# Load model directly
from transformers import AutoImageProcessor, AutoModelForObjectDetection
processor = AutoImageProcessor.from_pretrained("binitt/buttons-train")
model = AutoModelForObjectDetection.from_pretrained("binitt/buttons-train")Quick Links
buttons-train
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: 6e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
Training results
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for binitt/buttons-train
Base model
facebook/detr-resnet-50
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="binitt/buttons-train")