Instructions to use nothing95/detr-finetuned-window with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nothing95/detr-finetuned-window with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="nothing95/detr-finetuned-window")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("nothing95/detr-finetuned-window") model = AutoModelForObjectDetection.from_pretrained("nothing95/detr-finetuned-window") - Notebooks
- Google Colab
- Kaggle
detr-finetuned-window
This model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.
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-06
- train_batch_size: 8
- eval_batch_size: 4
- 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: 200
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1
- Downloads last month
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Model tree for nothing95/detr-finetuned-window
Base model
facebook/detr-resnet-50