bio-bert

praneethvasarla/bio-bert

bio-bert is a token classification model from praneethvasarla. Use it when you need labels on individual words, such as names. 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: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Nov 24, 2023
Updated: Nov 27, 2023
SHA: d51e966f

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Base models

Model card

From the Hugging Face model README

bio-bert

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0000
Precision: 1.0
Recall: 1.0
F1: 1.0
Accuracy: 1.0
All Metrics: {'CELL': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6270}, 'CHEMICAL': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 34547}, 'CORONAVIRUS': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4777}, 'DISEASE_OR_SYNDROME': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13422}, 'EUKARYOTE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2501}, 'GENE_OR_GENOME': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 32504}, 'ORGANISM': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4620}, 'THERAPEUTIC_OR_PREVENTIVE_PROCEDURE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3186}, 'TISSUE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2333}, 'VIRUS': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1596}, 'overall_precision': 1.0, 'overall_recall': 1.0, 'overall_f1': 1.0, 'overall_accuracy': 1.0}

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	All Metrics
0.0003	1.0	3375	0.0001	0.9999	1.0000	0.9999	1.0000	{'CELL': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6270}, 'CHEMICAL': {'precision': 0.9999131693198263, 'recall': 1.0, 'f1': 0.9999565827749395, 'number': 34547}, 'CORONAVIRUS': {'precision': 0.9989539748953975, 'recall': 0.9995813271927988, 'f1': 0.9992675525792613, 'number': 4777}, 'DISEASE_OR_SYNDROME': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13422}, 'EUKARYOTE': {'precision': 0.9992006394884093, 'recall': 0.9996001599360256, 'f1': 0.9994003597841296, 'number': 2501}, 'GENE_OR_GENOME': {'precision': 0.9998769457946225, 'recall': 0.999938469111494, 'f1': 0.9999077065066913, 'number': 32504}, 'ORGANISM': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4620}, 'THERAPEUTIC_OR_PREVENTIVE_PROCEDURE': {'precision': 0.9996862252902416, 'recall': 1.0, 'f1': 0.9998430880276166, 'number': 3186}, 'TISSUE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2333}, 'VIRUS': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1596}, 'overall_precision': 0.9998581774861487, 'overall_recall': 0.999952721358599, 'overall_f1': 0.9999054471875266, 'overall_accuracy': 0.9999971807367637}
0.0001	2.0	6750	0.0000	1.0	1.0	1.0	1.0	{'CELL': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6270}, 'CHEMICAL': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 34547}, 'CORONAVIRUS': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4777}, 'DISEASE_OR_SYNDROME': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13422}, 'EUKARYOTE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2501}, 'GENE_OR_GENOME': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 32504}, 'ORGANISM': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4620}, 'THERAPEUTIC_OR_PREVENTIVE_PROCEDURE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3186}, 'TISSUE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2333}, 'VIRUS': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1596}, 'overall_precision': 1.0, 'overall_recall': 1.0, 'overall_f1': 1.0, 'overall_accuracy': 1.0}
0.0	3.0	10125	0.0000	1.0	1.0	1.0	1.0	{'CELL': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6270}, 'CHEMICAL': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 34547}, 'CORONAVIRUS': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4777}, 'DISEASE_OR_SYNDROME': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13422}, 'EUKARYOTE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2501}, 'GENE_OR_GENOME': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 32504}, 'ORGANISM': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 4620}, 'THERAPEUTIC_OR_PREVENTIVE_PROCEDURE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3186}, 'TISSUE': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2333}, 'VIRUS': {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1596}, 'overall_precision': 1.0, 'overall_recall': 1.0, 'overall_f1': 1.0, 'overall_accuracy': 1.0}

Framework versions

Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Nov 24, 2023
Updated: Nov 27, 2023