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---
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
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