---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-pt-pl10-4
  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-pl10-4

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: 0.3026
- Accuracy: 0.8822
- Precision: 0.8624
- Recall: 0.8492
- F1: 0.8553

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5514        | 1.0   | 122  | 0.5084          | 0.7218   | 0.6601    | 0.6507 | 0.6546 |
| 0.4753        | 2.0   | 244  | 0.4007          | 0.8170   | 0.7870    | 0.7530 | 0.7662 |
| 0.3834        | 3.0   | 366  | 0.3542          | 0.8396   | 0.8449    | 0.7540 | 0.7805 |
| 0.3188        | 4.0   | 488  | 0.3214          | 0.8622   | 0.8342    | 0.8325 | 0.8333 |
| 0.2981        | 5.0   | 610  | 0.2984          | 0.8822   | 0.8624    | 0.8492 | 0.8553 |
| 0.2835        | 6.0   | 732  | 0.2810          | 0.8697   | 0.8520    | 0.8253 | 0.8368 |
| 0.2517        | 7.0   | 854  | 0.2866          | 0.8872   | 0.8672    | 0.8577 | 0.8622 |
| 0.2374        | 8.0   | 976  | 0.2997          | 0.8797   | 0.8671    | 0.8349 | 0.8485 |
| 0.2293        | 9.0   | 1098 | 0.2909          | 0.8797   | 0.8600    | 0.8449 | 0.8518 |
| 0.2091        | 10.0  | 1220 | 0.2928          | 0.8822   | 0.8564    | 0.8617 | 0.8590 |
| 0.198         | 11.0  | 1342 | 0.2847          | 0.8797   | 0.8522    | 0.8624 | 0.8570 |
| 0.1906        | 12.0  | 1464 | 0.3120          | 0.8747   | 0.8586    | 0.8313 | 0.8431 |
| 0.1818        | 13.0  | 1586 | 0.2906          | 0.8772   | 0.8535    | 0.8481 | 0.8507 |
| 0.1756        | 14.0  | 1708 | 0.2810          | 0.8772   | 0.8524    | 0.8506 | 0.8515 |
| 0.174         | 15.0  | 1830 | 0.2829          | 0.8847   | 0.8634    | 0.8559 | 0.8595 |
| 0.1705        | 16.0  | 1952 | 0.2922          | 0.8822   | 0.8624    | 0.8492 | 0.8553 |
| 0.1509        | 17.0  | 2074 | 0.2991          | 0.8822   | 0.8596    | 0.8542 | 0.8568 |
| 0.1549        | 18.0  | 2196 | 0.3000          | 0.8822   | 0.8624    | 0.8492 | 0.8553 |
| 0.1469        | 19.0  | 2318 | 0.2943          | 0.8847   | 0.8609    | 0.8609 | 0.8609 |
| 0.1493        | 20.0  | 2440 | 0.3026          | 0.8822   | 0.8624    | 0.8492 | 0.8553 |


### Framework versions

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