ms-cond-detr-res-50-vehicles

This model is a fine-tuned version of datamonster/ms-cond-detr-res-50-vehicles on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.8407
• eval_map: 0.5078
• eval_map_50: 0.8475
• eval_map_75: 0.543
• eval_map_small: 0.1375
• eval_map_medium: 0.5038
• eval_map_large: 0.7143
• eval_mar_1: 0.2612
• eval_mar_10: 0.5658
• eval_mar_100: 0.6127
• eval_mar_small: 0.3327
• eval_mar_medium: 0.6156
• eval_mar_large: 0.7981
• eval_map_motorbike: 0.3689
• eval_mar_100_motorbike: 0.4835
• eval_map_car: 0.5308
• eval_mar_100_car: 0.6198
• eval_map_bus: 0.5808
• eval_mar_100_bus: 0.6911
• eval_map_container: 0.5506
• eval_mar_100_container: 0.6566
• eval_runtime: 144.8577
• eval_samples_per_second: 15.898
• eval_steps_per_second: 1.988
• epoch: 36.0
• step: 82980

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: 0.0001
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine_with_restarts
• num_epochs: 60
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0