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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/swin-base-patch4-window7-224 |
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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: swin-base-patch4-window7-224_rice-leaf-disease-augmented_fft_012825 |
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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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# swin-base-patch4-window7-224_rice-leaf-disease-augmented_fft_012825 |
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This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0472 |
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- Accuracy: 0.988 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:| |
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| 1.5476 | 1.0 | 250 | 0.789 | 0.5917 | |
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| 0.3353 | 2.0 | 500 | 0.9575 | 0.1408 | |
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| 0.0827 | 3.0 | 750 | 0.985 | 0.0427 | |
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| 0.027 | 4.0 | 1000 | 0.9885 | 0.0344 | |
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| 0.0095 | 5.0 | 1250 | 0.9925 | 0.0188 | |
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| 0.0076 | 6.0 | 1500 | 0.995 | 0.0119 | |
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| 0.003 | 7.0 | 1750 | 0.9955 | 0.0090 | |
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| 0.0023 | 8.0 | 2000 | 0.9955 | 0.0163 | |
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| 0.0012 | 9.0 | 2250 | 0.992 | 0.0218 | |
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| 0.0017 | 10.0 | 2500 | 0.996 | 0.0100 | |
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| 0.0044 | 11.0 | 2750 | 0.9955 | 0.0236 | |
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| 0.0048 | 12.0 | 3000 | 0.9925 | 0.0249 | |
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| 0.0023 | 13.0 | 3250 | 0.9955 | 0.0182 | |
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| 0.0032 | 14.0 | 3500 | 0.994 | 0.0198 | |
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| 0.0017 | 15.0 | 3750 | 0.988 | 0.0472 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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