README.md

metadata

language: en
license: mit
library_name: timm
tags:
  - image-classification
  - timm/vit_base_patch16_224.orig_in21k_ft_in1k
  - cifar10
datasets: cifar10
metrics:
  - accuracy
model-index:
  - name: vit_base_patch16_224_in21k_ft_cifar10
    results:
      - task:
          type: image-classification
        dataset:
          name: CIFAR-10
          type: cifar10
        metrics:
          - type: accuracy
            value: 0.9896

Model Card for Model ID

This model is a small timm/vit_base_patch16_224.orig_in21k_ft_in1k trained on cifar10.

• Test Accuracy: 0.9896
• 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_cifar10/resolve/main/pytorch_model.bin",
        map_location="cpu",
        file_name="vit_base_patch16_224_in21k_ft_cifar10.pth",
    )
)

Training Data

Training data is cifar10.

Training Hyperparameters

• config: scripts/train_configs/ft_cifar10.json

• model: vit_base_patch16_224_in21k_ft_cifar10

• dataset: cifar10

• 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 cifar10.

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This model card was created by Eduardo Dadalto.