edadaltocg's picture
Update README.md
af39f3c
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.


This model card was created by Eduardo Dadalto.