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--- |
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license: other |
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base_model: google/mobilenet_v2_1.0_224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- A2H0H0R1/plant-disease |
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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-disease2 |
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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: 0.9638691322901849 |
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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-disease2 |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1510 |
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- Accuracy: 0.9639 |
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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: 5e-05 |
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- train_batch_size: 100 |
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- eval_batch_size: 100 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 400 |
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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: 6 |
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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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| 1.2171 | 1.0 | 158 | 1.0595 | 0.8188 | |
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| 0.4082 | 2.0 | 316 | 0.3154 | 0.9387 | |
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| 0.295 | 3.0 | 474 | 0.2191 | 0.9555 | |
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| 0.2266 | 4.0 | 633 | 0.1747 | 0.9595 | |
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| 0.2168 | 5.0 | 791 | 0.2135 | 0.9499 | |
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| 0.2091 | 5.99 | 948 | 0.1510 | 0.9639 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
