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furniture-ngpea_use_data_finetuning – AI Model by kimchanyeong | AlphaNeural AI
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furniture-ngpea_use_data_finetuning
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transformers
tensorboard
safetensors
detr
object-detection
generated_from_trainer
facebook/detr-resnet-50
finetune
apache-2.0
endpoints_compatible
us
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furniture-ngpea_use_data_finetuning
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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
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
num_epochs: 100
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
