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--- |
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license: apache-2.0 |
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base_model: gianlab/swin-tiny-patch4-window7-224-finetuned-plantdisease |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: CGIAR-Crop-disease |
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results: [] |
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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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# CGIAR-Crop-disease |
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This model is a fine-tuned version of [gianlab/swin-tiny-patch4-window7-224-finetuned-plantdisease](https://huggingface.co/gianlab/swin-tiny-patch4-window7-224-finetuned-plantdisease) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7668 |
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- Accuracy: 0.6726 |
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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: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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_steps: 50 |
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- num_epochs: 20 |
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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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| 1.047 | 1.0 | 652 | 0.9302 | 0.5817 | |
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| 0.899 | 2.0 | 1304 | 0.8669 | 0.6285 | |
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| 0.8656 | 3.0 | 1956 | 0.8434 | 0.6385 | |
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| 0.8514 | 4.0 | 2608 | 0.8421 | 0.6277 | |
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| 0.8395 | 5.0 | 3260 | 0.8275 | 0.6506 | |
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| 0.832 | 6.0 | 3912 | 0.8444 | 0.6415 | |
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| 0.8065 | 7.0 | 4564 | 0.8204 | 0.6494 | |
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| 0.8031 | 8.0 | 5216 | 0.8271 | 0.6438 | |
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| 0.7954 | 9.0 | 5868 | 0.8025 | 0.6632 | |
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| 0.7939 | 10.0 | 6520 | 0.7917 | 0.6592 | |
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| 0.7893 | 11.0 | 7172 | 0.8043 | 0.6515 | |
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| 0.7731 | 12.0 | 7824 | 0.7878 | 0.6695 | |
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| 0.7759 | 13.0 | 8476 | 0.7806 | 0.6657 | |
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| 0.7676 | 14.0 | 9128 | 0.7816 | 0.6653 | |
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| 0.7605 | 15.0 | 9780 | 0.7882 | 0.6550 | |
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| 0.7566 | 16.0 | 10432 | 0.7881 | 0.6548 | |
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| 0.7554 | 17.0 | 11084 | 0.7824 | 0.6619 | |
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| 0.7384 | 18.0 | 11736 | 0.7668 | 0.6726 | |
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| 0.7442 | 19.0 | 12388 | 0.7830 | 0.6594 | |
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| 0.7296 | 20.0 | 13040 | 0.7709 | 0.6667 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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