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--- |
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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-dmae-va-U |
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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-dmae-va-U |
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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: 0.0534 |
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- Accuracy: 0.9908 |
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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: 40 |
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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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| No log | 0.9 | 7 | 1.4319 | 0.2569 | |
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| 1.3911 | 1.94 | 15 | 1.2133 | 0.4771 | |
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| 1.3911 | 2.97 | 23 | 0.9487 | 0.6055 | |
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| 1.0766 | 4.0 | 31 | 0.6542 | 0.7156 | |
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| 0.6974 | 4.9 | 38 | 0.4644 | 0.8716 | |
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| 0.6974 | 5.94 | 46 | 0.3919 | 0.8716 | |
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| 0.421 | 6.97 | 54 | 0.3094 | 0.8716 | |
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| 0.2513 | 8.0 | 62 | 0.2334 | 0.8991 | |
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| 0.2513 | 8.9 | 69 | 0.1915 | 0.9174 | |
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| 0.1931 | 9.94 | 77 | 0.2431 | 0.8807 | |
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| 0.1757 | 10.97 | 85 | 0.1608 | 0.9450 | |
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| 0.1757 | 12.0 | 93 | 0.1424 | 0.9266 | |
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| 0.1442 | 12.9 | 100 | 0.1280 | 0.9450 | |
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| 0.1085 | 13.94 | 108 | 0.1055 | 0.9541 | |
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| 0.1085 | 14.97 | 116 | 0.1080 | 0.9541 | |
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| 0.1056 | 16.0 | 124 | 0.0997 | 0.9633 | |
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| 0.1056 | 16.9 | 131 | 0.1185 | 0.9633 | |
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| 0.0926 | 17.94 | 139 | 0.0773 | 0.9633 | |
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| 0.103 | 18.97 | 147 | 0.1279 | 0.9633 | |
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| 0.103 | 20.0 | 155 | 0.1043 | 0.9633 | |
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| 0.0938 | 20.9 | 162 | 0.0824 | 0.9817 | |
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| 0.0891 | 21.94 | 170 | 0.1449 | 0.9541 | |
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| 0.0891 | 22.97 | 178 | 0.1366 | 0.9633 | |
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| 0.0754 | 24.0 | 186 | 0.1148 | 0.9358 | |
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| 0.0882 | 24.9 | 193 | 0.1992 | 0.9358 | |
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| 0.0882 | 25.94 | 201 | 0.0743 | 0.9817 | |
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| 0.078 | 26.97 | 209 | 0.0668 | 0.9725 | |
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| 0.0666 | 28.0 | 217 | 0.0534 | 0.9908 | |
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| 0.0666 | 28.9 | 224 | 0.0499 | 0.9908 | |
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| 0.0514 | 29.94 | 232 | 0.0433 | 0.9725 | |
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| 0.062 | 30.97 | 240 | 0.0840 | 0.9633 | |
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| 0.062 | 32.0 | 248 | 0.0513 | 0.9725 | |
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| 0.0712 | 32.9 | 255 | 0.0482 | 0.9817 | |
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| 0.0712 | 33.94 | 263 | 0.0553 | 0.9817 | |
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| 0.0703 | 34.97 | 271 | 0.0602 | 0.9725 | |
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| 0.0553 | 36.0 | 279 | 0.0595 | 0.9725 | |
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| 0.0553 | 36.13 | 280 | 0.0595 | 0.9725 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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