metadata
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
- f1
model-index:
- name: indobert-classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
args: smsa
metrics:
- name: Accuracy
type: accuracy
value: 0.9428571428571428
- name: F1
type: f1
value: 0.9428847892722086
indobert-classification
This model is a fine-tuned version of indobenchmark/indobert-base-p1 on the indonlu dataset. It achieves the following results on the evaluation set:
- Loss: 0.2296
- Accuracy: 0.9429
- F1: 0.9429
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2409 | 1.0 | 688 | 0.2098 | 0.9413 | 0.9414 |
| 0.1091 | 2.0 | 1376 | 0.2296 | 0.9429 | 0.9429 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6