Edit model card

Model Card for Model ID

This model is a small resnet18 trained on cifar10.

  • Test Accuracy: 0.9498
  • 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_cifar10", pretrained=True)

Training Data

Training data is cifar10.

Training Hyperparameters

  • config: scripts/train_configs/cifar10.json

  • model: resnet18_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.

Downloads last month
193
Inference Examples
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.

Dataset used to train edadaltocg/resnet18_cifar10

Evaluation results