---
tags:
- image-classification
- sign-language
- indonesian
library_name: pytorch
base_model: google/efficientnet-b3
language:
- id
metrics:
- accuracy
pipeline_tag: image-classification
---

# EfficientNet-B3 BISINDO Indonesian Sign Language Classifier

Trained on 9169 images with 26 classes (A-Z BISINDO (Bahasa Isyarat Indonesia) sign language).

## Usage
```python
model = models.efficientnet_b3(pretrained=False)
model.classifier = nn.Sequential(
    nn.Dropout(p=0.4),
    nn.Linear(1536, 512),
    nn.SiLU(),
    nn.Dropout(p=0.3),
    nn.Linear(512, 26)
)
model.load_state_dict(torch.load('efficientnet_bisindo_sign_language.pth'))
```

## Training Result
| Epoch | Train Loss | Train Acc | Val Loss | Val Acc |
|-------|------------|-----------|----------|---------|
| 1     | 1.5356     | 0.7389    | 1.0504   | 0.9106  |
| 2     | 1.0970     | 0.8798    | 0.9385   | 0.9248  |
| 3     | 1.0251     | 0.8945    | 0.8828   | 0.9438  |
| 4     | 0.9710     | 0.9177    | 0.8689   | 0.9477  |
| 5     | 0.9382     | 0.9256    | 0.8370   | 0.9597  |
| 6     | 0.9161     | 0.9365    | 0.8222   | 0.9656  |
| 7     | 0.9052     | 0.9393    | 0.8133   | 0.9651  |
| 8     | 0.8904     | 0.9464    | 0.8094   | 0.9635  |
| 9     | 0.8756     | 0.9460    | 0.8023   | 0.9738  |
| 10    | 0.8656     | 0.9521    | 0.7939   | 0.9744  |
| 11    | 0.8609     | 0.9560    | 0.7836   | 0.9749  |
| 12    | 0.8544     | 0.9545    | 0.7876   | 0.9755  |
| 13    | 0.8396     | 0.9654    | 0.7929   | 0.9755  |
| 14    | 0.8415     | 0.9628    | 0.7776   | 0.9798  |
| 15    | 0.8333     | 0.9654    | 0.7827   | 0.9722  |
| 16    | 0.8286     | 0.9676    | 0.7695   | 0.9815  |
| 17    | 0.8235     | 0.9695    | 0.7761   | 0.9853  |
| 18    | 0.8155     | 0.9715    | 0.7714   | 0.9820  |
| 19    | 0.8151     | 0.9748    | 0.7589   | 0.9826  |
| 20    | 0.8139     | 0.9730    | 0.7756   | 0.9776  |
| 21    | 0.8018     | 0.9791    | 0.7613   | 0.9847  |
| 22    | 0.7942     | 0.9789    | 0.7475   | 0.9869  |
| 23    | 0.7859     | 0.9823    | 0.7458   | 0.9864  |
| 24    | 0.7871     | 0.9802    | 0.7538   | 0.9869  |
| 25    | 0.7880     | 0.9810    | 0.7525   | 0.9880  |