CORD19-BERT

How to use

from transformers import BertTokenizer, BertModel
tokenizer = BertTokenizer.from_pretrained('CovRelex-SE/CORD19-BERT')
model = BertModel.from_pretrained("CovRelex-SE/CORD19-BERT")
text = "The virus can spread from an infected person’s mouth or nose."
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 32
• 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

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1