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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: facebook/detr-resnet-50 |
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tags: |
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- image-regression |
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- human-movement |
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- vision |
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- generated_from_trainer |
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model-index: |
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- name: target_hold |
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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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# target_hold |
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This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the c14kevincardenas/beta_caller_284_target_hold dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8720 |
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- Iou: 0.0008 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 2014 |
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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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- lr_scheduler_warmup_steps: 250 |
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- num_epochs: 20.0 |
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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 | Iou | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 1.2348 | 1.0 | 100 | 1.1666 | 0.0001 | |
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| 1.0043 | 2.0 | 200 | 0.9816 | 0.0023 | |
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| 0.9101 | 3.0 | 300 | 0.9058 | 0.0020 | |
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| 0.8846 | 4.0 | 400 | 0.8883 | 0.0013 | |
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| 0.8755 | 5.0 | 500 | 0.8819 | 0.0011 | |
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| 0.8714 | 6.0 | 600 | 0.8789 | 0.0010 | |
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| 0.8684 | 7.0 | 700 | 0.8773 | 0.0009 | |
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| 0.8664 | 8.0 | 800 | 0.8764 | 0.0008 | |
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| 0.8677 | 9.0 | 900 | 0.8752 | 0.0009 | |
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| 0.863 | 10.0 | 1000 | 0.8747 | 0.0009 | |
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| 0.8619 | 11.0 | 1100 | 0.8737 | 0.0009 | |
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| 0.8637 | 12.0 | 1200 | 0.8732 | 0.0009 | |
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| 0.8632 | 13.0 | 1300 | 0.8730 | 0.0009 | |
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| 0.8581 | 14.0 | 1400 | 0.8727 | 0.0009 | |
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| 0.8615 | 15.0 | 1500 | 0.8724 | 0.0009 | |
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| 0.8604 | 16.0 | 1600 | 0.8724 | 0.0008 | |
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| 0.8606 | 17.0 | 1700 | 0.8720 | 0.0009 | |
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| 0.8592 | 18.0 | 1800 | 0.8720 | 0.0009 | |
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| 0.8621 | 19.0 | 1900 | 0.8720 | 0.0008 | |
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| 0.8629 | 20.0 | 2000 | 0.8720 | 0.0008 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.0+cu124 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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