---
license: mit
base_model: PORTULAN/albertina-100m-portuguese-ptpt-encoder
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: LVI_albertina-100m-portuguese-ptpt-encoder
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# LVI_albertina-100m-portuguese-ptpt-encoder

This model is a fine-tuned version of [PORTULAN/albertina-100m-portuguese-ptpt-encoder](https://huggingface.co/PORTULAN/albertina-100m-portuguese-ptpt-encoder) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1867
- Accuracy: 0.9802
- F1: 0.9800
- Precision: 0.9905
- Recall: 0.9696

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1284        | 1.0   | 3217  | 0.1454          | 0.9581   | 0.9567 | 0.9882    | 0.9272 |
| 0.0946        | 2.0   | 6434  | 0.1211          | 0.9737   | 0.9734 | 0.9864    | 0.9607 |
| 0.0575        | 3.0   | 9651  | 0.1087          | 0.9776   | 0.9774 | 0.9892    | 0.9659 |
| 0.0374        | 4.0   | 12868 | 0.1033          | 0.981    | 0.9809 | 0.9854    | 0.9765 |
| 0.0311        | 5.0   | 16085 | 0.1154          | 0.981    | 0.9808 | 0.9896    | 0.9722 |
| 0.0125        | 6.0   | 19302 | 0.1143          | 0.9830   | 0.9830 | 0.9833    | 0.9826 |
| 0.0107        | 7.0   | 22519 | 0.1562          | 0.9807   | 0.9805 | 0.9910    | 0.9702 |
| 0.0032        | 8.0   | 25736 | 0.1711          | 0.9808   | 0.9806 | 0.9892    | 0.9721 |
| 0.0036        | 9.0   | 28953 | 0.1867          | 0.9802   | 0.9800 | 0.9905    | 0.9696 |


### Framework versions

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