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Vantwoth/
betoNer-biobert

Name: betoNer-biobert
Availability: InStock

generated_from_trainer

dccuchile/bert-base-spanish-wwm-cased

finetune

autotrain_compatible

endpoints_compatible

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betoNer-biobert

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1179
Precision: 0.9511
Recall: 0.9644
F1: 0.9577
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	306	0.1159	0.9263	0.9509	0.9384	0.9686
0.3168	2.0	612	0.1014	0.9358	0.9642	0.9498	0.9742
0.3168	3.0	918	0.0959	0.9462	0.9656	0.9558	0.9767
0.0777	4.0	1224	0.1011	0.9451	0.9661	0.9555	0.9767
0.0541	5.0	1530	0.1073	0.9512	0.9643	0.9577	0.9772
0.0541	6.0	1836	0.1083	0.9441	0.9611	0.9525	0.9751
0.0385	7.0	2142	0.1100	0.9515	0.9632	0.9573	0.9776
0.0385	8.0	2448	0.1153	0.9477	0.9658	0.9567	0.9770
0.0325	9.0	2754	0.1161	0.9495	0.9633	0.9564	0.9769
0.0255	10.0	3060	0.1179	0.9511	0.9644	0.9577	0.9773

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0

Vantwoth/betoNer-biobert

betoNer-biobert

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Vantwoth/
betoNer-biobert