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--- |
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license: apache-2.0 |
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base_model: facebook/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-r50-mist1-bg-2ah-6l |
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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-r50-mist1-bg-2ah-6l |
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This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/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: 3.9051 |
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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: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 25 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 4.6721 | 1.0 | 115 | 5.0032 | |
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| 4.4438 | 2.0 | 230 | 4.6797 | |
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| 4.2953 | 3.0 | 345 | 4.7027 | |
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| 4.3899 | 4.0 | 460 | 5.4316 | |
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| 4.3184 | 5.0 | 575 | 4.4125 | |
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| 4.2749 | 6.0 | 690 | 4.1611 | |
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| 4.2153 | 7.0 | 805 | 4.6723 | |
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| 4.0788 | 8.0 | 920 | 4.1266 | |
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| 4.0752 | 9.0 | 1035 | 4.0529 | |
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| 4.0073 | 10.0 | 1150 | 4.4483 | |
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| 4.011 | 11.0 | 1265 | 4.2002 | |
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| 3.9993 | 12.0 | 1380 | 4.2450 | |
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| 4.0028 | 13.0 | 1495 | 4.1703 | |
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| 3.9572 | 14.0 | 1610 | 4.1861 | |
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| 3.9009 | 15.0 | 1725 | 4.0285 | |
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| 3.9173 | 16.0 | 1840 | 4.0673 | |
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| 3.8884 | 17.0 | 1955 | 3.9875 | |
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| 3.8415 | 18.0 | 2070 | 4.1062 | |
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| 3.8132 | 19.0 | 2185 | 4.0494 | |
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| 3.8297 | 20.0 | 2300 | 4.0119 | |
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| 3.8262 | 21.0 | 2415 | 3.9538 | |
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| 3.8045 | 22.0 | 2530 | 3.9500 | |
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| 3.8067 | 23.0 | 2645 | 3.9264 | |
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| 3.7651 | 24.0 | 2760 | 3.8820 | |
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| 3.756 | 25.0 | 2875 | 3.9051 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.14.1 |
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