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--- |
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license: other |
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tags: |
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- generated_from_trainer |
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datasets: |
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- image_folder |
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metrics: |
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- accuracy |
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model-index: |
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- name: mobilenet_v2_1.0_224-plant-disease-identification |
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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: image_folder |
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type: image_folder |
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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: 0.7857752489331437 |
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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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# mobilenet_v2_1.0_224-plant-disease-identification |
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This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the [Kaggle version](https://www.kaggle.com/datasets/vipoooool/new-plant-diseases-dataset) of the [Plant Village dataset](https://github.com/spMohanty/PlantVillage-Dataset). |
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It achieves the following results on the evaluation set: |
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- Cross Entropy Loss: 1.0461 |
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- Accuracy: 0.7858 |
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Will be further training it (such as finding optimal hyperparameters) better to achieve much better accuracy. |
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## Intended uses & limitations |
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For identifying common diseases in crops and assessing plant health. |
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## Training and evaluation data |
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The plant village dataset consists of 38 classes of diseases in common crops (including healthy/normal crops). |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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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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- lr_scheduler_warmup_ratio: 0.15 |
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- num_epochs: 8 |
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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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| 2.9265 | 1.0 | 248 | 2.7159 | 0.4703 | |
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| 1.9734 | 2.0 | 496 | 1.7668 | 0.6649 | |
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| 1.7206 | 3.0 | 744 | 1.4012 | 0.7206 | |
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| 1.6406 | 4.0 | 992 | 1.2514 | 0.7644 | |
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| 1.6075 | 5.0 | 1240 | 1.2934 | 0.7094 | |
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| 1.5932 | 6.0 | 1488 | 1.2093 | 0.7257 | |
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| 1.5203 | 7.0 | 1736 | 1.0461 | 0.7858 | |
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| 1.5076 | 8.0 | 1984 | 1.0580 | 0.7848 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 1.13.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.2 |
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