| --- |
| library_name: transformers |
| license: other |
| base_model: google/mobilenet_v2_1.0_224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: mobilenet_v2_1.0_224-finetuned-plantdisease |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9781976744186046 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # mobilenet_v2_1.0_224-finetuned-plantdisease |
| |
| 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 imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0841 |
| - Accuracy: 0.9782 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-------:|:----:|:---------------:|:--------:| |
| | 1.7982 | 0.9983 | 145 | 1.9825 | 0.4036 | |
| | 0.6137 | 1.9966 | 290 | 1.1130 | 0.6415 | |
| | 0.4176 | 2.9948 | 435 | 0.4887 | 0.8469 | |
| | 0.3107 | 4.0 | 581 | 0.3414 | 0.8944 | |
| | 0.2255 | 4.9983 | 726 | 0.2732 | 0.9123 | |
| | 0.1833 | 5.9966 | 871 | 0.7462 | 0.7582 | |
| | 0.2062 | 6.9948 | 1016 | 0.3771 | 0.8803 | |
| | 0.1657 | 8.0 | 1162 | 0.4718 | 0.8542 | |
| | 0.1427 | 8.9983 | 1307 | 0.4902 | 0.8474 | |
| | 0.1598 | 9.9966 | 1452 | 0.2229 | 0.9273 | |
| | 0.1504 | 10.9948 | 1597 | 0.3021 | 0.8973 | |
| | 0.1456 | 12.0 | 1743 | 0.2422 | 0.9225 | |
| | 0.119 | 12.9983 | 1888 | 0.2836 | 0.9021 | |
| | 0.114 | 13.9966 | 2033 | 0.2038 | 0.9293 | |
| | 0.1378 | 14.9948 | 2178 | 0.2173 | 0.9239 | |
| | 0.1249 | 16.0 | 2324 | 0.2467 | 0.9186 | |
| | 0.1504 | 16.9983 | 2469 | 0.2322 | 0.9254 | |
| | 0.0972 | 17.9966 | 2614 | 0.0841 | 0.9782 | |
| | 0.1293 | 18.9948 | 2759 | 0.1512 | 0.9467 | |
| | 0.1072 | 19.9656 | 2900 | 0.1663 | 0.9448 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.2 |
| - Pytorch 2.5.0+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.19.1 |
| |
