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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- table_detection_light
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model-index:
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- name: DeTr-TableDetection-5000-images
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# DeTr-TableDetection-5000-images
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.3184
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- Mean Iou: 0.0234
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.741 | 1.0 | 313 | 0.7054 | 0.0259 |
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| 0.5559 | 2.0 | 626 | 0.5159 | 0.0231 |
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| 0.4213 | 3.0 | 939 | 0.4154 | 0.0254 |
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| 0.4374 | 4.0 | 1252 | 0.4072 | 0.0249 |
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| 0.3884 | 5.0 | 1565 | 0.4454 | 0.0232 |
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| 0.4057 | 6.0 | 1878 | 0.4251 | 0.0249 |
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| 0.3511 | 7.0 | 2191 | 0.3882 | 0.0239 |
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| 0.3463 | 8.0 | 2504 | 0.3766 | 0.0243 |
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| 0.3346 | 9.0 | 2817 | 0.4142 | 0.0236 |
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| 0.3183 | 10.0 | 3130 | 0.3804 | 0.0242 |
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| 0.3049 | 11.0 | 3443 | 0.3642 | 0.0244 |
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| 0.2942 | 12.0 | 3756 | 0.3541 | 0.0253 |
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| 0.2836 | 13.0 | 4069 | 0.3359 | 0.0252 |
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| 0.2738 | 14.0 | 4382 | 0.3338 | 0.0254 |
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| 0.2629 | 15.0 | 4695 | 0.3318 | 0.0267 |
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| 0.2591 | 16.0 | 5008 | 0.3311 | 0.0224 |
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| 0.2457 | 17.0 | 5321 | 0.3317 | 0.0234 |
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| 0.2406 | 18.0 | 5634 | 0.3219 | 0.0238 |
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| 0.2383 | 19.0 | 5947 | 0.3143 | 0.0238 |
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| 0.2229 | 20.0 | 6260 | 0.3184 | 0.0234 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1+cu117
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- Datasets 2.5.1
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- Tokenizers 0.13.2
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