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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cd45rb
model-index:
- name: detr-r50-cd45rb-8ah-6l
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# detr-r50-cd45rb-8ah-6l
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the cd45rb dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5794
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 2.4794 | 1.0 | 4606 | 1.8245 |
| 2.2469 | 2.0 | 9212 | 1.7593 |
| 2.1817 | 3.0 | 13818 | 1.7109 |
| 2.1418 | 4.0 | 18424 | 1.6976 |
| 2.118 | 5.0 | 23030 | 1.6695 |
| 2.1237 | 6.0 | 27636 | 1.6781 |
| 2.1025 | 7.0 | 32242 | 1.6574 |
| 2.0796 | 8.0 | 36848 | 1.6418 |
| 2.0672 | 9.0 | 41454 | 1.6333 |
| 2.0597 | 10.0 | 46060 | 1.6313 |
| 2.0948 | 11.0 | 50666 | 1.6546 |
| 2.0943 | 12.0 | 55272 | 1.6905 |
| 2.0819 | 13.0 | 59878 | 1.6430 |
| 2.0795 | 14.0 | 64484 | 1.6439 |
| 2.0566 | 15.0 | 69090 | 1.6449 |
| 2.0435 | 16.0 | 73696 | 1.6204 |
| 2.0375 | 17.0 | 78302 | 1.6195 |
| 2.032 | 18.0 | 82908 | 1.6128 |
| 2.0079 | 19.0 | 87514 | 1.6082 |
| 1.9985 | 20.0 | 92120 | 1.6037 |
| 1.9976 | 21.0 | 96726 | 1.6005 |
| 1.9887 | 22.0 | 101332 | 1.5969 |
| 1.9841 | 23.0 | 105938 | 1.5841 |
| 1.9763 | 24.0 | 110544 | 1.5826 |
| 1.9686 | 25.0 | 115150 | 1.5794 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3
|