swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_12 – AI Model by amjadfqs | AlphaNeural AI

You can deploy this model and start earning money today!

amjadfqs/
swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_12

like

0

image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_12

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: 0.0789
Accuracy: 0.9760
F1 Score: 0.9761
Precision: 0.9762
Sensitivity: 0.9762
Specificity: 0.9940

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: 0.0001
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Score	Precision	Sensitivity	Specificity
0.3644	1.0	30	0.2918	0.8955	0.8974	0.9070	0.8957	0.9734
0.2177	2.0	60	0.2319	0.9152	0.9155	0.9237	0.9156	0.9786
0.1171	3.0	90	0.1654	0.9489	0.9494	0.9532	0.9492	0.9872
0.068	4.0	120	0.1600	0.9450	0.9451	0.9466	0.9455	0.9861
0.0499	5.0	150	0.0947	0.9654	0.9656	0.9656	0.9657	0.9913
0.0302	6.0	180	0.0882	0.9713	0.9714	0.9715	0.9715	0.9928
0.0207	7.0	210	0.1002	0.9698	0.9699	0.9708	0.9699	0.9924
0.0205	8.0	240	0.1550	0.9525	0.9521	0.9544	0.9529	0.9881
0.0163	9.0	270	0.0789	0.9760	0.9761	0.9762	0.9762	0.9940
0.0181	10.0	300	0.0923	0.9737	0.9737	0.9740	0.9738	0.9934

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3