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---
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
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