readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - table_detection_light
  model-index:
  - name: DeTr-TableDetection-3000-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-3000-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: 0.3415
  - Mean Iou: 0.0220
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.3991        | 1.0   | 188  | 0.8030          | 0.0267   |
  | 0.9905        | 2.0   | 376  | 0.9429          | 0.0262   |
  | 0.6871        | 3.0   | 564  | 1.2024          | 0.0118   |
  | 0.5837        | 4.0   | 752  | 0.5099          | 0.0202   |
  | 0.527         | 5.0   | 940  | 0.4839          | 0.0204   |
  | 0.4847        | 6.0   | 1128 | 0.4542          | 0.0179   |
  | 0.4255        | 7.0   | 1316 | 0.4381          | 0.0227   |
  | 0.3932        | 8.0   | 1504 | 0.4467          | 0.0243   |
  | 0.3846        | 9.0   | 1692 | 0.3817          | 0.0247   |
  | 0.3494        | 10.0  | 1880 | 0.4122          | 0.0261   |
  | 0.3343        | 11.0  | 2068 | 0.3696          | 0.0249   |
  | 0.324         | 12.0  | 2256 | 0.3683          | 0.0242   |
  | 0.3159        | 13.0  | 2444 | 0.3713          | 0.0241   |
  | 0.3079        | 14.0  | 2632 | 0.3563          | 0.0197   |
  | 0.2909        | 15.0  | 2820 | 0.3530          | 0.0237   |
  | 0.279         | 16.0  | 3008 | 0.3513          | 0.0229   |
  | 0.2769        | 17.0  | 3196 | 0.3390          | 0.0211   |
  | 0.2593        | 18.0  | 3384 | 0.3507          | 0.0238   |
  | 0.2533        | 19.0  | 3572 | 0.3370          | 0.0231   |
  | 0.2502        | 20.0  | 3760 | 0.3415          | 0.0220   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu117
  - Datasets 2.5.1
  - Tokenizers 0.13.2
  