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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- cd45rb |
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model-index: |
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- name: cdetr-r50-cd45rb-all-4ah |
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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-r50-cd45rb-all-4ah |
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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 the cd45rb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7969 |
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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: 8 |
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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: 20 |
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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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| 2.165 | 1.0 | 2303 | 2.0257 | |
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| 1.9843 | 2.0 | 4606 | 1.9742 | |
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| 1.9296 | 3.0 | 6909 | 1.9123 | |
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| 1.8949 | 4.0 | 9212 | 1.8928 | |
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| 1.8751 | 5.0 | 11515 | 1.9116 | |
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| 1.854 | 6.0 | 13818 | 1.8909 | |
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| 1.8354 | 7.0 | 16121 | 1.8533 | |
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| 1.8257 | 8.0 | 18424 | 1.8407 | |
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| 1.8101 | 9.0 | 20727 | 1.8453 | |
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| 1.8025 | 10.0 | 23030 | 1.8344 | |
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| 1.8177 | 11.0 | 25333 | 1.8496 | |
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| 1.8092 | 12.0 | 27636 | 1.8584 | |
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| 1.8016 | 13.0 | 29939 | 1.8277 | |
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| 1.7961 | 14.0 | 32242 | 1.8230 | |
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| 1.7853 | 15.0 | 34545 | 1.8130 | |
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| 1.7769 | 16.0 | 36848 | 1.8098 | |
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| 1.7708 | 17.0 | 39151 | 1.8030 | |
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| 1.7626 | 18.0 | 41454 | 1.7994 | |
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| 1.7596 | 19.0 | 43757 | 1.8018 | |
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| 1.7547 | 20.0 | 46060 | 1.7969 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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