Brain_Tumor_Classification_using_swin_transformer – AI Model by surajjoshi | AlphaNeural AI

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Brain_Tumor_Classification_using_swin_transformer

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image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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Brain_Tumor_Classification_using_swin_transformer

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0118
Accuracy: 0.9949
F1: 0.9949
Recall: 0.9949
Precision: 0.9949

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision
0.081	1.0	180	0.0557	0.9832	0.9832	0.9832	0.9832
0.0816	2.0	360	0.0187	0.9937	0.9937	0.9937	0.9937
0.0543	3.0	540	0.0118	0.9949	0.9949	0.9949	0.9949

Framework versions

Transformers 4.23.1
Pytorch 1.13.0
Datasets 2.6.1
Tokenizers 0.13.1