---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nees-bert-base-portuguese-cased-finetuned-ner
  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. -->

# nees-bert-base-portuguese-cased-finetuned-ner

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0255
- Precision: 0.6545
- Recall: 0.7802
- F1: 0.7119
- Accuracy: 0.9952

## 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: 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0344        | 1.0   | 519  | 0.0189          | 0.0       | 0.0    | 0.0    | 0.9949   |
| 0.0145        | 2.0   | 1038 | 0.0112          | 0.5050    | 0.4737 | 0.4888 | 0.9952   |
| 0.0121        | 3.0   | 1557 | 0.0132          | 0.3684    | 0.1300 | 0.1922 | 0.9953   |
| 0.0107        | 4.0   | 2076 | 0.0239          | 0.6366    | 0.7647 | 0.6948 | 0.9955   |
| 0.0056        | 5.0   | 2595 | 0.0151          | 0.6845    | 0.7121 | 0.6980 | 0.9950   |
| 0.0053        | 6.0   | 3114 | 0.0278          | 0.6432    | 0.7368 | 0.6869 | 0.9943   |
| 0.0047        | 7.0   | 3633 | 0.0199          | 0.5682    | 0.7740 | 0.6553 | 0.9953   |
| 0.0043        | 8.0   | 4152 | 0.0231          | 0.6429    | 0.7802 | 0.7049 | 0.9951   |
| 0.0022        | 9.0   | 4671 | 0.0255          | 0.6487    | 0.7833 | 0.7097 | 0.9955   |
| 0.0025        | 10.0  | 5190 | 0.0255          | 0.6545    | 0.7802 | 0.7119 | 0.9952   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2