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Brain-Tumor-Classification

Image Classification
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vit
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  1. README.md +23 -15
  2. model.safetensors +1 -1
  3. runs/Mar06_07-36-46_65f3a70606cc/events.out.tfevents.1709710607.65f3a70606cc.34.1 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.1728
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- - Accuracy: 0.9544
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 4e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 32
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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: 8
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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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- | 1.0978 | 0.99 | 52 | 0.6856 | 0.7602 |
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- | 0.5021 | 2.0 | 105 | 0.3709 | 0.9041 |
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- | 0.3131 | 2.99 | 157 | 0.2680 | 0.9281 |
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- | 0.226 | 4.0 | 210 | 0.2189 | 0.9424 |
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- | 0.1682 | 4.99 | 262 | 0.2105 | 0.9376 |
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- | 0.155 | 6.0 | 315 | 0.1873 | 0.9448 |
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- | 0.127 | 6.99 | 367 | 0.1635 | 0.9568 |
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- | 0.1227 | 7.92 | 416 | 0.1728 | 0.9544 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 0.1972
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+ - Accuracy: 0.9472
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 4e-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: 16
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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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+ | 1.3603 | 0.98 | 13 | 1.1922 | 0.5444 |
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+ | 1.0671 | 1.96 | 26 | 0.8661 | 0.7026 |
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+ | 0.7531 | 2.94 | 39 | 0.6021 | 0.8393 |
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+ | 0.4923 | 4.0 | 53 | 0.4488 | 0.8849 |
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+ | 0.3921 | 4.98 | 66 | 0.3764 | 0.9113 |
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+ | 0.3284 | 5.96 | 79 | 0.3130 | 0.9233 |
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+ | 0.3001 | 6.94 | 92 | 0.3303 | 0.9041 |
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+ | 0.2354 | 8.0 | 106 | 0.2644 | 0.9305 |
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+ | 0.2283 | 8.98 | 119 | 0.2602 | 0.9400 |
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+ | 0.2131 | 9.96 | 132 | 0.2318 | 0.9472 |
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+ | 0.2029 | 10.94 | 145 | 0.2197 | 0.9448 |
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+ | 0.1663 | 12.0 | 159 | 0.2352 | 0.9305 |
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+ | 0.1716 | 12.98 | 172 | 0.2014 | 0.9544 |
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+ | 0.1609 | 13.96 | 185 | 0.2081 | 0.9472 |
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+ | 0.1633 | 14.94 | 198 | 0.2030 | 0.9472 |
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+ | 0.1424 | 15.7 | 208 | 0.1972 | 0.9472 |
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  ### Framework versions
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