---
language: id
widget:
- text: "Saya mengapresiasi usaha anda"

---
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
model-index:
- name: roberta-base-indonesian-1.5G-finetuned-wnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: indonlu
      type: indonlu
      args: smsa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9246031746031746
---

<!-- 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. -->

# roberta-base-indonesian-1.5G-finetuned-wnli

This model is a fine-tuned version of [cahya/roberta-base-indonesian-1.5G](https://huggingface.co/cahya/roberta-base-indonesian-1.5G) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5420
- Accuracy: 0.9246

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3123        | 1.0   | 688  | 0.3496          | 0.8944   |
| 0.1888        | 2.0   | 1376 | 0.2877          | 0.9103   |
| 0.0981        | 3.0   | 2064 | 0.3936          | 0.9143   |
| 0.0529        | 4.0   | 2752 | 0.4431          | 0.9183   |
| 0.0419        | 5.0   | 3440 | 0.5350          | 0.9167   |
| 0.0121        | 6.0   | 4128 | 0.5420          | 0.9246   |
| 0.0116        | 7.0   | 4816 | 0.5920          | 0.9175   |
| 0.0042        | 8.0   | 5504 | 0.6440          | 0.9190   |
| 0.0013        | 9.0   | 6192 | 0.6460          | 0.9222   |
| 0.001         | 10.0  | 6880 | 0.6575          | 0.9230   |


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3