---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-pt-pl20-0
  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. -->

# sentiment-pt-pl20-0

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2882
- Accuracy: 0.9073
- Precision: 0.8875
- Recall: 0.8894
- F1: 0.8884

## 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: 30
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5417        | 1.0   | 122  | 0.4732          | 0.7544   | 0.7028    | 0.6612 | 0.6731 |
| 0.4395        | 2.0   | 244  | 0.4128          | 0.7920   | 0.7613    | 0.8028 | 0.7705 |
| 0.3319        | 3.0   | 366  | 0.3230          | 0.8647   | 0.8439    | 0.8217 | 0.8315 |
| 0.2873        | 4.0   | 488  | 0.3222          | 0.8521   | 0.8201    | 0.8279 | 0.8238 |
| 0.2571        | 5.0   | 610  | 0.2968          | 0.8722   | 0.8431    | 0.8546 | 0.8484 |
| 0.2443        | 6.0   | 732  | 0.2918          | 0.8672   | 0.8353    | 0.8635 | 0.8466 |
| 0.2256        | 7.0   | 854  | 0.2982          | 0.8647   | 0.8325    | 0.8642 | 0.8447 |
| 0.2172        | 8.0   | 976  | 0.2722          | 0.8922   | 0.8826    | 0.8512 | 0.8647 |
| 0.2049        | 9.0   | 1098 | 0.2648          | 0.8947   | 0.8698    | 0.8805 | 0.8749 |
| 0.1914        | 10.0  | 1220 | 0.2680          | 0.9073   | 0.8977    | 0.8744 | 0.8849 |
| 0.1724        | 11.0  | 1342 | 0.2645          | 0.8997   | 0.8757    | 0.8866 | 0.8808 |
| 0.1689        | 12.0  | 1464 | 0.2746          | 0.8997   | 0.8740    | 0.8916 | 0.8819 |
| 0.1473        | 13.0  | 1586 | 0.2837          | 0.9048   | 0.9002    | 0.8651 | 0.8801 |
| 0.1577        | 14.0  | 1708 | 0.2892          | 0.9023   | 0.8773    | 0.8933 | 0.8846 |
| 0.1468        | 15.0  | 1830 | 0.2789          | 0.9023   | 0.8802    | 0.8858 | 0.8830 |
| 0.1473        | 16.0  | 1952 | 0.2852          | 0.8972   | 0.8732    | 0.8823 | 0.8776 |
| 0.1274        | 17.0  | 2074 | 0.2858          | 0.9048   | 0.8838    | 0.8876 | 0.8857 |
| 0.1318        | 18.0  | 2196 | 0.2927          | 0.8997   | 0.8767    | 0.8841 | 0.8803 |
| 0.1355        | 19.0  | 2318 | 0.2884          | 0.9073   | 0.8875    | 0.8894 | 0.8884 |
| 0.1367        | 20.0  | 2440 | 0.2882          | 0.9073   | 0.8875    | 0.8894 | 0.8884 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2