DETR Resnet fine tuned with BrainHack dataset
This model is a fine-tuned version of facebook/detr-resnet-50 on the BrainHack VLM 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for MTWD/detr-resnet-50-brain-hack-v2-gcp
Base model
facebook/detr-resnet-50