| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: microsoft/conditional-detr-resnet-50 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: detr_finetuned_cppe5 |
| 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_finetuned_cppe5 |
|
|
| This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1909 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - num_epochs: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | No log | 1.0 | 107 | 1.9270 | |
| | No log | 2.0 | 214 | 1.7725 | |
| | No log | 3.0 | 321 | 1.6696 | |
| | No log | 4.0 | 428 | 1.6196 | |
| | 2.6515 | 5.0 | 535 | 1.5855 | |
| | 2.6515 | 6.0 | 642 | 1.5091 | |
| | 2.6515 | 7.0 | 749 | 1.4790 | |
| | 2.6515 | 8.0 | 856 | 1.4786 | |
| | 2.6515 | 9.0 | 963 | 1.3819 | |
| | 1.3311 | 10.0 | 1070 | 1.3668 | |
| | 1.3311 | 11.0 | 1177 | 1.3966 | |
| | 1.3311 | 12.0 | 1284 | 1.3492 | |
| | 1.3311 | 13.0 | 1391 | 1.3223 | |
| | 1.3311 | 14.0 | 1498 | 1.2781 | |
| | 1.1672 | 15.0 | 1605 | 1.2749 | |
| | 1.1672 | 16.0 | 1712 | 1.2671 | |
| | 1.1672 | 17.0 | 1819 | 1.2488 | |
| | 1.1672 | 18.0 | 1926 | 1.2500 | |
| | 1.0429 | 19.0 | 2033 | 1.2274 | |
| | 1.0429 | 20.0 | 2140 | 1.2308 | |
| | 1.0429 | 21.0 | 2247 | 1.2249 | |
| | 1.0429 | 22.0 | 2354 | 1.2157 | |
| | 1.0429 | 23.0 | 2461 | 1.2147 | |
| | 0.9595 | 24.0 | 2568 | 1.1956 | |
| | 0.9595 | 25.0 | 2675 | 1.1880 | |
| | 0.9595 | 26.0 | 2782 | 1.1912 | |
| | 0.9595 | 27.0 | 2889 | 1.1916 | |
| | 0.9595 | 28.0 | 2996 | 1.1921 | |
| | 0.9097 | 29.0 | 3103 | 1.1912 | |
| | 0.9097 | 30.0 | 3210 | 1.1909 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.2 |
| - Pytorch 2.8.0 |
| - Datasets 4.1.1 |
| - Tokenizers 0.22.1 |
| |
