metadata
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
model-index:
- name: indobert-base-uncased-finetuned-indonlu-smsa
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
args: smsa
metrics:
- name: Accuracy
type: accuracy
value: 0.9365079365079365
indobert-base-uncased-finetuned-indonlu-smsa
This model is a fine-tuned version of indolem/indobert-base-uncased on the indonlu dataset. It achieves the following results on the evaluation set:
- Loss: 0.2416
- Accuracy: 0.9365
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 | 0.6655 | 0.7206 |
| 0.7832 | 2.0 | 688 | 0.3297 | 0.8651 |
| 0.3331 | 3.0 | 1032 | 0.2184 | 0.9254 |
| 0.3331 | 4.0 | 1376 | 0.2057 | 0.9302 |
| 0.2053 | 5.0 | 1720 | 0.2105 | 0.9270 |
| 0.1408 | 6.0 | 2064 | 0.2036 | 0.9270 |
| 0.1408 | 7.0 | 2408 | 0.2416 | 0.9365 |
| 0.1044 | 8.0 | 2752 | 0.3145 | 0.9302 |
| 0.0637 | 9.0 | 3096 | 0.3095 | 0.9294 |
| 0.0637 | 10.0 | 3440 | 0.3354 | 0.9286 |
Framework versions
- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3