Downloads · 30 days
9
5% of all-time downloads
detr_finetuned
Nihel13/detr_finetuned
detr_finetuned is a object detection model from Nihel13. Use it when you need objects located in an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
173
Public
Parameters
28.8M
115 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors115 MB · 100%
At a glance
- Task
- Object Detection
- Library
- transformers
- Model type
- table-transformer
- Access
- Public
- Created
- Mar 12, 2025
- Updated
- Mar 12, 2025
- SHA
- bed811c8
Base models
Model card
From the Hugging Face model README
<!-- 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_finetuned
This model is a fine-tuned version of apkonsta/table-transformer-detection-ifrs on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4914.5493
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4887.0844 | 0.2381 | 100 | 4915.8008 |
| 4806.7622 | 0.4762 | 200 | 4915.0762 |
| 4883.3641 | 0.7143 | 300 | 4914.7651 |
| 4869.7525 | 0.9524 | 400 | 4914.6387 |
| 4809.9978 | 1.1905 | 500 | 4914.6133 |
| 4820.81 | 1.4286 | 600 | 4914.6948 |
| 4779.5872 | 1.6667 | 700 | 4914.6743 |
| 5094.1991 | 1.9048 | 800 | 4914.5752 |
| 4851.7441 | 2.1429 | 900 | 4914.6494 |
| 4928.8484 | 2.3810 | 1000 | 4914.5767 |
| 4852.6178 | 2.6190 | 1100 | 4914.5840 |
| 4855.8131 | 2.8571 | 1200 | 4914.5991 |
| 4948.5747 | 3.0952 | 1300 | 4914.5967 |
| 4887.945 | 3.3333 | 1400 | 4914.5645 |
| 4900.1669 | 3.5714 | 1500 | 4914.5747 |
| 4937.1328 | 3.8095 | 1600 | 4914.5571 |
| 4792.3219 | 4.0476 | 1700 | 4914.6787 |
| 4842.8072 | 4.2857 | 1800 | 4914.5640 |
| 4914.0503 | 4.5238 | 1900 | 4914.6113 |
| 4892.0153 | 4.7619 | 2000 | 4914.5693 |
| 4882.0288 | 5.0 | 2100 | 4914.5630 |
| 4903.9891 | 5.2381 | 2200 | 4914.5679 |
| 4870.5566 | 5.4762 | 2300 | 4914.5688 |
| 4919.3287 | 5.7143 | 2400 | 4914.5508 |
| 4927.9272 | 5.9524 | 2500 | 4914.5488 |
| 4981.8925 | 6.1905 | 2600 | 4914.5537 |
| 4864.6322 | 6.4286 | 2700 | 4914.5835 |
| 4794.4006 | 6.6667 | 2800 | 4914.5820 |
| 4878.885 | 6.9048 | 2900 | 4914.5488 |
| 4967.0887 | 7.1429 | 3000 | 4914.5518 |
| 4937.0766 | 7.3810 | 3100 | 4914.5464 |
| 4829.3891 | 7.6190 | 3200 | 4914.5493 |
| 4812.0778 | 7.8571 | 3300 | 4914.5459 |
| 4823.5034 | 8.0952 | 3400 | 4914.5444 |
| 4919.2544 | 8.3333 | 3500 | 4914.5474 |
| 4838.375 | 8.5714 | 3600 | 4914.5581 |
| 4832.6153 | 8.8095 | 3700 | 4914.5513 |
| 4787.5813 | 9.0476 | 3800 | 4914.5464 |
| 4862.2234 | 9.2857 | 3900 | 4914.5464 |
| 4878.2669 | 9.5238 | 4000 | 4914.5474 |
| 4933.3856 | 9.7619 | 4100 | 4914.5488 |
| 4945.8159 | 10.0 | 4200 | 4914.5493 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0
- Task
- Object Detection
- Library
- transformers
- Type
- table-transformer
- Created
- Mar 12, 2025
- Updated
- Mar 12, 2025