readme: ---
  tags:
  - generated_from_trainer
  - image-to-text
  model-index:
  - name: ViTGPT2_vizwiz
    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. -->
  
  # ViTGPT2_vizwiz
  
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0719
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 0.1207        | 0.07  | 1000  | 0.0906          |
  | 0.0916        | 0.14  | 2000  | 0.0861          |
  | 0.0879        | 0.2   | 3000  | 0.0840          |
  | 0.0856        | 0.27  | 4000  | 0.0822          |
  | 0.0834        | 0.34  | 5000  | 0.0806          |
  | 0.0817        | 0.41  | 6000  | 0.0795          |
  | 0.0812        | 0.48  | 7000  | 0.0785          |
  | 0.0808        | 0.55  | 8000  | 0.0779          |
  | 0.0796        | 0.61  | 9000  | 0.0771          |
  | 0.0786        | 0.68  | 10000 | 0.0767          |
  | 0.0774        | 0.75  | 11000 | 0.0762          |
  | 0.0772        | 0.82  | 12000 | 0.0758          |
  | 0.0756        | 0.89  | 13000 | 0.0754          |
  | 0.0759        | 0.96  | 14000 | 0.0750          |
  | 0.0756        | 1.02  | 15000 | 0.0748          |
  | 0.0726        | 1.09  | 16000 | 0.0745          |
  | 0.0727        | 1.16  | 17000 | 0.0745          |
  | 0.0715        | 1.23  | 18000 | 0.0742          |
  | 0.0726        | 1.3   | 19000 | 0.0741          |
  | 0.072         | 1.37  | 20000 | 0.0738          |
  | 0.0723        | 1.43  | 21000 | 0.0735          |
  | 0.0715        | 1.5   | 22000 | 0.0734          |
  | 0.0724        | 1.57  | 23000 | 0.0732          |
  | 0.0723        | 1.64  | 24000 | 0.0730          |
  | 0.0718        | 1.71  | 25000 | 0.0729          |
  | 0.07          | 1.78  | 26000 | 0.0728          |
  | 0.0702        | 1.84  | 27000 | 0.0726          |
  | 0.0704        | 1.91  | 28000 | 0.0725          |
  | 0.0703        | 1.98  | 29000 | 0.0725          |
  | 0.0686        | 2.05  | 30000 | 0.0726          |
  | 0.0687        | 2.12  | 31000 | 0.0726          |
  | 0.0688        | 2.19  | 32000 | 0.0724          |
  | 0.0677        | 2.25  | 33000 | 0.0724          |
  | 0.0665        | 2.32  | 34000 | 0.0725          |
  | 0.0684        | 2.39  | 35000 | 0.0723          |
  | 0.0678        | 2.46  | 36000 | 0.0722          |
  | 0.0686        | 2.53  | 37000 | 0.0722          |
  | 0.067         | 2.59  | 38000 | 0.0721          |
  | 0.0669        | 2.66  | 39000 | 0.0721          |
  | 0.0673        | 2.73  | 40000 | 0.0721          |
  | 0.0673        | 2.8   | 41000 | 0.0720          |
  | 0.0662        | 2.87  | 42000 | 0.0720          |
  | 0.0681        | 2.94  | 43000 | 0.0719          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  