PubMedBERT-LitCovid-v1.3h

sofia-todeschini/PubMedBERT-LitCovid-v1.3h

PubMedBERT-LitCovid-v1.3h is a text classification model from sofia-todeschini. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Feb 12, 2024
Updated: Feb 12, 2024
SHA: d722e3da

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Model card

From the Hugging Face model README

PubMedBERT-LitCovid-v1.3h

This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8774
Hamming loss: 0.0137
F1 micro: 0.8798
F1 macro: 0.4661
F1 weighted: 0.8928
F1 samples: 0.8920
Precision micro: 0.8303
Precision macro: 0.3861
Precision weighted: 0.8575
Precision samples: 0.8800
Recall micro: 0.9356
Recall macro: 0.7033
Recall weighted: 0.9356
Recall samples: 0.9451
Roc Auc: 0.9624
Accuracy: 0.7154

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_ratio: 0.157
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Hamming loss	F1 micro	F1 macro	F1 weighted	F1 samples	Precision micro	Precision macro	Precision weighted	Precision samples	Recall micro	Recall macro	Recall weighted	Recall samples	Roc Auc	Accuracy
1.2354	1.0	2272	0.4702	0.0473	0.6733	0.2437	0.8136	0.7898	0.5349	0.1961	0.7600	0.7551	0.9084	0.7924	0.9084	0.9263	0.9318	0.5030
0.9475	2.0	4544	0.5277	0.0214	0.8208	0.3449	0.8664	0.8541	0.7441	0.2778	0.8345	0.8362	0.9151	0.7371	0.9151	0.9304	0.9487	0.6209
0.7806	3.0	6816	0.5645	0.0187	0.8432	0.3871	0.8765	0.8632	0.7670	0.3096	0.8337	0.8350	0.9362	0.7431	0.9362	0.9472	0.9601	0.6337
0.5358	4.0	9088	0.7518	0.0145	0.8738	0.4462	0.8893	0.8873	0.8211	0.3653	0.8537	0.8742	0.9337	0.6984	0.9337	0.9443	0.9611	0.7024
0.1808	5.0	11360	0.8774	0.0137	0.8798	0.4661	0.8928	0.8920	0.8303	0.3861	0.8575	0.8800	0.9356	0.7033	0.9356	0.9451	0.9624	0.7154

Framework versions

Transformers 4.28.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
License: mit
Created: Feb 12, 2024
Updated: Feb 12, 2024