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deta-swin-large

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deta
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metadata
library_name: transformers
base_model: jozhang97/deta-swin-large
tags:
  - generated_from_trainer
model-index:
  - name: deta-swin-large
    results: []

deta-swin-large

This model is a fine-tuned version of jozhang97/deta-swin-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 7.7323
  • Map: 0.448
  • Map 50: 0.6146
  • Map 75: 0.4994
  • Map Small: 0.4453
  • Map Medium: 0.5526
  • Map Large: -1.0
  • Mar 1: 0.286
  • Mar 10: 0.4045
  • Mar 100: 0.5073
  • Mar Small: 0.5039
  • Mar Medium: 0.571
  • Mar Large: -1.0
  • Map Ball: 0.2858
  • Mar 100 Ball: 0.4068
  • Map Goalkeeper: 0.7008
  • Mar 100 Goalkeeper: 0.7649
  • Map Player: 0.8053
  • Mar 100 Player: 0.8576
  • Map Referee: 0.0
  • Mar 100 Referee: 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: 0.0001
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 20

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 Ball Mar 100 Ball Map Goalkeeper Mar 100 Goalkeeper Map Player Mar 100 Player Map Referee Mar 100 Referee
296.278 1.0 149 62.3890 0.0999 0.1535 0.1216 0.0976 0.1516 -1.0 0.0078 0.0616 0.1808 0.1808 0.2414 -1.0 0.0 0.0 0.0 0.0 0.3997 0.7232 0.0 0.0
74.5246 2.0 298 25.7949 0.1643 0.236 0.1843 0.1638 0.2281 -1.0 0.0162 0.1175 0.3643 0.3753 0.2564 -1.0 0.0 0.0 0.0189 0.6969 0.6384 0.7605 0.0 0.0
23.5211 3.0 447 16.6520 0.1984 0.25 0.2246 0.1971 0.2759 -1.0 0.0111 0.2288 0.4151 0.4131 0.5609 -1.0 0.0 0.0 0.0371 0.8114 0.7566 0.849 0.0 0.0
18.7573 4.0 596 13.6105 0.2271 0.3101 0.2518 0.2264 0.2742 -1.0 0.0608 0.2627 0.4917 0.4901 0.5426 -1.0 0.1064 0.3159 0.0287 0.8139 0.7732 0.8368 0.0 0.0
14.4593 5.0 745 11.9880 0.2282 0.309 0.2486 0.2272 0.2805 -1.0 0.0774 0.2571 0.4835 0.4812 0.531 -1.0 0.1022 0.3023 0.028 0.7914 0.7824 0.8405 0.0 0.0
12.878 6.0 894 10.9109 0.3867 0.5529 0.418 0.3955 0.3944 -1.0 0.2517 0.3723 0.4836 0.4837 0.526 -1.0 0.1759 0.3349 0.6007 0.7629 0.7704 0.8367 0.0 0.0
11.4964 7.0 1043 10.0801 0.4098 0.5788 0.4432 0.4076 0.5423 -1.0 0.2558 0.3796 0.4805 0.4774 0.5626 -1.0 0.2016 0.3227 0.6587 0.7622 0.7792 0.8372 0.0 0.0
10.938 8.0 1192 9.6962 0.4168 0.5909 0.4511 0.4136 0.5736 -1.0 0.2622 0.384 0.4829 0.479 0.5953 -1.0 0.2148 0.3045 0.6771 0.7944 0.7753 0.8327 0.0 0.0
10.2185 9.0 1341 9.2201 0.4414 0.6237 0.4939 0.4461 0.4126 -1.0 0.2975 0.4088 0.5078 0.5043 0.5659 -1.0 0.3159 0.4023 0.6628 0.7886 0.7866 0.8403 0.0 0.0
10.1417 10.0 1490 8.8414 0.4258 0.5998 0.4616 0.432 0.4459 -1.0 0.2829 0.4079 0.5097 0.5112 0.5104 -1.0 0.2659 0.4256 0.6382 0.76 0.799 0.8533 0.0 0.0
9.6417 11.0 1639 8.9382 0.4158 0.5798 0.4758 0.4134 0.5169 -1.0 0.2758 0.401 0.5016 0.499 0.5324 -1.0 0.2131 0.3791 0.6644 0.7857 0.7857 0.8414 0.0 0.0
9.3618 12.0 1788 8.5653 0.4349 0.6074 0.5026 0.4337 0.5436 -1.0 0.2857 0.4042 0.5052 0.5022 0.5646 -1.0 0.2359 0.375 0.7111 0.8 0.7927 0.8458 0.0 0.0
9.1601 13.0 1937 8.5162 0.4346 0.6159 0.4669 0.4332 0.5417 -1.0 0.2803 0.3997 0.4998 0.497 0.5623 -1.0 0.2628 0.3795 0.6862 0.7778 0.7892 0.842 0.0 0.0
8.9938 14.0 2086 8.2598 0.4403 0.6165 0.4962 0.4379 0.5494 -1.0 0.2803 0.4002 0.5017 0.4986 0.5674 -1.0 0.2661 0.3773 0.7019 0.7806 0.7931 0.8489 0.0 0.0
8.7258 15.0 2235 8.2129 0.4507 0.6142 0.5192 0.4505 0.5363 -1.0 0.2931 0.4137 0.5149 0.5123 0.5611 -1.0 0.3076 0.4114 0.7154 0.8028 0.7796 0.8453 0.0 0.0
8.1655 16.0 2384 8.1459 0.4436 0.6071 0.4985 0.4455 0.4346 -1.0 0.2891 0.4125 0.5136 0.5134 0.5115 -1.0 0.3046 0.4091 0.6794 0.7946 0.7905 0.8507 0.0 0.0
8.1808 17.0 2533 8.1069 0.4426 0.6231 0.4971 0.4436 0.5167 -1.0 0.2868 0.4078 0.5074 0.5057 0.5667 -1.0 0.2985 0.4023 0.6942 0.7886 0.7776 0.8388 0.0 0.0
8.45 18.0 2682 7.9322 0.4443 0.6157 0.4739 0.4427 0.5757 -1.0 0.2839 0.4082 0.5104 0.5066 0.5963 -1.0 0.2715 0.4023 0.704 0.7833 0.8018 0.856 0.0 0.0
8.0344 19.0 2831 7.9556 0.4464 0.6133 0.4963 0.4456 0.5388 -1.0 0.2866 0.4113 0.5129 0.5111 0.5584 -1.0 0.2678 0.4093 0.722 0.7914 0.7956 0.851 0.0 0.0
7.9178 20.0 2980 7.7323 0.448 0.6146 0.4994 0.4453 0.5526 -1.0 0.286 0.4045 0.5073 0.5039 0.571 -1.0 0.2858 0.4068 0.7008 0.7649 0.8053 0.8576 0.0 0.0

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.3.1
  • Tokenizers 0.21.0