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--- |
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license: apache-2.0 |
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base_model: facebook/detr-resnet-50 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: detr-r50-mist1-bg-8ah-4l |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# detr-r50-mist1-bg-8ah-4l |
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This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9274 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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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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| 4.4466 | 1.0 | 115 | 3.8127 | |
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| 3.85 | 2.0 | 230 | 3.8636 | |
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| 3.8198 | 3.0 | 345 | 3.6179 | |
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| 3.6799 | 4.0 | 460 | 3.4558 | |
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| 3.5806 | 5.0 | 575 | 3.2328 | |
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| 3.4958 | 6.0 | 690 | 3.3407 | |
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| 3.4662 | 7.0 | 805 | 3.1567 | |
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| 3.4295 | 8.0 | 920 | 3.0499 | |
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| 3.3977 | 9.0 | 1035 | 3.0460 | |
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| 3.3853 | 10.0 | 1150 | 3.0481 | |
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| 3.3608 | 11.0 | 1265 | 3.0337 | |
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| 3.2873 | 12.0 | 1380 | 3.0535 | |
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| 3.3164 | 13.0 | 1495 | 3.0140 | |
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| 3.2745 | 14.0 | 1610 | 3.0667 | |
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| 3.2691 | 15.0 | 1725 | 3.0134 | |
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| 3.2735 | 16.0 | 1840 | 3.0207 | |
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| 3.2718 | 17.0 | 1955 | 3.0004 | |
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| 3.2504 | 18.0 | 2070 | 3.1082 | |
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| 3.243 | 19.0 | 2185 | 2.9369 | |
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| 3.1669 | 20.0 | 2300 | 2.9596 | |
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| 3.1844 | 21.0 | 2415 | 2.9170 | |
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| 3.1979 | 22.0 | 2530 | 2.9344 | |
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| 3.1702 | 23.0 | 2645 | 2.9262 | |
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| 3.1738 | 24.0 | 2760 | 2.9251 | |
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| 3.1606 | 25.0 | 2875 | 2.9274 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.14.1 |
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