---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: newsdata-bertimbal
  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. -->

# newsdata-bertimbal

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: 0.7455
- Accuracy: 0.8743

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.8448        | 0.0859 | 5000  | 1.1296          | 0.8044   |
| 0.7301        | 0.1718 | 10000 | 1.0056          | 0.8258   |
| 0.6827        | 0.2577 | 15000 | 0.9388          | 0.8464   |
| 0.6221        | 0.3436 | 20000 | 0.9358          | 0.8502   |
| 0.5611        | 0.4295 | 25000 | 0.8983          | 0.8567   |
| 0.5291        | 0.5155 | 30000 | 0.8503          | 0.8575   |
| 0.4202        | 0.6014 | 35000 | 0.8353          | 0.8656   |
| 0.5436        | 0.6873 | 40000 | 0.7476          | 0.8706   |
| 0.4814        | 0.7732 | 45000 | 0.7863          | 0.8669   |
| 0.4853        | 0.8591 | 50000 | 0.7284          | 0.8720   |
| 0.39          | 0.9450 | 55000 | 0.7455          | 0.8743   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1