---
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
- f1
model-index:
- name: indobert-classification
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: indonlu
      type: indonlu
      args: smsa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9428571428571428
    - name: F1
      type: f1
      value: 0.9428847892722086
---

<!-- 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. -->

# indobert-classification

This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2296
- Accuracy: 0.9429
- F1: 0.9429

## 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: 2e-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
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2409        | 1.0   | 688  | 0.2098          | 0.9413   | 0.9414 |
| 0.1091        | 2.0   | 1376 | 0.2296          | 0.9429   | 0.9429 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6