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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/conditional-detr-resnet-50 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: detr_finetuned_cppe5 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# detr_finetuned_cppe5 |
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This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5826 |
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- Map: 0.0003 |
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- Map 50: 0.0007 |
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- Map 75: 0.0 |
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- Map Small: 0.0014 |
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- Map Medium: 0.0001 |
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- Map Large: 0.0 |
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- Mar 1: 0.0 |
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- Mar 10: 0.0021 |
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- Mar 100: 0.0075 |
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- Mar Small: 0.0118 |
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- Mar Medium: 0.0062 |
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- Mar Large: 0.01 |
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- Map Coverall: 0.0 |
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- Mar 100 Coverall: 0.0 |
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- Map Face Shield: 0.0 |
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- Mar 100 Face Shield: 0.0 |
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- Map Gloves: 0.0015 |
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- Mar 100 Gloves: 0.0375 |
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- Map Goggles: 0.0 |
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- Mar 100 Goggles: 0.0 |
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- Map Mask: 0.0 |
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- Mar 100 Mask: 0.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- num_epochs: 30 |
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### Training results |
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| 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 Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:| |
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| No log | 1.0 | 107 | 3.5856 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0061 | 0.0006 | 0.0065 | 0.0157 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0307 | |
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| No log | 2.0 | 214 | 3.7297 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0078 | 0.0097 | 0.011 | 0.0017 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0391 | |
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| No log | 3.0 | 321 | 3.8304 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0044 | 0.0 | 0.0032 | 0.0149 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0222 | |
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| No log | 4.0 | 428 | 3.6958 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0004 | 0.0071 | 0.0059 | 0.0105 | 0.0047 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0356 | |
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| 2.8722 | 5.0 | 535 | 4.0271 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0014 | 0.0 | 0.0017 | 0.0034 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0071 | |
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| 2.8722 | 6.0 | 642 | 3.6288 | 0.0 | 0.0001 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.001 | 0.0125 | 0.01 | 0.0159 | 0.014 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0627 | |
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| 2.8722 | 7.0 | 749 | 3.6254 | 0.0 | 0.0001 | 0.0 | 0.0001 | 0.0 | 0.0001 | 0.0 | 0.0005 | 0.0063 | 0.0105 | 0.0035 | 0.0132 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0312 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.8722 | 8.0 | 856 | 3.8407 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0016 | 0.0 | 0.0017 | 0.0043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.008 | |
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| 2.8722 | 9.0 | 963 | 3.6509 | 0.0 | 0.0002 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0009 | 0.0066 | 0.0072 | 0.007 | 0.0059 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.033 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5968 | 10.0 | 1070 | 3.6992 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0003 | 0.0033 | 0.0033 | 0.0041 | 0.0014 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0165 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5968 | 11.0 | 1177 | 3.6423 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0012 | 0.006 | 0.0006 | 0.0097 | 0.0085 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0298 | |
