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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 |
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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: 0.9396355353075171 |
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- name: Precision |
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type: precision |
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value: 0.9408448811333167 |
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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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# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final |
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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: 0.1577 |
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- Accuracy: 0.9396 |
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- F1 Score: 0.9385 |
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- Precision: 0.9408 |
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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: 1e-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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:| |
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| 1.1562 | 0.99 | 41 | 1.1378 | 0.6378 | 0.6191 | 0.6537 | |
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| 0.4878 | 1.99 | 82 | 0.6477 | 0.7591 | 0.7499 | 0.7874 | |
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| 0.2623 | 2.98 | 123 | 0.4410 | 0.8337 | 0.8311 | 0.8488 | |
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| 0.1985 | 4.0 | 165 | 0.4660 | 0.8144 | 0.8115 | 0.8455 | |
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| 0.1736 | 4.99 | 206 | 0.3230 | 0.8776 | 0.8760 | 0.8894 | |
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| 0.124 | 5.99 | 247 | 0.2684 | 0.9026 | 0.9014 | 0.9090 | |
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| 0.1278 | 6.98 | 288 | 0.2210 | 0.9180 | 0.9166 | 0.9210 | |
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| 0.0959 | 8.0 | 330 | 0.2151 | 0.9208 | 0.9195 | 0.9260 | |
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| 0.0849 | 8.99 | 371 | 0.2154 | 0.9220 | 0.9205 | 0.9291 | |
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| 0.0805 | 9.99 | 412 | 0.2112 | 0.9191 | 0.9179 | 0.9251 | |
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| 0.0682 | 10.98 | 453 | 0.1563 | 0.9385 | 0.9369 | 0.9402 | |
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| 0.0624 | 12.0 | 495 | 0.1577 | 0.9396 | 0.9385 | 0.9408 | |
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| 0.0415 | 12.99 | 536 | 0.1836 | 0.9305 | 0.9294 | 0.9332 | |
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| 0.0465 | 13.99 | 577 | 0.2145 | 0.9203 | 0.9192 | 0.9252 | |
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| 0.056 | 14.98 | 618 | 0.1710 | 0.9339 | 0.9325 | 0.9369 | |
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| 0.0545 | 16.0 | 660 | 0.2094 | 0.9248 | 0.9236 | 0.9298 | |
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| 0.0591 | 16.99 | 701 | 0.1752 | 0.9317 | 0.9303 | 0.9341 | |
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| 0.0512 | 17.99 | 742 | 0.1781 | 0.9311 | 0.9297 | 0.9342 | |
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| 0.0424 | 18.98 | 783 | 0.1873 | 0.9305 | 0.9293 | 0.9338 | |
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| 0.0438 | 19.88 | 820 | 0.1955 | 0.9265 | 0.9252 | 0.9307 | |
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### Framework versions |
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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 |
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