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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
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