readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - table_detection_light
  model-index:
  - name: DeTr-TableDetection-1000-images
    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. -->
  
  # DeTr-TableDetection-1000-images
  
  This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the table_detection_light dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5143
  - Mean Iou: 0.0242
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 63   | 0.8696          | 0.0215   |
  | 0.9227        | 2.0   | 126  | 0.7547          | 0.0245   |
  | 0.9227        | 3.0   | 189  | 0.7170          | 0.0211   |
  | 0.6775        | 4.0   | 252  | 0.8319          | 0.0222   |
  | 0.6801        | 5.0   | 315  | 0.6943          | 0.0212   |
  | 0.6801        | 6.0   | 378  | 0.6622          | 0.0252   |
  | 0.604         | 7.0   | 441  | 0.6043          | 0.0234   |
  | 0.5467        | 8.0   | 504  | 0.7404          | 0.0249   |
  | 0.5467        | 9.0   | 567  | 0.6755          | 0.0242   |
  | 0.4347        | 10.0  | 630  | 0.5507          | 0.0232   |
  | 0.4347        | 11.0  | 693  | 0.6633          | 0.0277   |
  | 0.4202        | 12.0  | 756  | 0.5941          | 0.0256   |
  | 0.3508        | 13.0  | 819  | 0.5387          | 0.0238   |
  | 0.3508        | 14.0  | 882  | 0.5381          | 0.0256   |
  | 0.3223        | 15.0  | 945  | 0.5646          | 0.0254   |
  | 0.3058        | 16.0  | 1008 | 0.5460          | 0.0213   |
  | 0.3058        | 17.0  | 1071 | 0.5589          | 0.0264   |
  | 0.2861        | 18.0  | 1134 | 0.5423          | 0.0257   |
  | 0.2861        | 19.0  | 1197 | 0.5207          | 0.0248   |
  | 0.2705        | 20.0  | 1260 | 0.5143          | 0.0242   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu117
  - Datasets 2.5.1
  - Tokenizers 0.13.2
  