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---
license: apache-2.0
base_model: qgyd2021/detr_cppe5_object_detection
tags:
- generated_from_trainer
datasets:
- cppe5
model-index:
- name: detr_cppe5_object_detection
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_cppe5_object_detection
This model is a fine-tuned version of [qgyd2021/detr_cppe5_object_detection](https://huggingface.co/qgyd2021/detr_cppe5_object_detection) on the cppe5 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1300
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8224 | 3.17 | 200 | 1.0183 |
| 0.8185 | 6.35 | 400 | 1.0975 |
| 0.7584 | 9.52 | 600 | 1.0917 |
| 0.7272 | 12.7 | 800 | 1.0980 |
| 0.7481 | 15.87 | 1000 | 1.1201 |
| 0.7586 | 19.05 | 1200 | 1.1300 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
|