readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: serverless-roomsort
    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. -->
  
  # serverless-roomsort
  
  This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0394
  - Accuracy: 0.9892
  
  ## 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: 16
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7844        | 1.0   | 762  | 0.0608          | 0.9791   |
  | 0.0361        | 2.0   | 1524 | 0.0626          | 0.9830   |
  | 0.0149        | 3.0   | 2286 | 0.0468          | 0.9879   |
  | 0.0027        | 4.0   | 3048 | 0.0394          | 0.9892   |
  | 0.0017        | 5.0   | 3810 | 0.0486          | 0.9889   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu113
  - Datasets 1.18.4
  - Tokenizers 0.13.0
  