readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  metrics:
  - accuracy
  model-index:
  - name: vit-base-patch16-224-in21k_vegetables_classification
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: imagefolder
        type: imagefolder
        config: default
        split: train
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 1.0
  ---
  
  <!-- 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-base-patch16-224-in21k_vegetables_classification
  
  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0014
  - Accuracy: 1.0
  - Weighted f1: 1.0
  - Micro f1: 1.0
  - Macro f1: 1.0
  - Weighted recall: 1.0
  - Micro recall: 1.0
  - Macro recall: 1.0
  - Weighted precision: 1.0
  - Micro precision: 1.0
  - Macro precision: 1.0
  
  ## 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: 0.0002
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
  | 0.2079        | 1.0   | 938  | 0.0193          | 0.996    | 0.9960      | 0.996    | 0.9960   | 0.996           | 0.996        | 0.9960       | 0.9960             | 0.996           | 0.9960          |
  | 0.0154        | 2.0   | 1876 | 0.0068          | 0.9987   | 0.9987      | 0.9987   | 0.9987   | 0.9987          | 0.9987       | 0.9987       | 0.9987             | 0.9987          | 0.9987          |
  | 0.0018        | 3.0   | 2814 | 0.0014          | 1.0      | 1.0         | 1.0      | 1.0      | 1.0             | 1.0          | 1.0          | 1.0                | 1.0             | 1.0             |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  