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---
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-50-dc5
tags:
- generated_from_trainer
model-index:
- name: facebook/detr-resnet-50-dc5
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. -->
# facebook/detr-resnet-50-dc5
This model is a fine-tuned version of [facebook/detr-resnet-50-dc5](https://huggingface.co/facebook/detr-resnet-50-dc5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7887
- Map: 0.55
- Map 50: 0.6825
- Map 75: 0.5932
- Map Small: 0.0
- Map Medium: 0.5352
- Map Large: 0.7531
- Mar 1: 0.1882
- Mar 10: 0.6735
- Mar 100: 0.7588
- Mar Small: 0.0
- Mar Medium: 0.7158
- Mar Large: 0.9385
- Map Object: -1.0
- Mar 100 Object: -1.0
- Map Balloon: 0.55
- Mar 100 Balloon: 0.7588
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 125
- mixed_precision_training: Native AMP
### Training results
| 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 Object | Mar 100 Object | Map Balloon | Mar 100 Balloon |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:----------:|:--------------:|:-----------:|:---------------:|
| 2.1236 | 0.7692 | 10 | 1.3396 | 0.0768 | 0.1002 | 0.0897 | 0.0 | 0.0966 | 0.1387 | 0.0765 | 0.3735 | 0.5647 | 0.0 | 0.3789 | 0.9231 | -1.0 | -1.0 | 0.0768 | 0.5647 |
| 1.5088 | 1.5385 | 20 | 1.2730 | 0.1472 | 0.1875 | 0.1691 | 0.0 | 0.1297 | 0.2723 | 0.1059 | 0.3647 | 0.6618 | 0.0 | 0.5684 | 0.9 | -1.0 | -1.0 | 0.1472 | 0.6618 |
| 1.3182 | 2.3077 | 30 | 1.2273 | 0.1816 | 0.2322 | 0.1918 | 0.0 | 0.2368 | 0.3423 | 0.1088 | 0.3941 | 0.6647 | 0.0 | 0.6053 | 0.8538 | -1.0 | -1.0 | 0.1816 | 0.6647 |
| 1.365 | 3.0769 | 40 | 1.0452 | 0.2476 | 0.3019 | 0.2823 | 0.0 | 0.3035 | 0.4146 | 0.1118 | 0.4882 | 0.7559 | 0.0 | 0.7158 | 0.9308 | -1.0 | -1.0 | 0.2476 | 0.7559 |
| 1.2013 | 3.8462 | 50 | 0.9825 | 0.3006 | 0.3891 | 0.3233 | 0.0 | 0.3747 | 0.496 | 0.1324 | 0.5265 | 0.7324 | 0.0 | 0.6737 | 0.9308 | -1.0 | -1.0 | 0.3006 | 0.7324 |
| 1.3605 | 4.6154 | 60 | 0.9307 | 0.3655 | 0.4809 | 0.4024 | 0.0 | 0.3706 | 0.5922 | 0.1324 | 0.5471 | 0.7294 | 0.0 | 0.6684 | 0.9308 | -1.0 | -1.0 | 0.3655 | 0.7294 |
| 1.0117 | 5.3846 | 70 | 0.8867 | 0.3834 | 0.5044 | 0.4222 | 0.0 | 0.4086 | 0.5963 | 0.1294 | 0.5882 | 0.7324 | 0.0 | 0.6737 | 0.9308 | -1.0 | -1.0 | 0.3834 | 0.7324 |
| 1.1224 | 6.1538 | 80 | 0.8413 | 0.478 | 0.6138 | 0.5427 | 0.0 | 0.472 | 0.7053 | 0.1676 | 0.6265 | 0.7529 | 0.0 | 0.7053 | 0.9385 | -1.0 | -1.0 | 0.478 | 0.7529 |
| 1.0109 | 6.9231 | 90 | 0.8210 | 0.5281 | 0.6515 | 0.5817 | 0.0 | 0.5391 | 0.7497 | 0.1559 | 0.6441 | 0.7735 | 0.0 | 0.7316 | 0.9538 | -1.0 | -1.0 | 0.5281 | 0.7735 |
| 1.0771 | 7.6923 | 100 | 0.8153 | 0.5506 | 0.6859 | 0.604 | 0.0 | 0.5638 | 0.7373 | 0.1794 | 0.6618 | 0.7676 | 0.0 | 0.7263 | 0.9462 | -1.0 | -1.0 | 0.5506 | 0.7676 |
| 0.9122 | 8.4615 | 110 | 0.7948 | 0.5551 | 0.6839 | 0.6097 | 0.0 | 0.5603 | 0.7503 | 0.1853 | 0.6618 | 0.7824 | 0.0 | 0.7526 | 0.9462 | -1.0 | -1.0 | 0.5551 | 0.7824 |
| 0.9918 | 9.2308 | 120 | 0.7887 | 0.55 | 0.6825 | 0.5932 | 0.0 | 0.5352 | 0.7531 | 0.1882 | 0.6735 | 0.7588 | 0.0 | 0.7158 | 0.9385 | -1.0 | -1.0 | 0.55 | 0.7588 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
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