readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: complete-prova
    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. -->
  
  # complete-prova
  
  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4074
  - Precision: 0.5533
  - Recall: 0.3424
  - F1: 0.4230
  - Accuracy: 0.9092
  
  ## 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: 1e-05
  - train_batch_size: 2
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 500
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 0.76  | 100  | 0.6181          | 0.0       | 0.0    | 0.0    | 0.8733   |
  | No log        | 1.52  | 200  | 0.5377          | 0.4167    | 0.0485 | 0.0869 | 0.8792   |
  | No log        | 2.27  | 300  | 0.4737          | 0.4286    | 0.1222 | 0.1902 | 0.8870   |
  | No log        | 3.03  | 400  | 0.4254          | 0.5152    | 0.3278 | 0.4007 | 0.9063   |
  | 0.5393        | 3.79  | 500  | 0.4074          | 0.5533    | 0.3424 | 0.4230 | 0.9092   |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  