BioElectra-LitCovid-1.4

sofia-todeschini/BioElectra-LitCovid-1.4

BioElectra-LitCovid-1.4 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: electra
Access: Public
Created: Jun 25, 2024
Updated: Jun 25, 2024
SHA: b2ea3b8c

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Model card

From the Hugging Face model README

BioElectra-LitCovid-1.4

This model is a fine-tuned version of kamalkraj/bioelectra-base-discriminator-pubmed on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6551
Hamming loss: 0.1096
F1 micro: 0.5375
F1 macro: 0.4017
F1 weighted: 0.6519
F1 samples: 0.5520
Precision micro: 0.3867
Precision macro: 0.2948
Precision weighted: 0.5638
Precision samples: 0.4347
Recall micro: 0.8813
Recall macro: 0.8425
Recall weighted: 0.8813
Recall samples: 0.8977
Roc Auc: 0.8862
Accuracy: 0.0375

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
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
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
0.8117	1.0	1151	0.7562	0.1732	0.4140	0.3137	0.5784	0.4179	0.2740	0.2255	0.4949	0.2947	0.8462	0.8285	0.8462	0.8675	0.8357	0.0005
0.639	2.0	2303	0.6690	0.1346	0.4836	0.3618	0.6199	0.4952	0.3347	0.2629	0.5289	0.3716	0.8714	0.8448	0.8714	0.8906	0.8682	0.0095
0.556	3.0	3454	0.6453	0.1253	0.5012	0.3747	0.6358	0.5147	0.3519	0.2750	0.5539	0.3944	0.8706	0.8536	0.8706	0.8895	0.8728	0.0220
0.4906	4.0	4606	0.6567	0.1111	0.5339	0.4013	0.6494	0.5469	0.3832	0.2946	0.5608	0.4282	0.8800	0.8428	0.8800	0.8976	0.8848	0.0312
0.4594	5.0	5755	0.6551	0.1096	0.5375	0.4017	0.6519	0.5520	0.3867	0.2948	0.5638	0.4347	0.8813	0.8425	0.8813	0.8977	0.8862	0.0375

Framework versions

Transformers 4.28.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: electra
Created: Jun 25, 2024
Updated: Jun 25, 2024