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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-50 |
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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: resnet-50-plant-disease |
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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: 0.9285917496443812 |
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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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# resnet-50-plant-disease |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3609 |
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- Accuracy: 0.9286 |
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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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| 3.4023 | 1.0 | 158 | 3.2949 | 0.4071 | |
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| 1.9184 | 2.0 | 316 | 1.5580 | 0.7788 | |
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| 0.94 | 3.0 | 474 | 0.7401 | 0.8761 | |
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| 0.6491 | 4.0 | 633 | 0.4772 | 0.9118 | |
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| 0.5516 | 5.0 | 791 | 0.3857 | 0.9242 | |
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| 0.5164 | 5.99 | 948 | 0.3609 | 0.9286 | |
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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 2.16.0 |
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- Tokenizers 0.15.0 |
