Bioformer-LitCovid-v1.3h

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

Bioformer-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 apache-2.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Feb 10, 2024
Updated: Feb 11, 2024
SHA: 922635f3

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Model card

From the Hugging Face model README

Bioformer-LitCovid-v1.3h

This model is a fine-tuned version of bioformers/bioformer-litcovid on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8951
Hamming loss: 0.0168
F1 micro: 0.8565
F1 macro: 0.3960
F1 weighted: 0.8831
F1 samples: 0.8789
Precision micro: 0.7903
Precision macro: 0.3221
Precision weighted: 0.8426
Precision samples: 0.8631
Recall micro: 0.9348
Recall macro: 0.6915
Recall weighted: 0.9348
Recall samples: 0.9435
Roc Auc: 0.9604
Accuracy: 0.6896

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: 0.0001
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 3257
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
1.2033	1.0	2272	0.5628	0.0616	0.6107	0.2167	0.7918	0.7257	0.4618	0.1789	0.7347	0.6771	0.9014	0.7310	0.9014	0.9194	0.9209	0.3870
1.2127	2.0	4544	0.5062	0.0325	0.7555	0.2834	0.8357	0.8037	0.6337	0.2273	0.7680	0.7535	0.9353	0.7100	0.9353	0.9434	0.9523	0.4954
0.96	3.0	6816	0.4943	0.0245	0.8043	0.3363	0.8608	0.8409	0.7043	0.2676	0.8069	0.8048	0.9372	0.7637	0.9372	0.9477	0.9575	0.5735
0.5852	4.0	9088	0.7306	0.0195	0.8371	0.3860	0.8687	0.8624	0.7568	0.3083	0.8212	0.8378	0.9365	0.7232	0.9365	0.9459	0.9597	0.6410
0.3454	5.0	11360	0.8951	0.0168	0.8565	0.3960	0.8831	0.8789	0.7903	0.3221	0.8426	0.8631	0.9348	0.6915	0.9348	0.9435	0.9604	0.6896

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: apache-2.0
Created: Feb 10, 2024
Updated: Feb 11, 2024