Edit model card

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
Downloads last month
3
Hosted inference API
Drag image file here or click to browse from your device
This model can be loaded on the Inference API on-demand.

Space using Devarshi/Brain_Tumor_Detector_swin 1

Evaluation results