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---
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
|