README.md

metadata

language: en
license: mit
library_name: timm
tags:
  - image-classification
  - resnet34
  - cifar10
datasets: cifar10
metrics:
  - accuracy
model-index:
  - name: resnet34_cifar10
    results:
      - task:
          type: image-classification
        dataset:
          name: CIFAR-10
          type: cifar10
        metrics:
          - type: accuracy
            value: 0.954

Model Card for Model ID

This model is a small resnet34 trained on cifar10.

• Test Accuracy: 0.954
• 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("resnet34_cifar10", pretrained=True)

Training Data

Training data is cifar10.

Training Hyperparameters

• config: scripts/train_configs/cifar10.json

• model: resnet34_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.

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This model card was created by Eduardo Dadalto.