: 0.9239

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	F1	Precision	Recall
0.0495	1.0	1023	0.2682	0.9600	0.8920	0.8982	0.8858
0.0135	2.0	2046	0.2513	0.9639	0.9051	0.8870	0.9239

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3