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snap-plate-rim-marker-dfine-v6
aguxez/snap-plate-rim-marker-dfine-v6
snap-plate-rim-marker-dfine-v6 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
- eb3b7f4c
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-rim-marker-dfine-v6
This model is a fine-tuned version of aguxez/snap-plate-stack-instance-dfine-v5 on the aguxez/snap-plate-rim-marker-v6 dataset. It achieves the following results on the evaluation set:
- Loss: 10.6621
- Map: 0.0
- Map 50: 0.0
- Map 75: 0.0
- Map Small: -1.0
- Map Medium: 0.0
- Map Large: -1.0
- Mar 1: 0.0
- Mar 10: 0.0
- Mar 100: 0.0
- Mar Small: -1.0
- Mar Medium: 0.0
- Mar Large: -1.0
- Map Plate Rim: 0.0
- Mar 100 Plate Rim: 0.0
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: 6.0
- 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 Plate Rim | Mar 100 Plate Rim |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 30.4838 | 1.0 | 8 | 10.9252 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 |
| 28.7425 | 2.0 | 16 | 9.6348 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 |
| 29.1607 | 3.0 | 24 | 10.5503 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 |
| 30.0144 | 4.0 | 32 | 9.5758 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 |
| 29.1989 | 5.0 | 40 | 10.7574 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 |
| 28.7440 | 6.0 | 48 | 10.6621 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 | 0.0 | -1.0 | 0.0 | -1.0 | 0.0 | 0.0 |
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