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metadata
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: swin-brain-abnormalities-classification-fold1
    results: []

swin-brain-abnormalities-classification-fold1

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

  • Loss: 0.1102
  • Accuracy: 0.9607

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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.9214 0.9714 17 0.7237 0.7249
0.5441 2.0 35 0.3606 0.8523
0.3592 2.9714 52 0.2474 0.9024
0.2732 4.0 70 0.2265 0.9173
0.2283 4.9714 87 0.1731 0.9404
0.1865 6.0 105 0.1808 0.9309
0.185 6.9714 122 0.1703 0.9201
0.1597 8.0 140 0.1262 0.9485
0.1545 8.9714 157 0.1375 0.9472
0.1237 10.0 175 0.1133 0.9580
0.1165 10.9714 192 0.1299 0.9512
0.1086 12.0 210 0.1118 0.9634
0.1129 12.9714 227 0.1101 0.9580
0.0898 14.0 245 0.1089 0.9607
0.0811 14.5714 255 0.1102 0.9607

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0