---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-pt-pl30-4
  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-pl30-4

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: 0.3072
- Accuracy: 0.8822
- Precision: 0.8574
- Recall: 0.8592
- F1: 0.8583

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5438        | 1.0   | 122  | 0.4988          | 0.7218   | 0.6601    | 0.6507 | 0.6546 |
| 0.4428        | 2.0   | 244  | 0.3788          | 0.8446   | 0.8107    | 0.8226 | 0.8161 |
| 0.3441        | 3.0   | 366  | 0.3289          | 0.8596   | 0.8510    | 0.7982 | 0.8179 |
| 0.2986        | 4.0   | 488  | 0.2884          | 0.8797   | 0.8572    | 0.8499 | 0.8534 |
| 0.2667        | 5.0   | 610  | 0.2698          | 0.8772   | 0.8535    | 0.8481 | 0.8507 |
| 0.2524        | 6.0   | 732  | 0.2723          | 0.8847   | 0.8609    | 0.8609 | 0.8609 |
| 0.2343        | 7.0   | 854  | 0.3180          | 0.8647   | 0.8533    | 0.8092 | 0.8266 |
| 0.2212        | 8.0   | 976  | 0.2949          | 0.8822   | 0.8674    | 0.8417 | 0.8529 |
| 0.2142        | 9.0   | 1098 | 0.2828          | 0.8847   | 0.8697    | 0.8459 | 0.8565 |
| 0.1958        | 10.0  | 1220 | 0.2887          | 0.8697   | 0.8399    | 0.8528 | 0.8458 |
| 0.1855        | 11.0  | 1342 | 0.2868          | 0.8822   | 0.8548    | 0.8667 | 0.8603 |
| 0.1742        | 12.0  | 1464 | 0.2981          | 0.8747   | 0.8552    | 0.8363 | 0.8448 |
| 0.1601        | 13.0  | 1586 | 0.2930          | 0.8797   | 0.8539    | 0.8574 | 0.8556 |
| 0.1602        | 14.0  | 1708 | 0.2979          | 0.8797   | 0.8504    | 0.8699 | 0.8590 |
| 0.1497        | 15.0  | 1830 | 0.2969          | 0.8872   | 0.8606    | 0.8727 | 0.8662 |
| 0.1447        | 16.0  | 1952 | 0.2963          | 0.8847   | 0.8599    | 0.8634 | 0.8616 |
| 0.1394        | 17.0  | 2074 | 0.3018          | 0.8822   | 0.8564    | 0.8617 | 0.8590 |
| 0.1333        | 18.0  | 2196 | 0.3065          | 0.8822   | 0.8574    | 0.8592 | 0.8583 |
| 0.1406        | 19.0  | 2318 | 0.3062          | 0.8822   | 0.8574    | 0.8592 | 0.8583 |
| 0.1243        | 20.0  | 2440 | 0.3072          | 0.8822   | 0.8574    | 0.8592 | 0.8583 |


### Framework versions

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