Model Card for Model ID

This model is a small resnet34 trained on svhn.

  • Test Accuracy: 0.9626229256299939
  • 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_svhn", pretrained=True)

Training Data

Training data is svhn.

Training Hyperparameters

  • config: scripts/train_configs/svhn.json

  • model: resnet34_svhn

  • dataset: svhn

  • batch_size: 128

  • epochs: 300

  • validation_frequency: 5

  • seed: 1

  • criterion: CrossEntropyLoss

  • criterion_kwargs: {}

  • optimizer: SGD

  • lr: 0.01

  • optimizer_kwargs: {'momentum': 0.9, 'weight_decay': 0.0005}

  • scheduler: MultiStepLR

  • scheduler_kwargs: {'gamma': 0.1, 'milestones': [75, 100, 150, 225]}

  • debug: False

Testing Data

Testing data is svhn.


This model card was created by Eduardo Dadalto.

Downloads last month
7
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/resnet34_svhn

Evaluation results