readme: ---
  tags:
  - image-classification
  - vision
  - generated_from_trainer
  datasets:
  - beans
  metrics:
  - accuracy
  model-index:
  - name: resnet-50-base-beans-demo
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: beans
        type: beans
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9022556390977443
  ---
  
  <!-- 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. -->
  
  # resnet-50-base-beans-demo
  
  This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the beans dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2188
  - Accuracy: 0.9023
  
  ## 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: 0.002
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 1337
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 1.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.5679        | 1.0   | 130  | 0.2188          | 0.9023   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  