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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ - precision
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+ model-index:
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+ - name: swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9591516103692066
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+ - name: Precision
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+ type: precision
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+ value: 0.9627515459909033
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+ ---
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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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+
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+ # swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08
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+
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+ This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1210
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+ - Accuracy: 0.9592
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+ - F1 Score: 0.9600
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+ - Precision: 0.9628
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 100
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+ - eval_batch_size: 100
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 400
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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: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
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+ | 1.2882 | 0.99 | 19 | 0.5469 | 0.7962 | 0.7863 | 0.8077 |
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+ | 0.3491 | 1.97 | 38 | 0.3030 | 0.8861 | 0.8878 | 0.8981 |
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+ | 0.1791 | 2.96 | 57 | 0.2077 | 0.9211 | 0.9229 | 0.9307 |
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+ | 0.122 | 4.0 | 77 | 0.2007 | 0.9254 | 0.9272 | 0.9369 |
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+ | 0.0671 | 4.99 | 96 | 0.2073 | 0.9269 | 0.9294 | 0.9401 |
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+ | 0.0474 | 5.97 | 115 | 0.1384 | 0.9482 | 0.9494 | 0.9547 |
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+ | 0.032 | 6.96 | 134 | 0.1683 | 0.9430 | 0.9447 | 0.9511 |
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+ | 0.0225 | 8.0 | 154 | 0.1101 | 0.9650 | 0.9657 | 0.9671 |
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+ | 0.0193 | 8.99 | 173 | 0.1372 | 0.9533 | 0.9544 | 0.9585 |
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+ | 0.0193 | 9.87 | 190 | 0.1210 | 0.9592 | 0.9600 | 0.9628 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3