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snap-plate-instance-localization-dfine-v4
aguxez/snap-plate-instance-localization-dfine-v4
snap-plate-instance-localization-dfine-v4 is a object detection model from aguxez. Use it when you need objects located in an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Object Detection
- Library
- transformers
- License
- apache-2.0
- Model type
- d_fine
- Access
- Public
- Created
- Aug 12, 2026
- Updated
- Aug 12, 2026
- SHA
- ed97a52a
Base models
Datasets
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. -->
snap-plate-instance-localization-dfine-v4
This model is a fine-tuned version of aguxez/snap-plate-localization-dfine-v1 on the aguxez/snap-plate-instance-localization-v4 dataset. It achieves the following results on the evaluation set:
- Loss: 4.1975
- Map: 0.2631
- Map 50: 0.5376
- Map 75: 0.1749
- Map Small: -1.0
- Map Medium: 0.1537
- Map Large: 0.3632
- Mar 1: 0.1375
- Mar 10: 0.3917
- Mar 100: 0.4625
- Mar Small: -1.0
- Mar Medium: 0.3727
- Mar Large: 0.5385
- Map Weight Plate: 0.2631
- Mar 100 Weight Plate: 0.4625
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: 2e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 7
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.05
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Weight Plate | Mar 100 Weight Plate |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 13.6666 | 1.0 | 66 | 4.3026 | 0.2542 | 0.5147 | 0.1399 | -1.0 | 0.1212 | 0.3802 | 0.1458 | 0.3625 | 0.4458 | -1.0 | 0.3545 | 0.5231 | 0.2542 | 0.4458 |
| 14.0320 | 2.0 | 132 | 4.2434 | 0.2583 | 0.5265 | 0.145 | -1.0 | 0.1174 | 0.3759 | 0.1625 | 0.3542 | 0.4583 | -1.0 | 0.3636 | 0.5385 | 0.2583 | 0.4583 |
| 14.2001 | 3.0 | 198 | 4.1975 | 0.2631 | 0.5376 | 0.1749 | -1.0 | 0.1537 | 0.3632 | 0.1375 | 0.3917 | 0.4625 | -1.0 | 0.3727 | 0.5385 | 0.2631 | 0.4625 |
Framework versions
- Transformers 5.14.1
- Pytorch 2.13.0+cu130
- Datasets 5.0.1
- Tokenizers 0.22.2
- Task
- Object Detection
- Library
- transformers
- Type
- d_fine
- License
- apache-2.0
- Created
- Aug 12, 2026
- Updated
- Aug 12, 2026