ModelPrésentéExterne

CIFAR10 Custom Cnn

Model ini adalah arsitektur Convolutional Neural Network (CNN) kustom yang dilatih dari awal pada dataset CIFAR-10 untuk tugas klasifikasi gambar menjadi 10 kelas berbeda.

Sourcehuggingface.co/HBEKS/CIFAR10-custom-cnn/tree/4cebcf21d989fc112cc2bc9f01598f69a85381c3

TypeOtherVersionRevision 4cebcf2CClasse

Source du modèle

Type: Other
Taille du fichier: 2,23 MB
Version: vRevision 4cebcf2
Mis à jour: 16 sept. 2026
Téléchargements: 6
Source: Hugging Face

Description de la source

Custom CNN for CIFAR-10

Model Description

Model ini adalah arsitektur Convolutional Neural Network (CNN) kustom yang dilatih dari awal pada dataset CIFAR-10 untuk tugas klasifikasi gambar menjadi 10 kelas berbeda.

Arsitektur model terdiri dari:

5 convolutional blocks dengan Batch Normalization
Global Average Pooling
2 Fully Connected layers dengan Dropout (0.5 dan 0.3)

10 Kelas yang Dikenali

ID	Kelas
0	airplane
1	automobile
2	bird
3	cat
4	deer
5	dog
6	frog
7	horse
8	ship
9	truck

Performa Model

Set	Akurasi
Train	82.75%
Validation	80.73%
Test	84.78%

Detail Training

Parameter	Nilai
Dataset	CIFAR-10 (50,000 training, 10,000 test)
Epochs	50 (dengan early stopping, patience=8)
Batch Size	64
Optimizer	Adam (lr=0.001, weight_decay=5e-4)
Loss Function	CrossEntropyLoss
Learning Rate Scheduler	ReduceLROnPlateau (patience=3, factor=0.5)
Best Model Epoch	Epoch 49 (Val Acc: 80.73%)

Data Augmentasi

RandomHorizontalFlip (p=0.5)
RandomRotation (20 derajat)
ColorJitter (brightness=0.3, contrast=0.3, saturation=0.3)
RandomAffine (translate=0.15)

Hasil Pengujian

Metrik	Nilai
Test Accuracy	84.78%
Correct Predictions	8,478 / 10,000
Test Loss	0.4654

Penulis

Nama: [Daniel Wuliutomo]
Batch: batch-11

Sources

1 source

Hugging FacePrincipalVersion 4cebcf21d989fc112cc2bc9f01598f69a85381c3

huggingface.co/HBEKS/CIFAR10-custom-cnn/tree/4cebcf21d989fc112cc2bc9f01598f69a85381c3

Vérifié 1 sept.

Artefacts du modèle

1 artefact

pytorch_model.bin

bin · 2,23 MB · SHA-256 13c8d2e85de8…0743 · Hugging Face

Download file

Extraits de sources

2 extraits

Readme1 sept.huggingface.co/HBEKS/CIFAR10-custom-cnn

--- tags: - image-classification - computer-vision - pytorch - cifar10 datasets: - cifar10 metrics: - accuracy license: mit pipeline_tag: image-segmentation --- # Custom CNN for CIFAR-10 ## Model Description Model ini adalah arsitektur **Convolutional Neural Network (CNN) kustom** yang dilatih dari awal pada dataset **CIFAR-10** untuk tugas klasifikasi gambar menjadi 10 kelas berbeda. Arsitektur model terdiri dari: - 5 convolutional blocks dengan Batch Normalization - Global Average Pooling - 2 Fully Connected layers dengan Dropout (0.5 dan 0.3) ## 10 Kelas yang Dikenali | ID | Kelas | |----|-------| | 0 | airplane | | 1 | automobile | | 2 | bird | | 3 | cat | | 4 | deer | | 5 | dog | | 6 | frog | | 7 | horse | | 8 | ship | | 9 | truck | ## Performa Model | Set | Akurasi | |-----|---------| | Train | 82.75% | | Validation | 80.73% | | **Test** | **84.78%** | ## Detail Training | Parameter | Nilai | |-----------|-------| | **Dataset** | CIFAR-10 (50,000 training, 10,000 test) | | **Epochs** | 50 (dengan early stopping, patience=8) | | **Batch Size** | 64 | | **Optimizer** | Adam (lr=0.001, weight_decay=5e-4) | | **Loss Function** | CrossEntropyLoss | | **Learning Rate Scheduler** | ReduceLROnPlateau (patience=3, factor=0.5) | | **Best Model Epoch** | Epoch 49 (Val Acc: 80.73%) | ### Data Augmentasi - RandomHorizontalFlip (p=0.5) - RandomRotation (20 derajat) - ColorJitter (brightness=0.3, contrast=0.3, saturation=0.3) - RandomAffine (translate=0.15) ## Hasil Pengujian | Metrik | Nilai | |--------|-------| | **Test Accuracy** | **84.78%** | | **Correct Predictions** | 8,478 / 10,000 | | **Test Loss** | 0.4654 | ## Penulis - **Nama:** [Daniel Wuliutomo] - **Batch:** batch-11

Note1 sept.huggingface.co/HBEKS/CIFAR10-custom-cnn

Source context: 6 downloads · 0 likes · Pipeline image-segmentation · Repo HBEKS/CIFAR10-custom-cnn