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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: Crop_Disease_model_1 |
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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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# Crop_Disease_model_1 |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2482 |
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- Accuracy: 0.7 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 18 |
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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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| 2.974 | 0.9787 | 23 | 2.9288 | 0.1573 | |
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| 2.8301 | 2.0 | 47 | 2.6713 | 0.5173 | |
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| 2.3995 | 2.9787 | 70 | 2.3223 | 0.5707 | |
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| 2.112 | 4.0 | 94 | 2.0321 | 0.604 | |
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| 1.8965 | 4.9787 | 117 | 1.8377 | 0.6133 | |
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| 1.6807 | 6.0 | 141 | 1.6895 | 0.6307 | |
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| 1.4942 | 6.9787 | 164 | 1.5807 | 0.6693 | |
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| 1.3849 | 8.0 | 188 | 1.5080 | 0.664 | |
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| 1.2975 | 8.9787 | 211 | 1.4605 | 0.6613 | |
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| 1.1747 | 10.0 | 235 | 1.3888 | 0.692 | |
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| 1.1457 | 10.9787 | 258 | 1.3622 | 0.692 | |
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| 1.0602 | 12.0 | 282 | 1.3318 | 0.6893 | |
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| 1.0296 | 12.9787 | 305 | 1.2968 | 0.7133 | |
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| 0.9556 | 14.0 | 329 | 1.2999 | 0.676 | |
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| 0.9317 | 14.9787 | 352 | 1.2625 | 0.7053 | |
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| 0.9134 | 16.0 | 376 | 1.2656 | 0.696 | |
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| 0.914 | 16.9787 | 399 | 1.2593 | 0.7013 | |
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| 0.9013 | 17.6170 | 414 | 1.2482 | 0.7 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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