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detr

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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
  - generated_from_trainer
model-index:
  - name: detr
    results: []

Visualize in Weights & Biases Visualize in Weights & Biases

detr

This model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1588
  • Map: 0.0662
  • Map 50: 0.1137
  • Map 75: 0.0667
  • Map Small: 0.0
  • Map Medium: 0.0013
  • Map Large: 0.0706
  • Mar 1: 0.0705
  • Mar 10: 0.1303
  • Mar 100: 0.1374
  • Mar Small: 0.0
  • Mar Medium: 0.009
  • Mar Large: 0.1536
  • Map Person: 0.5545
  • Mar 100 Person: 0.6988
  • Map Ear: 0.0068
  • Mar 100 Ear: 0.1599
  • Map Earmuffs: 0.0
  • Mar 100 Earmuffs: 0.0
  • Map Face: 0.1494
  • Mar 100 Face: 0.3924
  • Map Face-guard: 0.0
  • Mar 100 Face-guard: 0.0
  • Map Face-mask-medical: 0.0
  • Mar 100 Face-mask-medical: 0.0
  • Map Foot: 0.0
  • Mar 100 Foot: 0.0
  • Map Tools: 0.0012
  • Mar 100 Tools: 0.0722
  • Map Glasses: 0.0
  • Mar 100 Glasses: 0.0
  • Map Gloves: 0.0
  • Mar 100 Gloves: 0.0
  • Map Helmet: 0.0
  • Mar 100 Helmet: 0.0
  • Map Hands: 0.1315
  • Mar 100 Hands: 0.4111
  • Map Head: 0.274
  • Mar 100 Head: 0.5671
  • Map Medical-suit: 0.0
  • Mar 100 Medical-suit: 0.0
  • Map Shoes: 0.0073
  • Mar 100 Shoes: 0.035
  • Map Safety-suit: 0.0
  • Mar 100 Safety-suit: 0.0
  • Map Safety-vest: 0.0
  • Mar 100 Safety-vest: 0.0

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 10
  • 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 Person Mar 100 Person Map Ear Mar 100 Ear Map Earmuffs Mar 100 Earmuffs Map Face Mar 100 Face Map Face-guard Mar 100 Face-guard Map Face-mask-medical Mar 100 Face-mask-medical Map Foot Mar 100 Foot Map Tools Mar 100 Tools Map Glasses Mar 100 Glasses Map Gloves Mar 100 Gloves Map Helmet Mar 100 Helmet Map Hands Mar 100 Hands Map Head Mar 100 Head Map Medical-suit Mar 100 Medical-suit Map Shoes Mar 100 Shoes Map Safety-suit Mar 100 Safety-suit Map Safety-vest Mar 100 Safety-vest
No log 0.9913 57 2.9995 0.0253 0.0391 0.0271 0.0 0.0001 0.0263 0.0319 0.0569 0.0684 0.0 0.0005 0.0725 0.3757 0.6561 0.0002 0.0046 0.0 0.0 0.0006 0.0042 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0211 0.3065 0.0333 0.1919 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
No log 2.0 115 2.6946 0.0312 0.0518 0.0323 0.0 0.0002 0.0327 0.0411 0.0775 0.0874 0.0 0.003 0.094 0.42 0.6762 0.0007 0.0246 0.0 0.0 0.0053 0.0515 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0373 0.3427 0.0669 0.3916 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
No log 2.9913 172 2.5527 0.0325 0.0595 0.0308 0.0 0.002 0.0343 0.0441 0.0853 0.0961 0.0 0.0057 0.1058 0.3649 0.652 0.0021 0.0798 0.0 0.0 0.0142 0.0748 0.0 0.0 0.0 0.0 0.0 0.0 0.0022 0.0073 0.0 0.0 0.0 0.0 0.0 0.0 0.0508 0.3384 0.1178 0.482 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
No log 4.0 230 2.4637 0.0425 0.0788 0.0396 0.0 0.0006 0.0449 0.0503 0.0968 0.1059 0.0 0.0049 0.1168 0.451 0.6564 0.0018 0.0867 0.0 0.0 0.0548 0.1764 0.0 0.0 0.0 0.0 0.0 0.0 0.0017 0.0225 0.0 0.0 0.0 0.0 0.0 0.0 0.0725 0.3554 0.1402 0.5027 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
No log 4.9913 287 2.3455 0.0527 0.0929 0.052 0.0 0.0006 0.0561 0.0625 0.1154 0.1234 0.0 0.0042 0.1375 0.4924 0.6771 0.0068 0.1346 0.0 0.0 0.1061 0.3505 0.0 0.0 0.0 0.0 0.0 0.0 0.0011 0.0278 0.0 0.0 0.0 0.0 0.0 0.0 0.0916 0.3802 0.1918 0.5232 0.0 0.0 0.0058 0.0047 0.0 0.0 0.0 0.0
No log 6.0 345 2.2859 0.0538 0.0938 0.0534 0.0 0.0011 0.0572 0.0624 0.1175 0.1268 0.0 0.0051 0.1412 0.5106 0.6945 0.0037 0.1284 0.0 0.0 0.1108 0.3333 0.0 0.0 0.0 0.0 0.0 0.0 0.0006 0.0503 0.0 0.0 0.0 0.0 0.0 0.0 0.1048 0.4016 0.1793 0.5394 0.0 0.0 0.0055 0.0088 0.0 0.0 0.0 0.0
No log 6.9913 402 2.2126 0.0609 0.1056 0.0596 0.0 0.0019 0.065 0.0681 0.1257 0.1319 0.0 0.0086 0.1469 0.5288 0.6915 0.0064 0.1412 0.0 0.0 0.1366 0.3886 0.0 0.0 0.0 0.0 0.0 0.0 0.0006 0.0517 0.0 0.0 0.0 0.0 0.0 0.0 0.1204 0.3905 0.2371 0.5637 0.0 0.0 0.0055 0.0154 0.0 0.0 0.0 0.0
No log 8.0 460 2.1794 0.0641 0.11 0.0643 0.0 0.0015 0.0685 0.0699 0.1294 0.1372 0.0 0.0089 0.1533 0.5525 0.6964 0.0064 0.1599 0.0 0.0 0.1375 0.3892 0.0 0.0 0.0 0.0 0.0 0.0 0.0012 0.0775 0.0 0.0 0.0 0.0 0.0 0.0 0.1273 0.4089 0.2586 0.567 0.0 0.0 0.007 0.0333 0.0 0.0 0.0 0.0
2.8481 8.9913 517 2.1642 0.0658 0.113 0.0661 0.0 0.0016 0.0703 0.0702 0.1296 0.1369 0.0 0.0091 0.1532 0.5529 0.6969 0.0067 0.1606 0.0 0.0 0.1475 0.3875 0.0 0.0 0.0 0.0 0.0 0.0 0.0012 0.0725 0.0 0.0 0.0 0.0 0.0 0.0 0.13 0.4102 0.2727 0.5659 0.0 0.0 0.0073 0.0344 0.0 0.0 0.0 0.0
2.8481 9.9130 570 2.1588 0.0662 0.1137 0.0667 0.0 0.0013 0.0706 0.0705 0.1303 0.1374 0.0 0.009 0.1536 0.5545 0.6988 0.0068 0.1599 0.0 0.0 0.1494 0.3924 0.0 0.0 0.0 0.0 0.0 0.0 0.0012 0.0722 0.0 0.0 0.0 0.0 0.0 0.0 0.1315 0.4111 0.274 0.5671 0.0 0.0 0.0073 0.035 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1