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---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: LVI_bert-base-portuguese-cased
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# LVI_bert-base-portuguese-cased
This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2393
- Accuracy: 0.9428
- F1: 0.9445
- Precision: 0.9182
- Recall: 0.9723
## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1736 | 1.0 | 3217 | 0.1532 | 0.9615 | 0.9618 | 0.955 | 0.9686 |
| 0.1105 | 2.0 | 6434 | 0.1464 | 0.9629 | 0.9630 | 0.9582 | 0.9679 |
| 0.0984 | 3.0 | 9651 | 0.2067 | 0.9525 | 0.9511 | 0.9786 | 0.9251 |
| 0.0996 | 4.0 | 12868 | 0.1873 | 0.9608 | 0.9610 | 0.9569 | 0.9651 |
| 0.17 | 5.0 | 16085 | 0.2393 | 0.9428 | 0.9445 | 0.9182 | 0.9723 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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