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resnet50_cifar10
edadaltocg/resnet50_cifar10
resnet50_cifar10 is a image classification model from edadaltocg. Use it when you need a label for an image. It is set up for timm. The card lists the license as mit.
This model is a small resnet50 trained on cifar10.
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Repo size
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At a glance
- Task
- Image Classification
- Library
- timm
- License
- mit
- Access
- Public
- Created
- Feb 19, 2023
- Updated
- Feb 19, 2023
- SHA
- 057f6b2e
Datasets
Model card
From the Hugging Face model README
Model Card for Model ID
This model is a small resnet50 trained on cifar10.
- Test Accuracy: 0.9465
- License: MIT
How to Get Started with the Model
Use the code below to get started with the model.
import detectors
import timm
model = timm.create_model("resnet50_cifar10", pretrained=True)
Training Data
Training data is cifar10.
Training Hyperparameters
-
config:
scripts/train_configs/cifar10.json -
model:
resnet50_cifar10 -
dataset:
cifar10 -
batch_size:
128 -
epochs:
300 -
validation_frequency:
5 -
seed:
1 -
criterion:
CrossEntropyLoss -
criterion_kwargs:
{} -
optimizer:
SGD -
lr:
0.1 -
optimizer_kwargs:
{'momentum': 0.9, 'weight_decay': 0.0005, 'nesterov': 'True'} -
scheduler:
ReduceLROnPlateau -
scheduler_kwargs:
{'factor': 0.1, 'patience': 3, 'threshold': 0.001, 'mode': 'max'} -
debug:
False
Testing Data
Testing data is cifar10.
This model card was created by Eduardo Dadalto.
- Task
- Image Classification
- Library
- timm
- License
- mit
- Languages
- en
- Created
- Feb 19, 2023
- Updated
- Feb 19, 2023