Brain-Tumor-Detection

ShimaGh/Brain-Tumor-Detection

Brain-Tumor-Detection is a image classification model from ShimaGh. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

Repo makeup

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.safetensors347 MB · 100%

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How the weights are stored.

F3286.7M · 100%

Base models

microsoft/swin-base-patch4-window7-224

Datasets

imagefolder

Spaces

APB37/brain-tumor-detection-demo

Model card

From the Hugging Face model README

Brain-Tumor-Detection

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0946
Accuracy: 0.9804

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.92	3	0.4395	0.6667
No log	1.85	6	0.2817	0.9020
No log	2.77	9	0.1354	0.9608
0.3994	4.0	13	0.0956	0.9804
0.3994	4.62	15	0.0946	0.9804

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1

Task: Image Classification
Library: transformers
Type: swin
License: apache-2.0
Created: Feb 13, 2024
Updated: Feb 13, 2024