readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: emotion-det
    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. -->
  
  # emotion-det
  
  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 None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9378
  - Accuracy: 0.6623
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.0009        | 1.0   | 449  | 1.0473          | 0.6275   |
  | 0.8898        | 2.0   | 898  | 0.9876          | 0.6495   |
  | 0.7885        | 3.0   | 1347 | 0.9502          | 0.6620   |
  | 0.661         | 4.0   | 1796 | 0.9378          | 0.6623   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  