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tiagoblima/
punctuation-nilc-bert-large

Name: punctuation-nilc-bert-large
Availability: InStock

generated_from_trainer

mit

autotrain_compatible

endpoints_compatible

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punctuation-nilc-bert-large

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: 0.1585
Precision: 0.9053
Recall: 0.8923
F1: 0.8988
Accuracy: 0.9755

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: 5e-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: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0742	1.0	1172	0.0653	0.9194	0.8702	0.8941	0.9742
0.0396	2.0	2344	0.0773	0.9088	0.8834	0.8959	0.9748
0.0153	3.0	3516	0.1171	0.8996	0.8817	0.8906	0.9739
0.0059	4.0	4688	0.1390	0.9174	0.8719	0.8941	0.9747
0.0024	5.0	5860	0.1585	0.9053	0.8923	0.8988	0.9755

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2

tiagoblima/punctuation-nilc-bert-large

punctuation-nilc-bert-large

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tiagoblima/
punctuation-nilc-bert-large