readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - image_folder
  metrics:
  - f1
  model-index:
  - name: vit_flyswot_test
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: image_folder
        type: image_folder
        args: default
      metrics:
      - name: F1
        type: f1
        value: 0.849172221610369
  ---
  
  <!-- 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. -->
  
  # vit_flyswot_test
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the image_folder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4777
  - F1: 0.8492
  
  ## 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: 2e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 666
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 52   | 1.2007          | 0.3533 |
  | No log        | 2.0   | 104  | 1.0037          | 0.5525 |
  | No log        | 3.0   | 156  | 0.8301          | 0.6318 |
  | No log        | 4.0   | 208  | 0.7224          | 0.6946 |
  | No log        | 5.0   | 260  | 0.7298          | 0.7145 |
  | No log        | 6.0   | 312  | 0.6328          | 0.7729 |
  | No log        | 7.0   | 364  | 0.6010          | 0.7992 |
  | No log        | 8.0   | 416  | 0.5174          | 0.8364 |
  | No log        | 9.0   | 468  | 0.5084          | 0.8479 |
  | 0.6372        | 10.0  | 520  | 0.4777          | 0.8492 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  