metadata
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
model-index:
- name: bert-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: 0.9373015873015873
language: id
widget:
- text: Saya mengapresiasi usaha anda
bert-base-indonesian-1.5G-finetuned-wnli
This model is a fine-tuned version of cahya/bert-base-indonesian-1.5G on the indonlu dataset. It achieves the following results on the evaluation set:
- Loss: 0.3390
- Accuracy: 0.9373
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 |
---|---|---|---|---|
0.2864 | 1.0 | 688 | 0.2154 | 0.9286 |
0.1648 | 2.0 | 1376 | 0.2238 | 0.9357 |
0.0759 | 3.0 | 2064 | 0.3351 | 0.9365 |
0.044 | 4.0 | 2752 | 0.3390 | 0.9373 |
0.0308 | 5.0 | 3440 | 0.4346 | 0.9365 |
0.0113 | 6.0 | 4128 | 0.4708 | 0.9365 |
0.006 | 7.0 | 4816 | 0.5533 | 0.9325 |
0.0047 | 8.0 | 5504 | 0.5888 | 0.9310 |
0.0001 | 9.0 | 6192 | 0.5961 | 0.9333 |
0.0 | 10.0 | 6880 | 0.5992 | 0.9357 |
Framework versions
- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3