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| 2.5968 | 12.0 | 1284 | 3.5987 | 0.0005 | 0.0023 | 0.0 | 0.0019 | 0.0001 | 0.0 | 0.0002 | 0.0009 | 0.0077 | 0.0092 | 0.0066 | 0.0114 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0024 | 0.0384 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5968 | 13.0 | 1391 | 3.6200 | 0.0 | 0.0001 | 0.0 | 0.0005 | 0.0 | 0.0 | 0.0 | 0.0028 | 0.0076 | 0.0099 | 0.0077 | 0.0068 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0379 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5968 | 14.0 | 1498 | 3.7723 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0001 | 0.0 | 0.0003 | 0.0006 | 0.0044 | 0.0007 | 0.0044 | 0.0077 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0219 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5557 | 15.0 | 1605 | 3.6236 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0011 | 0.0081 | 0.0021 | 0.0099 | 0.0162 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0404 | |
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| 2.5557 | 16.0 | 1712 | 3.6496 | 0.0001 | 0.0002 | 0.0 | 0.0008 | 0.0003 | 0.0 | 0.0004 | 0.0017 | 0.0065 | 0.0059 | 0.0066 | 0.0077 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0326 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5557 | 17.0 | 1819 | 3.6098 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0009 | 0.0046 | 0.0007 | 0.0039 | 0.0105 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0232 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5557 | 18.0 | 1926 | 3.6017 | 0.0001 | 0.0003 | 0.0 | 0.0 | 0.0005 | 0.0 | 0.0004 | 0.0015 | 0.0061 | 0.0026 | 0.0069 | 0.0068 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0304 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5084 | 19.0 | 2033 | 3.5866 | 0.0003 | 0.0006 | 0.0004 | 0.0045 | 0.0002 | 0.0 | 0.0013 | 0.0029 | 0.0078 | 0.0066 | 0.0079 | 0.0095 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0014 | 0.0388 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5084 | 20.0 | 2140 | 3.6129 | 0.0002 | 0.0022 | 0.0 | 0.0008 | 0.0001 | 0.0 | 0.0001 | 0.0015 | 0.0073 | 0.0066 | 0.0069 | 0.0105 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0012 | 0.0366 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5084 | 21.0 | 2247 | 3.5974 | 0.0004 | 0.001 | 0.0 | 0.002 | 0.0002 | 0.0 | 0.0004 | 0.0033 | 0.0083 | 0.0099 | 0.0086 | 0.0077 | 0.0 | 0.0 | 0.0 | 0.0 | 0.002 | 0.0415 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5084 | 22.0 | 2354 | 3.5810 | 0.0 | 0.0002 | 0.0 | 0.0001 | 0.0001 | 0.0 | 0.0 | 0.0012 | 0.0075 | 0.0072 | 0.0069 | 0.0109 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0375 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.5084 | 23.0 | 2461 | 3.6132 | 0.0005 | 0.0013 | 0.0 | 0.0016 | 0.0002 | 0.0 | 0.0 | 0.0028 | 0.0077 | 0.0079 | 0.0079 | 0.0082 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0023 | 0.0384 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4812 | 24.0 | 2568 | 3.5863 | 0.0002 | 0.0022 | 0.0 | 0.0009 | 0.0001 | 0.0 | 0.0001 | 0.0018 | 0.0069 | 0.0079 | 0.007 | 0.0068 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0012 | 0.0344 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4812 | 25.0 | 2675 | 3.6469 | 0.0002 | 0.0022 | 0.0 | 0.0008 | 0.0001 | 0.0 | 0.0001 | 0.0018 | 0.007 | 0.0059 | 0.0076 | 0.0068 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0012 | 0.0348 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4812 | 26.0 | 2782 | 3.5896 | 0.0001 | 0.0006 | 0.0 | 0.0004 | 0.0001 | 0.0 | 0.0 | 0.0017 | 0.007 | 0.0099 | 0.0063 | 0.0082 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0004 | 0.0348 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4812 | 27.0 | 2889 | 3.5994 | 0.0001 | 0.0005 | 0.0 | 0.0007 | 0.0001 | 0.0 | 0.0004 | 0.0024 | 0.0074 | 0.0112 | 0.0066 | 0.0086 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0006 | 0.0371 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4812 | 28.0 | 2996 | 3.5806 | 0.0002 | 0.0006 | 0.0 | 0.0014 | 0.0001 | 0.0 | 0.0 | 0.0019 | 0.0072 | 0.0112 | 0.0058 | 0.0105 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0012 | 0.0362 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4512 | 29.0 | 3103 | 3.5821 | 0.0002 | 0.0006 | 0.0 | 0.0014 | 0.0001 | 0.0 | 0.0004 | 0.0023 | 0.0075 | 0.0118 | 0.0062 | 0.01 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0011 | 0.0375 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 2.4512 | 30.0 | 3210 | 3.5826 | 0.0003 | 0.0007 | 0.0 | 0.0014 | 0.0001 | 0.0 | 0.0 | 0.0021 | 0.0075 | 0.0118 | 0.0062 | 0.01 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0015 | 0.0375 | 0.0 | 0.0 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.55.4 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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