---
license: mit
base_model: w11wo/indo-roberta-small
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
model-index:
- name: indo-roberta-small-finetuned-indonlu-smsa
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: indonlu
      type: indonlu
      config: smsa
      split: validation
      args: smsa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.888095238095238
---

<!-- 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. -->

# indo-roberta-small-finetuned-indonlu-smsa

This model is a fine-tuned version of [w11wo/indo-roberta-small](https://huggingface.co/w11wo/indo-roberta-small) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4497
- Accuracy: 0.8881

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 172  | 0.6502          | 0.7143   |
| No log        | 2.0   | 344  | 0.4720          | 0.8127   |
| 0.6168        | 3.0   | 516  | 0.4511          | 0.8357   |
| 0.6168        | 4.0   | 688  | 0.3825          | 0.8540   |
| 0.6168        | 5.0   | 860  | 0.3655          | 0.8595   |
| 0.2954        | 6.0   | 1032 | 0.3672          | 0.8683   |
| 0.2954        | 7.0   | 1204 | 0.3839          | 0.8746   |
| 0.2954        | 8.0   | 1376 | 0.4220          | 0.8706   |
| 0.1328        | 9.0   | 1548 | 0.4497          | 0.8881   |
| 0.1328        | 10.0  | 1720 | 0.4455          | 0.8865   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2