---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: text-classification
  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. -->

# text-classification

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9158
- Accuracy: 0.7695

## 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: 8
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0037        | 1.0   | 499  | 1.0119          | 0.7024   |
| 0.7645        | 2.0   | 998  | 0.9929          | 0.7275   |
| 0.6417        | 3.0   | 1497 | 0.9623          | 0.7335   |
| 0.8177        | 4.0   | 1996 | 0.9158          | 0.7695   |
| 0.4176        | 5.0   | 2495 | 1.2640          | 0.7635   |
| 0.7335        | 6.0   | 2994 | 1.2080          | 0.7615   |
| 0.3151        | 7.0   | 3493 | 1.3485          | 0.7575   |
| 0.7147        | 8.0   | 3992 | 1.2736          | 0.7605   |
| 0.0728        | 9.0   | 4491 | 1.4076          | 0.7565   |
| 0.2183        | 10.0  | 4990 | 1.5012          | 0.7505   |
| 0.2202        | 11.0  | 5489 | 1.5981          | 0.7405   |
| 0.2694        | 12.0  | 5988 | 1.5516          | 0.7415   |
| 0.0497        | 13.0  | 6487 | 1.6425          | 0.7485   |
| 0.2473        | 14.0  | 6986 | 1.7087          | 0.7475   |
| 0.1949        | 15.0  | 7485 | 1.6820          | 0.7535   |
| 0.1233        | 16.0  | 7984 | 1.7447          | 0.7405   |
| 0.0632        | 17.0  | 8483 | 1.7229          | 0.7475   |
| 0.1161        | 18.0  | 8982 | 1.7292          | 0.7545   |
| 0.0023        | 19.0  | 9481 | 1.7930          | 0.7465   |
| 0.0854        | 20.0  | 9980 | 1.8089          | 0.7495   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1