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--- |
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license: apache-2.0 |
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tags: |
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- image-classification |
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- generated_from_trainer |
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datasets: |
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- beans |
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widget: |
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- src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/healthy.jpeg |
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example_title: Healthy |
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- src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/angular_leaf_spot.jpeg |
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example_title: Angular Leaf Spot |
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- src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/bean_rust.jpeg |
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example_title: Bean Rust |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-beans |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: beans |
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type: beans |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9849624060150376 |
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- task: |
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type: image-classification |
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name: Image Classification |
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dataset: |
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name: beans |
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type: beans |
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config: default |
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split: test |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.96875 |
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verified: true |
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- name: Precision Macro |
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type: precision |
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value: 0.9716312056737588 |
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verified: true |
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- name: Precision Micro |
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type: precision |
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value: 0.96875 |
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verified: true |
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- name: Precision Weighted |
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type: precision |
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value: 0.9714095744680851 |
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verified: true |
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- name: Recall Macro |
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type: recall |
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value: 0.9689922480620154 |
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verified: true |
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- name: Recall Micro |
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type: recall |
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value: 0.96875 |
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verified: true |
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- name: Recall Weighted |
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type: recall |
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value: 0.96875 |
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verified: true |
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- name: F1 Macro |
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type: f1 |
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value: 0.9689250225835592 |
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verified: true |
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- name: F1 Micro |
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type: f1 |
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value: 0.96875 |
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verified: true |
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- name: F1 Weighted |
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type: f1 |
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value: 0.9686822493224932 |
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verified: true |
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- name: loss |
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type: loss |
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value: 0.1282731592655182 |
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verified: true |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vit-base-beans |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0505 |
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- Accuracy: 0.9850 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.1166 | 1.54 | 100 | 0.0764 | 0.9850 | |
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| 0.1607 | 3.08 | 200 | 0.2114 | 0.9398 | |
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| 0.0067 | 4.62 | 300 | 0.0692 | 0.9774 | |
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| 0.005 | 6.15 | 400 | 0.0944 | 0.9624 | |
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| 0.0043 | 7.69 | 500 | 0.0505 | 0.9850 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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