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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
    results: []

swin-brain-abnormalities-classification

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: 0.2291
  • Accuracy: 0.9262

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: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.2609 1.0 6 0.9906 0.6779
0.8038 2.0 12 0.6710 0.7718
0.7211 3.0 18 0.5718 0.7785
0.5931 4.0 24 0.4404 0.8255
0.4773 5.0 30 0.3184 0.8859
0.4233 6.0 36 0.2672 0.9396
0.3331 7.0 42 0.2489 0.9262
0.2819 8.0 48 0.2307 0.9396
0.2437 9.0 54 0.2180 0.9262
0.2231 10.0 60 0.2301 0.9128
0.2023 11.0 66 0.1972 0.9262
0.1873 12.0 72 0.2396 0.9128
0.1627 13.0 78 0.1933 0.9262
0.1372 14.0 84 0.2708 0.9195
0.1559 15.0 90 0.2443 0.9128
0.1455 16.0 96 0.2369 0.9195
0.1064 17.0 102 0.2470 0.9128
0.1152 18.0 108 0.2397 0.9128
0.0994 19.0 114 0.2626 0.9128
0.1046 20.0 120 0.2738 0.9195
0.1056 21.0 126 0.2384 0.9195
0.0902 22.0 132 0.2373 0.9195
0.0735 23.0 138 0.2268 0.9329
0.096 24.0 144 0.2240 0.9329
0.1087 25.0 150 0.2291 0.9262

Framework versions

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