---
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: 0.8809523809523809
---

<!-- 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: 0.4075
- Accuracy: 0.8810

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 344  | 0.6672          | 0.7103   |
| 0.7802        | 2.0   | 688  | 0.4828          | 0.8111   |
| 0.4817        | 3.0   | 1032 | 0.4378          | 0.8278   |
| 0.4817        | 4.0   | 1376 | 0.3920          | 0.8540   |
| 0.3703        | 5.0   | 1720 | 0.4251          | 0.8524   |
| 0.2826        | 6.0   | 2064 | 0.3883          | 0.8659   |
| 0.2826        | 7.0   | 2408 | 0.3782          | 0.8698   |
| 0.2024        | 8.0   | 2752 | 0.3932          | 0.8698   |
| 0.1429        | 9.0   | 3096 | 0.4075          | 0.8810   |
| 0.1429        | 10.0  | 3440 | 0.4257          | 0.8738   |


### Framework versions

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