swin-tiny-patch4-window7-224-finetuned-brain-ich – AI Model by codewithaman | AlphaNeural AI

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codewithaman/
swin-tiny-patch4-window7-224-finetuned-brain-ich

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image-classification

generated_from_trainer

microsoft/swin-tiny-patch4-window7-224

autotrain_compatible

endpoints_compatible

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swin-tiny-patch4-window7-224-finetuned-brain-ich

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: 0.0123
Accuracy: 0.9961
F1: 0.9961
Recall: 0.9961
Precision: 0.9961

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
0.1234	1.0	180	0.0450	0.9840	0.9840	0.9840	0.9840
0.0837	2.0	360	0.0198	0.9926	0.9926	0.9926	0.9926
0.0373	3.0	540	0.0123	0.9961	0.9961	0.9961	0.9961

Framework versions

Transformers 4.23.1
Pytorch 1.13.0
Datasets 2.6.1
Tokenizers 0.13.1