Bioformer-LitCovid-v1.2.3

sofia-todeschini/Bioformer-LitCovid-v1.2.3

Bioformer-LitCovid-v1.2.3 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: Aug 16, 2023
Updated: Aug 16, 2023
SHA: 767c2d77

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Model card

From the Hugging Face model README

Bioformer-LitCovid-v1.2.3

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: 0.9317
F1 micro: 0.7843
F1 macro: 0.2816
F1 weighted: 0.8523
F1 samples: 0.8647
Precision micro: 0.6737
Precision macro: 0.2255
Precision weighted: 0.7914
Precision samples: 0.8417
Recall micro: 0.9384
Recall macro: 0.7715
Recall weighted: 0.9384
Recall samples: 0.9468
Roc Auc: 0.9568
Accuracy: 0.6515

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: 32
eval_batch_size: 32
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	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
0.8024	1.0	1136	0.6487	0.6577	0.2288	0.7528	0.7600	0.5118	0.1747	0.6503	0.7007	0.9198	0.8185	0.9198	0.9253	0.9361	0.3919
0.639	2.0	2272	0.8280	0.7187	0.2482	0.8039	0.8088	0.5833	0.1935	0.7200	0.7602	0.9361	0.7535	0.9361	0.9441	0.9499	0.4986
0.5167	3.0	3408	0.8318	0.7589	0.2686	0.8342	0.8469	0.6372	0.2127	0.7628	0.8153	0.9382	0.7903	0.9382	0.9462	0.9546	0.6008
0.3641	4.0	4544	0.9231	0.7793	0.2788	0.8472	0.8578	0.6644	0.2220	0.7815	0.8290	0.9422	0.7678	0.9422	0.9497	0.9582	0.6311
0.3754	5.0	5680	0.9317	0.7843	0.2816	0.8523	0.8647	0.6737	0.2255	0.7914	0.8417	0.9384	0.7715	0.9384	0.9468	0.9568	0.6515

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: Aug 16, 2023
Updated: Aug 16, 2023