readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-aiornot-baseline
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # swin-tiny-patch4-window7-224-finetuned-aiornot-baseline
  
  This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2231
  - Accuracy: 0.9119
  - F1: 0.9086
  - Log Loss: 3.0422
  
  ## 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: 8
  - total_train_batch_size: 512
  - 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Log Loss |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|
  | 0.2538        | 0.98  | 32   | 0.2327          | 0.9055   | 0.9018 | 3.2647   |
  | 0.1735        | 1.98  | 64   | 0.2029          | 0.9151   | 0.9122 | 2.9309   |
  | 0.1562        | 2.98  | 96   | 0.2231          | 0.9119   | 0.9086 | 3.0422   |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  