metadata

license: apache-2.0
tags:
  - image-classification
  - 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: 0.9924812030075187

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: 0.0226
Accuracy: 0.9925

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: 8
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
0.3365	0.38	50	0.2455	0.9323
0.1728	0.77	100	0.1544	0.9549
0.1519	1.15	150	0.1072	0.9624
0.0209	1.54	200	0.1594	0.9624
0.0206	1.92	250	0.0913	0.9699
0.0135	2.31	300	0.1488	0.9624
0.0079	2.69	350	0.0226	0.9925
0.0074	3.08	400	0.0582	0.9925
0.0064	3.46	450	0.0984	0.9774
0.0061	3.85	500	0.1151	0.9699

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu117
Datasets 2.11.0
Tokenizers 0.13.3