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.
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