metadata

license: apache-2.0
tags:
  - image-classification
  - vision
  - generated_from_trainer
datasets:
  - beans
metrics:
  - accuracy
model-index:
  - name: vit-base-beans
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: beans
          type: beans
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9699248120300752

vit-base-beans

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

Loss: 0.1328
Accuracy: 0.9699

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 1337
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.49	1.0	65	0.9624	0.4050
0.2769	2.0	130	0.9850	0.1862
0.1441	3.0	195	0.9774	0.1554
0.1661	4.0	260	0.9774	0.1333
0.1754	5.0	325	0.9699	0.1328

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2