readme: ---
  tags:
  - image-classification
  - timm
  - generated_from_trainer
  datasets:
  - beans
  metrics:
  - accuracy
  model_index:
  - name: timm-resnet18-beans-test-2
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: beans
        type: beans
        args: default
      metric:
        name: Accuracy
        type: accuracy
        value: 0.5789473684210527
  ---
  
  <!-- 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. -->
  
  # timm-resnet18-beans-test-2
  
  This model is a fine-tuned version of [resnet18](https://huggingface.co/resnet18) on the beans dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3225
  - Accuracy: 0.5789
  
  ## 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: 0.001
  - train_batch_size: 4
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.2601        | 0.02  | 5    | 2.8349          | 0.5113   |
  | 1.8184        | 0.04  | 10   | 1.3225          | 0.5789   |
  
  
  ### Framework versions
  
  - Transformers 4.9.1
  - Pytorch 1.9.0
  - Datasets 1.11.1.dev0
  - Tokenizers 0.10.3
  