Model Card for Model ID
This model is a small resnet18 trained on cifar100.
- Test Accuracy: 0.7926
- 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("resnet18_cifar100", pretrained=True)
Training Data
Training data is cifar100.
Training Hyperparameters
config:
scripts/train_configs/cifar100.json
model:
resnet18_cifar100
dataset:
cifar100
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}
scheduler:
CosineAnnealingLR
scheduler_kwargs:
{'T_max': 280}
debug:
False
Testing Data
Testing data is cifar100.
This model card was created by Eduardo Dadalto.
- Downloads last month
- 237
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.