readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - table_detection_light
  model-index:
  - name: DeTr-TableDetection-5000-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-5000-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: 0.3184
  - Mean Iou: 0.0234
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.741         | 1.0   | 313  | 0.7054          | 0.0259   |
  | 0.5559        | 2.0   | 626  | 0.5159          | 0.0231   |
  | 0.4213        | 3.0   | 939  | 0.4154          | 0.0254   |
  | 0.4374        | 4.0   | 1252 | 0.4072          | 0.0249   |
  | 0.3884        | 5.0   | 1565 | 0.4454          | 0.0232   |
  | 0.4057        | 6.0   | 1878 | 0.4251          | 0.0249   |
  | 0.3511        | 7.0   | 2191 | 0.3882          | 0.0239   |
  | 0.3463        | 8.0   | 2504 | 0.3766          | 0.0243   |
  | 0.3346        | 9.0   | 2817 | 0.4142          | 0.0236   |
  | 0.3183        | 10.0  | 3130 | 0.3804          | 0.0242   |
  | 0.3049        | 11.0  | 3443 | 0.3642          | 0.0244   |
  | 0.2942        | 12.0  | 3756 | 0.3541          | 0.0253   |
  | 0.2836        | 13.0  | 4069 | 0.3359          | 0.0252   |
  | 0.2738        | 14.0  | 4382 | 0.3338          | 0.0254   |
  | 0.2629        | 15.0  | 4695 | 0.3318          | 0.0267   |
  | 0.2591        | 16.0  | 5008 | 0.3311          | 0.0224   |
  | 0.2457        | 17.0  | 5321 | 0.3317          | 0.0234   |
  | 0.2406        | 18.0  | 5634 | 0.3219          | 0.0238   |
  | 0.2383        | 19.0  | 5947 | 0.3143          | 0.0238   |
  | 0.2229        | 20.0  | 6260 | 0.3184          | 0.0234   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu117
  - Datasets 2.5.1
  - Tokenizers 0.13.2
  