README.md

metadata

license: apache-2.0
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - cifar100
metrics:
  - accuracy
model-index:
  - name: vit-base-beans-demo-v5
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: Cifar100
          type: cifar100
          args: cifar100
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8985

vit-base-beans-demo-v5

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the Cifar100 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4420
• Accuracy: 0.8985

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.08	1.0	3125	0.6196	0.8262
0.3816	2.0	6250	0.5322	0.8555
0.1619	3.0	9375	0.4817	0.8765
0.0443	4.0	12500	0.4420	0.8985

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.1
• Tokenizers 0.12.1