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metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-RCC
    results: []

swin-tiny-patch4-window7-224-finetuned-RCC

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3565
  • Accuracy: 0.9032
  • Precision: 0.9032
  • Recall: 1.0
  • F1: 0.4746
  • Auc: 0.5

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: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Auc
No log 0.8571 3 0.3383 0.9032 0.9032 1.0 0.4746 0.5
No log 2.0 7 0.3654 0.9032 0.9032 1.0 0.4746 0.5
0.3833 2.8571 10 0.3422 0.9032 0.9032 1.0 0.4746 0.5
0.3833 4.0 14 0.3556 0.9032 0.9032 1.0 0.4746 0.5
0.3833 4.8571 17 0.3425 0.9032 0.9032 1.0 0.4746 0.5
0.2492 6.0 21 0.3401 0.9032 0.9032 1.0 0.4746 0.5
0.2492 6.8571 24 0.3543 0.9032 0.9032 1.0 0.4746 0.5
0.2492 8.0 28 0.3572 0.9032 0.9032 1.0 0.4746 0.5
0.2304 8.5714 30 0.3565 0.9032 0.9032 1.0 0.4746 0.5

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.0.0+cu117
  • Datasets 2.19.1
  • Tokenizers 0.19.1