swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_07 – AI Model by amjadfqs | AlphaNeural AI

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amjadfqs/
swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_07

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image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_07

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: 0.2904
Accuracy: 0.9095
F1 Score: 0.9095
Precision: 0.9189

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: 100
eval_batch_size: 100
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 400
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
1.3335	0.98	13	0.9195	0.6281	0.6111	0.7245
0.6062	1.96	26	0.6114	0.7625	0.7673	0.8385
0.274	2.94	39	0.5468	0.7802	0.7772	0.8533
0.1211	4.0	53	0.3922	0.8417	0.8417	0.8749
0.0991	4.98	66	0.4734	0.8172	0.8209	0.8802
0.0682	5.96	79	0.3751	0.8599	0.8600	0.8882
0.0414	6.94	92	0.2951	0.8986	0.8995	0.9100
0.0264	8.0	106	0.3485	0.8844	0.8855	0.9069
0.021	8.98	119	0.3803	0.8764	0.8782	0.9031
0.0151	9.81	130	0.2904	0.9095	0.9095	0.9189

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3