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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: Rice-Plant-Disease-Detection-Model |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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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: 0.8958333333333334 |
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- name: F1 |
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type: f1 |
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value: 0.8965189410560187 |
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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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# Rice-Plant-Disease-Detection-Model |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2929 |
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- Accuracy: 0.8958 |
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- F1: 0.8965 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.5517 | 1.0 | 18 | 0.5222 | 0.875 | 0.8754 | |
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| 0.2996 | 2.0 | 36 | 0.3833 | 0.8542 | 0.8564 | |
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| 0.1529 | 3.0 | 54 | 0.3152 | 0.875 | 0.8763 | |
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| 0.0843 | 4.0 | 72 | 0.2929 | 0.8958 | 0.8965 | |
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| 0.0549 | 5.0 | 90 | 0.2756 | 0.875 | 0.8754 | |
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| 0.0402 | 6.0 | 108 | 0.2765 | 0.875 | 0.8754 | |
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| 0.0327 | 7.0 | 126 | 0.2875 | 0.875 | 0.8754 | |
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| 0.0277 | 8.0 | 144 | 0.2938 | 0.875 | 0.8754 | |
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| 0.0244 | 9.0 | 162 | 0.2992 | 0.875 | 0.8754 | |
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| 0.0222 | 10.0 | 180 | 0.2996 | 0.8958 | 0.8960 | |
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| 0.0203 | 11.0 | 198 | 0.3052 | 0.8958 | 0.8960 | |
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| 0.019 | 12.0 | 216 | 0.3087 | 0.8958 | 0.8960 | |
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| 0.018 | 13.0 | 234 | 0.3143 | 0.8958 | 0.8960 | |
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| 0.0171 | 14.0 | 252 | 0.3206 | 0.8958 | 0.8960 | |
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| 0.0164 | 15.0 | 270 | 0.3227 | 0.8958 | 0.8960 | |
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| 0.0158 | 16.0 | 288 | 0.3250 | 0.8958 | 0.8960 | |
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| 0.0155 | 17.0 | 306 | 0.3257 | 0.8958 | 0.8960 | |
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| 0.0152 | 18.0 | 324 | 0.3264 | 0.8958 | 0.8960 | |
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| 0.015 | 19.0 | 342 | 0.3276 | 0.8958 | 0.8960 | |
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| 0.0149 | 20.0 | 360 | 0.3275 | 0.8958 | 0.8960 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.1.0+cpu |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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