BioBERT-LitCovid-v1.3hh

sofia-todeschini/BioBERT-LitCovid-v1.3hh

BioBERT-LitCovid-v1.3hh 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: Mar 9, 2024
Updated: Mar 9, 2024
SHA: 0c0830ad

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Model card

From the Hugging Face model README

BioBERT-LitCovid-v1.3hh

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: 0.9050
Hamming loss: 0.0147
F1 micro: 0.8717
F1 macro: 0.4368
F1 weighted: 0.8882
F1 samples: 0.8857
Precision micro: 0.8176
Precision macro: 0.3560
Precision weighted: 0.8520
Precision samples: 0.8728
Recall micro: 0.9334
Recall macro: 0.7011
Recall weighted: 0.9334
Recall samples: 0.9438
Roc Auc: 0.9608
Accuracy: 0.7014

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: 0.11492820779210673
num_epochs: 5
mixed_precision_training: Native AMP

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
1.1889	1.0	2272	0.4213	0.0512	0.6596	0.2446	0.8084	0.7608	0.5126	0.1941	0.7385	0.7077	0.9250	0.8376	0.9250	0.9404	0.9376	0.4492
0.8405	2.0	4544	0.4523	0.0234	0.8101	0.3434	0.8586	0.8435	0.7177	0.2700	0.8104	0.8130	0.9296	0.7802	0.9296	0.9421	0.9544	0.5954
0.6991	3.0	6816	0.5218	0.0214	0.8253	0.3595	0.8703	0.8563	0.7327	0.2829	0.8184	0.8238	0.9447	0.7721	0.9447	0.9534	0.9626	0.6190
0.3865	4.0	9088	0.8428	0.0155	0.8655	0.4279	0.8826	0.8808	0.8092	0.3453	0.8458	0.8667	0.9302	0.6992	0.9302	0.9417	0.9589	0.6917
0.1332	5.0	11360	0.9050	0.0147	0.8717	0.4368	0.8882	0.8857	0.8176	0.3560	0.8520	0.8728	0.9334	0.7011	0.9334	0.9438	0.9608	0.7014

Framework versions

Transformers 4.28.0
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
Created: Mar 9, 2024
Updated: Mar 9, 2024