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belisards/
mmnlab

Name: mmnlab
Availability: InStock

generated_from_trainer

neuralmind/bert-large-portuguese-cased

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final

This model is a fine-tuned version of neuralmind/bert-large-portuguese-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3507
Accuracy: 0.8945
F1: 0.8863
Recall: 0.8760
Precision: 0.8968

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: 64
eval_batch_size: 64
seed: 5151
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision
0.485	0.9756	80	0.3916	0.8182	0.7984	0.7674	0.8319
0.3395	1.9512	160	0.3039	0.8764	0.8547	0.7752	0.9524
0.2139	2.9268	240	0.3122	0.8691	0.8548	0.8217	0.8908
0.084	3.9024	320	0.3507	0.8945	0.8863	0.8760	0.8968
0.058	4.8780	400	0.5087	0.8727	0.8571	0.8140	0.9052
0.0389	5.8537	480	0.4579	0.8982	0.888	0.8605	0.9174
0.0264	6.8293	560	0.5052	0.8873	0.8765	0.8527	0.9016

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

belisards/mmnlab

final

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

belisards/
mmnlab