---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-pt-pl10-0
  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-pl10-0

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: 0.2798
- Accuracy: 0.8972
- Precision: 0.8723
- Recall: 0.8848
- F1: 0.8781

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5568        | 1.0   | 122  | 0.4822          | 0.7243   | 0.6557    | 0.6074 | 0.6144 |
| 0.4661        | 2.0   | 244  | 0.4453          | 0.7544   | 0.7241    | 0.7612 | 0.7304 |
| 0.3875        | 3.0   | 366  | 0.3447          | 0.8622   | 0.8488    | 0.8075 | 0.8239 |
| 0.318         | 4.0   | 488  | 0.3442          | 0.8496   | 0.8158    | 0.8436 | 0.8267 |
| 0.2855        | 5.0   | 610  | 0.3349          | 0.8496   | 0.8158    | 0.8411 | 0.8260 |
| 0.2638        | 6.0   | 732  | 0.3548          | 0.8371   | 0.8052    | 0.8472 | 0.8177 |
| 0.2397        | 7.0   | 854  | 0.3254          | 0.8647   | 0.8326    | 0.8592 | 0.8434 |
| 0.2428        | 8.0   | 976  | 0.2799          | 0.8922   | 0.8804    | 0.8537 | 0.8655 |
| 0.2229        | 9.0   | 1098 | 0.2903          | 0.8722   | 0.8431    | 0.8546 | 0.8484 |
| 0.2144        | 10.0  | 1220 | 0.2583          | 0.8972   | 0.8743    | 0.8798 | 0.8770 |
| 0.1967        | 11.0  | 1342 | 0.2743          | 0.8822   | 0.8530    | 0.8742 | 0.8622 |
| 0.1855        | 12.0  | 1464 | 0.2913          | 0.8772   | 0.8473    | 0.8681 | 0.8563 |
| 0.1761        | 13.0  | 1586 | 0.2660          | 0.9023   | 0.8913    | 0.8683 | 0.8786 |
| 0.1733        | 14.0  | 1708 | 0.2868          | 0.8822   | 0.8530    | 0.8742 | 0.8622 |
| 0.1582        | 15.0  | 1830 | 0.2801          | 0.8847   | 0.8561    | 0.8759 | 0.8648 |
| 0.1537        | 16.0  | 1952 | 0.3073          | 0.8747   | 0.8438    | 0.8713 | 0.8550 |
| 0.1537        | 17.0  | 2074 | 0.2702          | 0.8972   | 0.8723    | 0.8848 | 0.8781 |
| 0.1461        | 18.0  | 2196 | 0.2923          | 0.8947   | 0.8682    | 0.8855 | 0.8760 |
| 0.1449        | 19.0  | 2318 | 0.2791          | 0.8947   | 0.8690    | 0.8830 | 0.8755 |
| 0.1502        | 20.0  | 2440 | 0.2798          | 0.8972   | 0.8723    | 0.8848 | 0.8781 |


### Framework versions

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