biobert-finetuned-ner – AI Model by jialinselenasong | AlphaNeural AI

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jialinselenasong/
biobert-finetuned-ner

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token-classification

generated_from_trainer

dmis-lab/biobert-v1.1

autotrain_compatible

endpoints_compatible

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biobert-finetuned-ner

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: 0.6965
Precision: 0.6381
Recall: 0.6865
F1: 0.6614
Accuracy: 0.8583

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	305	0.4123	0.6110	0.6694	0.6389	0.8542
0.4534	2.0	610	0.4023	0.6259	0.6848	0.6540	0.8586
0.4534	3.0	915	0.4384	0.6369	0.6991	0.6666	0.8615
0.2438	4.0	1220	0.4799	0.6445	0.6941	0.6684	0.8615
0.1551	5.0	1525	0.5190	0.6464	0.6908	0.6678	0.8628
0.1551	6.0	1830	0.5772	0.6454	0.6751	0.6599	0.8597
0.1044	7.0	2135	0.6141	0.6413	0.6881	0.6639	0.8586
0.1044	8.0	2440	0.6587	0.6353	0.6945	0.6636	0.8590
0.0755	9.0	2745	0.6856	0.6357	0.6905	0.6620	0.8580
0.0604	10.0	3050	0.6965	0.6381	0.6865	0.6614	0.8583

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1