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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: google/vit-base-patch16-224 |
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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: vit-base-patch16-224_rice-leaf-disease-augmented-v2_fft |
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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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# vit-base-patch16-224_rice-leaf-disease-augmented-v2_fft |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3621 |
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- Accuracy: 0.9226 |
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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: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 19 |
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- mixed_precision_training: Native AMP |
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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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| 1.9482 | 1.0 | 125 | 1.5012 | 0.5685 | |
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| 0.9894 | 2.0 | 250 | 0.6444 | 0.7976 | |
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| 0.3321 | 3.0 | 375 | 0.3859 | 0.8958 | |
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| 0.1115 | 4.0 | 500 | 0.3081 | 0.9107 | |
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| 0.0387 | 5.0 | 625 | 0.2980 | 0.9137 | |
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| 0.0204 | 6.0 | 750 | 0.2936 | 0.9137 | |
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| 0.0169 | 7.0 | 875 | 0.2953 | 0.9196 | |
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| 0.0078 | 8.0 | 1000 | 0.3067 | 0.9226 | |
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| 0.0034 | 9.0 | 1125 | 0.3087 | 0.9286 | |
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| 0.0025 | 10.0 | 1250 | 0.3139 | 0.9196 | |
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| 0.0023 | 11.0 | 1375 | 0.3142 | 0.9196 | |
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| 0.0019 | 12.0 | 1500 | 0.3288 | 0.9196 | |
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| 0.0013 | 13.0 | 1625 | 0.3359 | 0.9196 | |
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| 0.001 | 14.0 | 1750 | 0.3413 | 0.9226 | |
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| 0.0009 | 15.0 | 1875 | 0.3425 | 0.9226 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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