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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_05 |
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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: 0.9584282460136674 |
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- name: Precision |
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type: precision |
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value: 0.9575941658443274 |
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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_05 |
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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: 0.1136 |
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- Accuracy: 0.9584 |
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- F1 Score: 0.9562 |
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- Precision: 0.9576 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:| |
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| 1.2801 | 0.98 | 13 | 0.6953 | 0.7335 | 0.6819 | 0.7815 | |
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| 0.5928 | 1.96 | 26 | 0.3691 | 0.8440 | 0.8218 | 0.8629 | |
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| 0.3122 | 2.94 | 39 | 0.1664 | 0.9402 | 0.9377 | 0.9373 | |
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| 0.1513 | 4.0 | 53 | 0.1292 | 0.9493 | 0.9468 | 0.9467 | |
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| 0.1227 | 4.98 | 66 | 0.1030 | 0.9601 | 0.9577 | 0.9585 | |
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| 0.1201 | 5.96 | 79 | 0.1312 | 0.9522 | 0.9496 | 0.9508 | |
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| 0.0806 | 6.94 | 92 | 0.1306 | 0.9522 | 0.9494 | 0.9520 | |
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| 0.0645 | 8.0 | 106 | 0.1474 | 0.9482 | 0.9457 | 0.9490 | |
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| 0.0668 | 8.98 | 119 | 0.0947 | 0.9613 | 0.9589 | 0.9600 | |
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| 0.0577 | 9.81 | 130 | 0.1136 | 0.9584 | 0.9562 | 0.9576 | |
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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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