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--- |
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license: apache-2.0 |
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base_model: microsoft/conditional-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: cdetr-mist1-brain-gt-tumors-8ah-6l |
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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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# cdetr-mist1-brain-gt-tumors-8ah-6l |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8303 |
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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: 50 |
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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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| 5.4149 | 1.0 | 115 | 4.3974 | |
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| 3.9453 | 2.0 | 230 | 3.6520 | |
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| 3.7269 | 3.0 | 345 | 3.7602 | |
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| 3.5898 | 4.0 | 460 | 3.5671 | |
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| 3.486 | 5.0 | 575 | 3.4912 | |
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| 3.4073 | 6.0 | 690 | 3.4095 | |
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| 3.4181 | 7.0 | 805 | 3.3183 | |
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| 3.3603 | 8.0 | 920 | 3.1111 | |
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| 3.2777 | 9.0 | 1035 | 3.1992 | |
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| 3.2851 | 10.0 | 1150 | 3.3997 | |
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| 3.266 | 11.0 | 1265 | 3.2861 | |
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| 3.2803 | 12.0 | 1380 | 3.1813 | |
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| 3.1733 | 13.0 | 1495 | 2.9838 | |
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| 3.2094 | 14.0 | 1610 | 3.1175 | |
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| 3.1718 | 15.0 | 1725 | 3.0064 | |
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| 3.1303 | 16.0 | 1840 | 3.0869 | |
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| 3.0897 | 17.0 | 1955 | 3.0306 | |
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| 3.0233 | 18.0 | 2070 | 2.9479 | |
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| 3.0156 | 19.0 | 2185 | 2.9145 | |
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| 3.0277 | 20.0 | 2300 | 2.8919 | |
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| 3.0847 | 21.0 | 2415 | 2.9321 | |
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| 3.0333 | 22.0 | 2530 | 2.9128 | |
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| 3.0126 | 23.0 | 2645 | 2.8627 | |
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| 2.9968 | 24.0 | 2760 | 3.0186 | |
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| 3.0295 | 25.0 | 2875 | 3.0148 | |
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| 3.0294 | 26.0 | 2990 | 3.0341 | |
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| 3.0395 | 27.0 | 3105 | 2.9997 | |
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| 3.0445 | 28.0 | 3220 | 3.0575 | |
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| 2.9761 | 29.0 | 3335 | 2.9707 | |
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| 3.0075 | 30.0 | 3450 | 2.9392 | |
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| 3.0198 | 31.0 | 3565 | 2.9122 | |
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| 2.9782 | 32.0 | 3680 | 2.9471 | |
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| 2.9773 | 33.0 | 3795 | 3.0306 | |
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| 2.9528 | 34.0 | 3910 | 2.8513 | |
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| 2.9228 | 35.0 | 4025 | 2.8997 | |
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| 2.9221 | 36.0 | 4140 | 2.8646 | |
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| 2.8933 | 37.0 | 4255 | 2.8871 | |
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| 2.8925 | 38.0 | 4370 | 2.9407 | |
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| 2.9069 | 39.0 | 4485 | 2.9625 | |
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| 2.9246 | 40.0 | 4600 | 2.9946 | |
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| 2.9089 | 41.0 | 4715 | 2.8936 | |
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| 2.8573 | 42.0 | 4830 | 2.8272 | |
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| 2.8378 | 43.0 | 4945 | 2.8543 | |
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| 2.8957 | 44.0 | 5060 | 2.8590 | |
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| 2.8454 | 45.0 | 5175 | 2.8525 | |
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| 2.7964 | 46.0 | 5290 | 2.8658 | |
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| 2.8172 | 47.0 | 5405 | 2.8872 | |
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| 2.8472 | 48.0 | 5520 | 2.8654 | |
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| 2.811 | 49.0 | 5635 | 2.8572 | |
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| 2.801 | 50.0 | 5750 | 2.8303 | |
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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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