BioBERT-finetuned-ner-S800

ViktorDo/BioBERT-finetuned-ner-S800

BioBERT-finetuned-ner-S800 is a token classification model from ViktorDo. Use it when you need labels on individual words, such as names. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
Model type: bert
Access: Public
Created: May 19, 2023
Updated: May 19, 2023
SHA: b20f8815

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Model card

From the Hugging Face model README

BioBERT-finetuned-ner-S800

This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0693
Precision: 0.6727
Recall: 0.7767
F1: 0.7210
Accuracy: 0.9773

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
No log	1.0	55	0.0689	0.5835	0.6573	0.6182	0.9739
No log	2.0	110	0.0687	0.6524	0.7514	0.6984	0.9766
No log	3.0	165	0.0693	0.6727	0.7767	0.7210	0.9773

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
Created: May 19, 2023
Updated: May 19, 2023