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detr-r50-cd45rb-2ah-6l-corrected

Object Detection
Transformers
PyTorch
detr
Generated from Trainer
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update model card README.md

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  1. README.md +29 -19
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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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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 cd45rb_nan_xywh dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.8243
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  ## Model description
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@@ -41,28 +41,38 @@ The following hyperparameters were used during training:
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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: 15
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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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- | 3.4312 | 1.0 | 4606 | 2.4426 |
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- | 2.9035 | 2.0 | 9212 | 2.1671 |
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- | 2.6788 | 3.0 | 13818 | 2.0925 |
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- | 2.5847 | 4.0 | 18424 | 2.0215 |
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- | 2.5075 | 5.0 | 23030 | 1.9689 |
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- | 2.445 | 6.0 | 27636 | 1.9528 |
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- | 2.4078 | 7.0 | 32242 | 1.9058 |
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- | 2.3794 | 8.0 | 36848 | 1.8889 |
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- | 2.3572 | 9.0 | 41454 | 1.8751 |
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- | 2.3374 | 10.0 | 46060 | 1.8623 |
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- | 2.3423 | 11.0 | 50666 | 1.8636 |
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- | 2.3292 | 12.0 | 55272 | 1.8500 |
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- | 2.3078 | 13.0 | 59878 | 1.8354 |
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- | 2.2958 | 14.0 | 64484 | 1.8350 |
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- | 2.2779 | 15.0 | 69090 | 1.8243 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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 cd45rb_nan_xywh dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7676
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  ## Model description
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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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+ | 3.4312 | 1.0 | 4606 | 2.4426 |
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+ | 2.9035 | 2.0 | 9212 | 2.1671 |
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+ | 2.6788 | 3.0 | 13818 | 2.0925 |
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+ | 2.5847 | 4.0 | 18424 | 2.0215 |
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+ | 2.5075 | 5.0 | 23030 | 1.9689 |
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+ | 2.445 | 6.0 | 27636 | 1.9528 |
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+ | 2.4078 | 7.0 | 32242 | 1.9058 |
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+ | 2.3794 | 8.0 | 36848 | 1.8889 |
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+ | 2.3572 | 9.0 | 41454 | 1.8751 |
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+ | 2.3374 | 10.0 | 46060 | 1.8623 |
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+ | 2.3423 | 11.0 | 50666 | 1.8636 |
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+ | 2.3292 | 12.0 | 55272 | 1.8500 |
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+ | 2.3078 | 13.0 | 59878 | 1.8354 |
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+ | 2.2958 | 14.0 | 64484 | 1.8350 |
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+ | 2.2779 | 15.0 | 69090 | 1.8243 |
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+ | 2.3118 | 16.0 | 73696 | 1.8304 |
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+ | 2.2927 | 17.0 | 78302 | 1.8243 |
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+ | 2.2726 | 18.0 | 82908 | 1.8161 |
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+ | 2.2546 | 19.0 | 87514 | 1.8106 |
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+ | 2.2394 | 20.0 | 92120 | 1.7949 |
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+ | 2.237 | 21.0 | 96726 | 1.7747 |
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+ | 2.2158 | 22.0 | 101332 | 1.7796 |
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+ | 2.2069 | 23.0 | 105938 | 1.7757 |
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+ | 2.2061 | 24.0 | 110544 | 1.7746 |
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+ | 2.1974 | 25.0 | 115150 | 1.7676 |
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  ### Framework versions