---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-pt-pl30-1
  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-pl30-1

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: 0.3019
- Accuracy: 0.8647
- Precision: 0.8377
- Recall: 0.8342
- F1: 0.8359

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5413        | 1.0   | 122  | 0.4949          | 0.7368   | 0.6763    | 0.6438 | 0.6531 |
| 0.4306        | 2.0   | 244  | 0.3954          | 0.8246   | 0.7902    | 0.8259 | 0.8019 |
| 0.3344        | 3.0   | 366  | 0.3397          | 0.8521   | 0.8370    | 0.7929 | 0.8099 |
| 0.2925        | 4.0   | 488  | 0.3211          | 0.8471   | 0.8264    | 0.7918 | 0.8058 |
| 0.2794        | 5.0   | 610  | 0.3064          | 0.8622   | 0.8314    | 0.8425 | 0.8365 |
| 0.2464        | 6.0   | 732  | 0.2857          | 0.8672   | 0.8356    | 0.8585 | 0.8453 |
| 0.2332        | 7.0   | 854  | 0.2846          | 0.8772   | 0.8496    | 0.8581 | 0.8537 |
| 0.2216        | 8.0   | 976  | 0.2906          | 0.8596   | 0.8360    | 0.8182 | 0.8262 |
| 0.2123        | 9.0   | 1098 | 0.2781          | 0.8697   | 0.8488    | 0.8303 | 0.8386 |
| 0.1911        | 10.0  | 1220 | 0.2896          | 0.8722   | 0.8562    | 0.8271 | 0.8395 |
| 0.1878        | 11.0  | 1342 | 0.2814          | 0.8747   | 0.8479    | 0.8513 | 0.8496 |
| 0.1797        | 12.0  | 1464 | 0.2830          | 0.8672   | 0.8402    | 0.8385 | 0.8394 |
| 0.1746        | 13.0  | 1586 | 0.2900          | 0.8672   | 0.8496    | 0.8210 | 0.8332 |
| 0.1677        | 14.0  | 1708 | 0.2798          | 0.8697   | 0.8411    | 0.8478 | 0.8443 |
| 0.1585        | 15.0  | 1830 | 0.2823          | 0.8722   | 0.8437    | 0.8521 | 0.8477 |
| 0.1575        | 16.0  | 1952 | 0.2816          | 0.8722   | 0.8413    | 0.8646 | 0.8511 |
| 0.146         | 17.0  | 2074 | 0.3027          | 0.8647   | 0.8377    | 0.8342 | 0.8359 |
| 0.1368        | 18.0  | 2196 | 0.2961          | 0.8672   | 0.8372    | 0.8485 | 0.8425 |
| 0.133         | 19.0  | 2318 | 0.3024          | 0.8622   | 0.8342    | 0.8325 | 0.8333 |
| 0.1377        | 20.0  | 2440 | 0.3019          | 0.8647   | 0.8377    | 0.8342 | 0.8359 |


### Framework versions

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