metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - pritamdeka/cord-19-abstract
metrics:
  - accuracy
model-index:
  - name: pubmedbert-abstract-cord19
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: pritamdeka/cord-19-abstract
          type: pritamdeka/cord-19-abstract
          args: fulltext
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7246798699728464

PubMedBert-abstract-cord19-v2

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the pritamdeka/cord-19-abstract dataset. It achieves the following results on the evaluation set:

Loss: 1.2371
Accuracy: 0.7247

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=(0.9,0.95) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10000
num_epochs: 4.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.27	0.53	5000	1.2425	0.7236
1.2634	1.06	10000	1.3123	0.7141
1.3041	1.59	15000	1.3583	0.7072
1.3829	2.12	20000	1.3590	0.7121
1.3069	2.65	25000	1.3506	0.7154
1.2921	3.18	30000	1.3448	0.7160
1.2731	3.7	35000	1.3375	0.7178

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.11.0