queue_detection / README.md
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metadata
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
  - generated_from_trainer
model-index:
  - name: queue_detection
    results: []

queue_detection

This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4686
  • Map: 0.2556
  • Map 50: 0.4262
  • Map 75: 0.2687
  • Map Small: -1.0
  • Map Medium: 0.0006
  • Map Large: 0.2572
  • Mar 1: 0.2033
  • Mar 10: 0.561
  • Mar 100: 0.715
  • Mar Small: -1.0
  • Mar Medium: 0.0036
  • Mar Large: 0.7212
  • Map Cashier: 0.3957
  • Mar 100 Cashier: 0.812
  • Map Cx: 0.1154
  • Mar 100 Cx: 0.618

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-05
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Map Map 50 Map 75 Map Small Map Medium Map Large Mar 1 Mar 10 Mar 100 Mar Small Mar Medium Mar Large Map Cashier Mar 100 Cashier Map Cx Mar 100 Cx
No log 1.0 218 1.6672 0.1422 0.2781 0.1441 -1.0 0.0 0.1427 0.166 0.421 0.6116 -1.0 0.0 0.6154 0.2345 0.7322 0.05 0.4911
No log 2.0 436 1.4686 0.2556 0.4262 0.2687 -1.0 0.0006 0.2572 0.2033 0.561 0.715 -1.0 0.0036 0.7212 0.3957 0.812 0.1154 0.618

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cpu
  • Datasets 2.20.0
  • Tokenizers 0.19.1