BioBERT-LitCovid-v1.3.1

sofia-todeschini/BioBERT-LitCovid-v1.3.1

BioBERT-LitCovid-v1.3.1 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.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Nov 2, 2023
Updated: Nov 2, 2023
SHA: 7bd7a5a6

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Model card

From the Hugging Face model README

BioBERT-LitCovid-v1.3.1

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6731
Hamming loss: 0.0186
F1 micro: 0.8434
F1 macro: 0.3657
F1 weighted: 0.8790
F1 samples: 0.8763
Precision micro: 0.7702
Precision macro: 0.2942
Precision weighted: 0.8399
Precision samples: 0.8618
Recall micro: 0.9320
Recall macro: 0.7288
Recall weighted: 0.9320
Recall samples: 0.9432
Roc Auc: 0.9581
Accuracy: 0.6841

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: 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
1.1065	1.0	2272	0.4899	0.0357	0.7347	0.2684	0.8280	0.8274	0.6112	0.2128	0.7700	0.7976	0.9207	0.7424	0.9207	0.9370	0.9437	0.5688
0.8552	2.0	4544	0.4641	0.0246	0.8018	0.3270	0.8588	0.8548	0.7057	0.2595	0.8123	0.8327	0.9282	0.7833	0.9282	0.9424	0.9531	0.6325
0.7061	3.0	6816	0.5058	0.0227	0.8166	0.3320	0.8679	0.8652	0.7201	0.2640	0.8146	0.8402	0.9429	0.7601	0.9429	0.9522	0.9611	0.6548
0.5914	4.0	9088	0.6116	0.0196	0.8368	0.3588	0.8758	0.8719	0.7572	0.2869	0.8321	0.8533	0.9353	0.7398	0.9353	0.9456	0.9591	0.6706
0.294	5.0	11360	0.6731	0.0186	0.8434	0.3657	0.8790	0.8763	0.7702	0.2942	0.8399	0.8618	0.9320	0.7288	0.9320	0.9432	0.9581	0.6841

Framework versions

Transformers 4.28.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
Created: Nov 2, 2023
Updated: Nov 2, 2023