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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: 2.3956 |
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- Map: 0.0065 |
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- Map 50: 0.0182 |
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- Map 75: 0.0036 |
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- Map Small: 0.0006 |
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- Map Medium: 0.014 |
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- Map Large: 0.007 |
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- Mar 1: 0.0123 |
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- Mar 10: 0.0366 |
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- Mar 100: 0.067 |
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- Mar Small: 0.0072 |
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- Mar Medium: 0.0388 |
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- Mar Large: 0.0714 |
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- Map Coverall: 0.0323 |
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- Mar 100 Coverall: 0.3018 |
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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: 0.0001 |
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- Mar 100 Gloves: 0.0165 |
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- Map Goggles: 0.0 |
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- Mar 100 Goggles: 0.0062 |
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- Map Mask: 0.0 |
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- Mar 100 Mask: 0.0107 |
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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: 5e-05 |
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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 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: 3 |
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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 | 2.6211 | 0.0025 | 0.0088 | 0.0008 | 0.0 | 0.008 | 0.0025 | 0.0098 | 0.0172 | 0.0569 | 0.0 | 0.0309 | 0.0621 | 0.0124 | 0.2802 | 0.0 | 0.0025 | 0.0 | 0.0004 | 0.0 | 0.0015 | 0.0 | 0.0 | |
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| No log | 2.0 | 214 | 2.4397 | 0.0058 | 0.0156 | 0.0032 | 0.0004 | 0.014 | 0.0062 | 0.0081 | 0.0352 | 0.0525 | 0.0098 | 0.0338 | 0.0524 | 0.0287 | 0.2297 | 0.0 | 0.0 | 0.0001 | 0.029 | 0.0 | 0.0 | 0.0 | 0.0036 | |
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| No log | 3.0 | 321 | 2.3956 | 0.0065 | 0.0182 | 0.0036 | 0.0006 | 0.014 | 0.007 | 0.0123 | 0.0366 | 0.067 | 0.0072 | 0.0388 | 0.0714 | 0.0323 | 0.3018 | 0.0 | 0.0 | 0.0001 | 0.0165 | 0.0 | 0.0062 | 0.0 | 0.0107 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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