| --- |
| license: apache-2.0 |
| base_model: microsoft/resnet-50 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - A2H0H0R1/plant-disease |
| metrics: |
| - accuracy |
| model-index: |
| - name: resnet-50-plant-disease |
| 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: 0.9285917496443812 |
| --- |
| |
| <!-- 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. --> |
|
|
| # resnet-50-plant-disease |
|
|
| This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3609 |
| - Accuracy: 0.9286 |
|
|
| ## 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: 100 |
| - eval_batch_size: 100 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 400 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 6 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 3.4023 | 1.0 | 158 | 3.2949 | 0.4071 | |
| | 1.9184 | 2.0 | 316 | 1.5580 | 0.7788 | |
| | 0.94 | 3.0 | 474 | 0.7401 | 0.8761 | |
| | 0.6491 | 4.0 | 633 | 0.4772 | 0.9118 | |
| | 0.5516 | 5.0 | 791 | 0.3857 | 0.9242 | |
| | 0.5164 | 5.99 | 948 | 0.3609 | 0.9286 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.0 |
| - Tokenizers 0.15.0 |
