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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: 0.7145092460881934 |
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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 image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3799 |
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- Accuracy: 0.7145 |
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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: 0.0003 |
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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: 0.1 |
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- num_epochs: 5 |
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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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| 2.3889 | 1.0 | 248 | 2.1952 | 0.6310 | |
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| 1.8202 | 2.0 | 496 | 1.6363 | 0.7013 | |
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| 1.6266 | 3.0 | 744 | 1.6291 | 0.6343 | |
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| 1.5566 | 4.0 | 992 | 1.3514 | 0.7129 | |
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| 1.5507 | 5.0 | 1240 | 1.3799 | 0.7145 | |
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### Framework versions |
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- Transformers 4.26.1 |
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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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