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Brain_Tumor_Detector_swin – AI Model by Devarshi | AlphaNeural AI
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Devarshi
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Brain_Tumor_Detector_swin
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transformers
pytorch
swin
image-classification
generated_from_trainer
imagefolder
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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Brain_Tumor_Detector_swin
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: 0.0054
Accuracy: 0.9981
F1: 0.9985
Recall: 0.9990
Precision: 0.9980
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
0.079
1.0
113
0.0283
0.9882
0.9906
0.9930
0.9881
0.0575
2.0
226
0.0121
0.9956
0.9965
0.9950
0.9980
0.0312
3.0
339
0.0054
0.9981
0.9985
0.9990
0.9980
Framework versions
Transformers 4.23.1
Pytorch 1.12.1
Datasets 2.6.1
Tokenizers 0.13.1
