readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  model-index:
  - name: vit-base-patch16-224-in21k-finetuned-eurosat
    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. -->
  
  # vit-base-patch16-224-in21k-finetuned-eurosat
  
  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:
  - eval_loss: 0.2695
  - eval_accuracy: 0.9022
  - eval_runtime: 195.5267
  - eval_samples_per_second: 21.486
  - eval_steps_per_second: 0.675
  - epoch: 51.76
  - step: 10196
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 200
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.1+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  