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This model is a small timm/vit_base_patch16_224.orig_in21k_ft_in1k trained on svhn.

  • Test Accuracy: 0.9672326367547633
  • License: MIT

How to Get Started with the Model

Use the code below to get started with the model.

import timm
import torch
from torch import nn

model = timm.create_model("timm/vit_base_patch16_224.orig_in21k_ft_in1k",
pretrained=False)
model.head = nn.Linear(model.head.in_features, 10)
model.load_state_dict(
    torch.hub.load_state_dict_from_url(
        "https://huggingface.co/edadaltocg/vit_base_patch16_224_in21k_ft_svhn/resolve/main/pytorch_model.bin",
        map_location="cpu",
        file_name="vit_base_patch16_224_in21k_ft_svhn.pth",
    )
)

Training Data

Training data is svhn.

Training Hyperparameters

  • config: scripts/train_configs/ft_svhn.json

  • model: vit_base_patch16_224_in21k_ft_svhn

  • dataset: svhn

  • batch_size: 64

  • epochs: 10

  • validation_frequency: 1

  • seed: 1

  • criterion: CrossEntropyLoss

  • criterion_kwargs: {}

  • optimizer: SGD

  • lr: 0.01

  • optimizer_kwargs: {'momentum': 0.9, 'weight_decay': 0.0}

  • scheduler: CosineAnnealingLR

  • scheduler_kwargs: {'T_max': 10}

  • debug: False

Testing Data

Testing data is svhn.


This model card was created by Eduardo Dadalto.

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Dataset used to train edadaltocg/vit_base_patch16_224_in21k_ft_svhn

Evaluation results