BioBERT-LitCovid-1.4

sofia-todeschini/BioBERT-LitCovid-1.4

BioBERT-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: bert
Access: Public
Created: Jun 25, 2024
Updated: Jun 25, 2024
SHA: e7fca1a0

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Model card

From the Hugging Face model README

BioBERT-LitCovid-1.4

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: 0.5756
Hamming loss: 0.0802
F1 micro: 0.6160
F1 macro: 0.4740
F1 weighted: 0.6962
F1 samples: 0.6217
Precision micro: 0.4710
Precision macro: 0.3578
Precision weighted: 0.6089
Precision samples: 0.5156
Recall micro: 0.8901
Recall macro: 0.8404
Recall weighted: 0.8901
Recall samples: 0.9055
Roc Auc: 0.9061
Accuracy: 0.0775

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
0.6673	1.0	1151	0.6365	0.1262	0.5023	0.3822	0.6341	0.5084	0.3513	0.2799	0.5428	0.3829	0.8808	0.8538	0.8808	0.8981	0.8770	0.0088
0.5371	2.0	2303	0.5721	0.1080	0.5442	0.4060	0.6607	0.5578	0.3916	0.2993	0.5701	0.4391	0.8917	0.8644	0.8917	0.9074	0.8919	0.0365
0.4628	3.0	3454	0.5620	0.0940	0.5780	0.4370	0.6776	0.5874	0.4280	0.3248	0.5909	0.4739	0.8899	0.8572	0.8899	0.9054	0.8986	0.0510
0.3925	4.0	4606	0.5744	0.0796	0.6160	0.4742	0.6960	0.6208	0.4728	0.3591	0.6113	0.5160	0.8837	0.8377	0.8837	0.9004	0.9035	0.0752
0.3647	5.0	5755	0.5756	0.0802	0.6160	0.4740	0.6962	0.6217	0.4710	0.3578	0.6089	0.5156	0.8901	0.8404	0.8901	0.9055	0.9061	0.0775

Framework versions

Transformers 4.28.0
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.13.3

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