metadata

license: apache-2.0
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - beans
metrics:
  - accuracy
widget:
  - src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/healthy.jpeg
    example_title: Healthy
  - src: >-
      https://huggingface.co/nateraw/vit-base-beans/resolve/main/angular_leaf_spot.jpeg
    example_title: Angular Leaf Spot
  - src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/bean_rust.jpeg
    example_title: Bean Rust
model-index:
  - name: vit-base-beans
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: beans
          type: beans
          args: default
        metrics:
          - type: accuracy
            value: 0.9849624060150376
            name: Accuracy
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: beans
          type: beans
          config: default
          split: test
        metrics:
          - type: accuracy
            value: 0.96875
            name: Accuracy
            verified: true
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          - type: precision
            value: 0.9716312056737588
            name: Precision Macro
            verified: true
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          - type: precision
            value: 0.96875
            name: Precision Micro
            verified: true
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          - type: precision
            value: 0.9714095744680851
            name: Precision Weighted
            verified: true
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          - type: recall
            value: 0.9689922480620154
            name: Recall Macro
            verified: true
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          - type: recall
            value: 0.96875
            name: Recall Micro
            verified: true
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          - type: recall
            value: 0.96875
            name: Recall Weighted
            verified: true
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          - type: f1
            value: 0.9689250225835592
            name: F1 Macro
            verified: true
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          - type: f1
            value: 0.96875
            name: F1 Micro
            verified: true
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          - type: f1
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          - type: loss
            value: 0.1282731592655182
            name: loss
            verified: true
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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: 0.0505
Accuracy: 0.9850

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: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1166	1.54	100	0.0764	0.9850
0.1607	3.08	200	0.2114	0.9398
0.0067	4.62	300	0.0692	0.9774
0.005	6.15	400	0.0944	0.9624
0.0043	7.69	500	0.0505	0.9850

Framework versions

Transformers 4.16.2
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.11.0