---
license: mit
base_model: cahya/distilbert-base-indonesian
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-indonesian-finetuned-PRDECT-ID
  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. -->

# distilbert-base-indonesian-finetuned-PRDECT-ID

This model is a fine-tuned version of [cahya/distilbert-base-indonesian](https://huggingface.co/cahya/distilbert-base-indonesian) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9507        | 1.0   | 41   | 0.8377          |
| 0.0765        | 2.0   | 82   | 0.0212          |
| 0.0025        | 3.0   | 123  | 0.0020          |
| 0.0013        | 4.0   | 164  | 0.0013          |
| 0.0009        | 5.0   | 205  | 0.0009          |
| 0.0007        | 6.0   | 246  | 0.0007          |
| 0.0005        | 7.0   | 287  | 0.0006          |
| 0.0004        | 8.0   | 328  | 0.0005          |
| 0.0003        | 9.0   | 369  | 0.0004          |
| 0.0002        | 10.0  | 410  | 0.0003          |
| 0.0002        | 11.0  | 451  | 0.0003          |
| 0.0002        | 12.0  | 492  | 0.0003          |
| 0.0002        | 13.0  | 533  | 0.0002          |
| 0.0001        | 14.0  | 574  | 0.0002          |
| 0.0001        | 15.0  | 615  | 0.0002          |
| 0.0001        | 16.0  | 656  | 0.0002          |
| 0.0001        | 17.0  | 697  | 0.0002          |
| 0.0001        | 18.0  | 738  | 0.0002          |
| 0.0001        | 19.0  | 779  | 0.0002          |
| 0.0001        | 20.0  | 820  | 0.0002          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1