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metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-mobile-eye-tracking-dataset-v2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.598512173128945

swin-tiny-patch4-window7-224-finetuned-mobile-eye-tracking-dataset-v2

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

  • Loss: 0.6732
  • Accuracy: 0.5985

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
0.6726 1.0 329 0.6758 0.5985
0.6773 2.0 658 0.6738 0.5985
0.6701 3.0 987 0.6736 0.5985
0.6734 4.0 1317 0.6735 0.5985
0.671 5.0 1646 0.6738 0.5985
0.6725 6.0 1975 0.6740 0.5985
0.6702 7.0 2304 0.6737 0.5985
0.6708 8.0 2634 0.6733 0.5983
0.6732 9.0 2963 0.6735 0.5985
0.671 9.99 3290 0.6732 0.5985

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.1