readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-uncased-finetuned-docvqa
    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. -->
  
  # bert-base-uncased-finetuned-docvqa
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9146
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 250500
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 2.2151        | 0.1   | 1000  | 2.6299          |
  | 1.8885        | 0.21  | 2000  | 2.2217          |
  | 1.7353        | 0.31  | 3000  | 2.1675          |
  | 1.6188        | 0.41  | 4000  | 2.2436          |
  | 1.5802        | 0.52  | 5000  | 2.0539          |
  | 1.4875        | 0.62  | 6000  | 2.0551          |
  | 1.4675        | 0.73  | 7000  | 1.9368          |
  | 1.3485        | 0.83  | 8000  | 1.9456          |
  | 1.3273        | 0.93  | 9000  | 1.9281          |
  | 1.1048        | 1.04  | 10000 | 1.9333          |
  | 0.9529        | 1.14  | 11000 | 2.2019          |
  | 0.9418        | 1.24  | 12000 | 2.0381          |
  | 0.9209        | 1.35  | 13000 | 1.8753          |
  | 0.8788        | 1.45  | 14000 | 1.9964          |
  | 0.8729        | 1.56  | 15000 | 1.9690          |
  | 0.8671        | 1.66  | 16000 | 1.8513          |
  | 0.8379        | 1.76  | 17000 | 1.9627          |
  | 0.8722        | 1.87  | 18000 | 1.8988          |
  | 0.7842        | 1.97  | 19000 | 1.9146          |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  