Downloads · 30 days
14
35% of all-time downloads
snap-plate-stack-instance-dfine-v5
aguxez/snap-plate-stack-instance-dfine-v5
snap-plate-stack-instance-dfine-v5 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. --
All-time downloads
40
Public
Parameters
10.2M
288 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors41.1 MB · 100%
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
- 54c74ec4
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-stack-instance-dfine-v5
This model is a fine-tuned version of aguxez/snap-plate-instance-localization-dfine-v4 on the aguxez/snap-plate-stack-instance-v5 dataset. It achieves the following results on the evaluation set:
- Loss: 3.5716
- Map: 0.8835
- Map 50: 1.0
- Map 75: 1.0
- Map Small: -1.0
- Map Medium: 0.9
- Map Large: 0.8831
- Mar 1: 0.3375
- Mar 10: 0.9375
- Mar 100: 0.95
- Mar Small: -1.0
- Mar Medium: 0.9
- Mar Large: 0.9571
- Map Weight Plate: 0.8835
- Mar 100 Weight Plate: 0.95
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-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: 8.0
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 19.4634 | 1.0 | 7 | 2.7761 | 0.8851 | 1.0 | 1.0 | -1.0 | 1.0 | 0.8799 | 0.325 | 0.925 | 0.975 | -1.0 | 1.0 | 0.9714 | 0.8851 | 0.975 |
| 21.5298 | 2.0 | 14 | 3.0125 | 0.8701 | 1.0 | 1.0 | -1.0 | 0.9 | 0.869 | 0.325 | 0.9125 | 0.9375 | -1.0 | 0.9 | 0.9429 | 0.8701 | 0.9375 |
| 17.9227 | 3.0 | 21 | 3.1628 | 0.8969 | 1.0 | 1.0 | -1.0 | 1.0 | 0.8855 | 0.3375 | 0.9625 | 0.975 | -1.0 | 1.0 | 0.9714 | 0.8969 | 0.975 |
| 20.3749 | 4.0 | 28 | 3.2891 | 0.8691 | 0.9743 | 0.9743 | -1.0 | 1.0 | 0.8843 | 0.35 | 0.95 | 0.9625 | -1.0 | 1.0 | 0.9571 | 0.8691 | 0.9625 |
| 17.0228 | 5.0 | 35 | 3.3509 | 0.8836 | 1.0 | 1.0 | -1.0 | 0.9 | 0.8844 | 0.3375 | 0.9375 | 0.95 | -1.0 | 0.9 | 0.9571 | 0.8836 | 0.95 |
| 19.0717 | 6.0 | 42 | 3.4911 | 0.8787 | 1.0 | 1.0 | -1.0 | 0.9 | 0.8791 | 0.325 | 0.925 | 0.925 | -1.0 | 0.9 | 0.9286 | 0.8787 | 0.925 |
| 16.4956 | 7.0 | 49 | 3.5982 | 0.8778 | 1.0 | 1.0 | -1.0 | 0.9 | 0.8756 | 0.325 | 0.925 | 0.925 | -1.0 | 0.9 | 0.9286 | 0.8778 | 0.925 |
| 18.0839 | 8.0 | 56 | 3.5716 | 0.8835 | 1.0 | 1.0 | -1.0 | 0.9 | 0.8831 | 0.3375 | 0.9375 | 0.95 | -1.0 | 0.9 | 0.9571 | 0.8835 | 0.95 |
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