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Rtdetr v2 R50 Cppe5 Finetune 2

This model is a fine-tuned version of PekingU/rtdetrv2r50vd on an unknown dataset. It achieves the following results on the evaluation set: evalloss: 56.8776 evalmap: 0.0016 evalmap50: 0.0033 evalmap75: 0.0013...

KindOtherBase modelPekingU/rtdetr_v2_r50vdVersionRevision 27657baCgrade

Model source

Kind
Other
File size
164 MB
Base model
PekingU/rtdetr_v2_r50vd
Version
vRevision 27657ba
Updated
Sep 16, 2026
Downloads
5
Source
Hugging Face

Source description

rtdetr-v2-r50-cppe5-finetune-2

This model is a fine-tuned version of PekingU/rtdetr_v2_r50vd on an unknown dataset. It achieves the following results on the evaluation set:

  • eval_loss: 56.8776
  • eval_map: 0.0016
  • eval_map_50: 0.0033
  • eval_map_75: 0.0013
  • eval_map_small: 0.0001
  • eval_map_medium: 0.002
  • eval_map_large: 0.0141
  • eval_mar_1: 0.0047
  • eval_mar_10: 0.0217
  • eval_mar_100: 0.0874
  • eval_mar_small: 0.0102
  • eval_mar_medium: 0.0588
  • eval_mar_large: 0.1563
  • eval_map_Coverall: 0.0002
  • eval_mar_100_Coverall: 0.0821
  • eval_map_Face_Shield: 0.0055
  • eval_mar_100_Face_Shield: 0.1176
  • eval_map_Gloves: 0.002
  • eval_mar_100_Gloves: 0.1983
  • eval_map_Goggles: 0.0
  • eval_mar_100_Goggles: 0.0
  • eval_map_Mask: 0.0002
  • eval_mar_100_Mask: 0.0392
  • eval_runtime: 65.4375
  • eval_samples_per_second: 0.443
  • eval_steps_per_second: 0.061
  • epoch: 0.0748
  • step: 8

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 300
  • num_epochs: 40

Framework versions

  • Transformers 5.12.1
  • Pytorch 2.12.1+cu130
  • Datasets 5.0.0
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrimaryVersion 27657ba49bff7e35a157c5762e4e0a8094f12728
huggingface.co/AmanyAzzam/rtdetr-v2-r50-cppe5-finetune-2/tree/27657ba49bff7e35a157c5762e4e0a8094f12728

Verified Sep 2

Model artifacts

1 artifact

model.safetensors

safetensors · 164 MB · SHA-256 5b6c9cb55781…59f6 · Hugging Face

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Source excerpts

2 excerpts

--- library_name: transformers license: apache-2.0 base_model: PekingU/rtdetr_v2_r50vd tags: - generated_from_trainer model-index: - name: rtdetr-v2-r50-cppe5-finetune-2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # rtdetr-v2-r50-cppe5-finetune-2 This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 56.8776 - eval_map: 0.0016 - eval_map_50: 0.0033 - eval_map_75: 0.0013 - eval_map_small: 0.0001 - eval_map_medium: 0.002 - eval_map_large: 0.0141 - eval_mar_1: 0.0047 - eval_mar_10: 0.0217 - eval_mar_100: 0.0874 - eval_mar_small: 0.0102 - eval_mar_medium: 0.0588 - eval_mar_large: 0.1563 - eval_map_Coverall: 0.0002 - eval_mar_100_Coverall: 0.0821 - eval_map_Face_Shield: 0.0055 - eval_mar_100_Face_Shield: 0.1176 - eval_map_Gloves: 0.002 - eval_mar_100_Gloves: 0.1983 - eval_map_Goggles: 0.0 - eval_mar_100_Goggles: 0.0 - eval_map_Mask: 0.0002 - eval_mar_100_Mask: 0.0392 - eval_runtime: 65.4375 - eval_samples_per_second: 0.443 - eval_steps_per_second: 0.061 - epoch: 0.0748 - step: 8 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 300 - num_epochs: 40 ### Framework versions - Transformers 5.12.1 - Pytorch 2.12.1+cu130 - Datasets 5.0.0 - Tokenizers 0.22.2

Source context: 5 downloads · 0 likes · Pipeline object-detection · Library transformers · Repo AmanyAzzam/rtdetr-v2-r50-cppe5-finetune-2