README.md

metadata

license: mit
base_model: neuralmind/bert-large-portuguese-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: LVI_bert-large-portuguese-cased
    results: []

LVI_bert-large-portuguese-cased

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: 0.0755
• Accuracy: 0.9775
• F1: 0.9775
• Precision: 0.9758
• Recall: 0.9793

Run it

import transformers

model_name = "liaad/LVI_bert-large-portuguese-cased"
pipe = transformers.pipeline(model=model_name)

text = "Olá, como você está?"
print(pipe(text))

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-06
• train_batch_size: 16
• eval_batch_size: 16
• 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	Accuracy	F1	Precision	Recall
0.1071	1.0	3217	0.0755	0.9775	0.9775	0.9758	0.9793

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2