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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: detr-r50-cd45rb-8ah-6l-gelu-corrected |
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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-cd45rb-8ah-6l-gelu-corrected |
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This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/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: 1.5992 |
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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: 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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| 3.0438 | 1.0 | 4606 | 1.9413 | |
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| 2.3933 | 2.0 | 9212 | 1.8238 | |
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| 2.2782 | 3.0 | 13818 | 1.7718 | |
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| 2.2383 | 4.0 | 18424 | 1.7528 | |
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| 2.2046 | 5.0 | 23030 | 1.7265 | |
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| 2.1659 | 6.0 | 27636 | 1.7125 | |
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| 2.1457 | 7.0 | 32242 | 1.6760 | |
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| 2.1111 | 8.0 | 36848 | 1.6622 | |
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| 2.0959 | 9.0 | 41454 | 1.6467 | |
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| 2.0826 | 10.0 | 46060 | 1.6392 | |
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| 2.1132 | 11.0 | 50666 | 1.6875 | |
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| 2.1145 | 12.0 | 55272 | 1.6863 | |
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| 2.0947 | 13.0 | 59878 | 1.6528 | |
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| 2.0777 | 14.0 | 64484 | 1.6669 | |
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| 2.0551 | 15.0 | 69090 | 1.6241 | |
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| 2.0567 | 16.0 | 73696 | 1.6241 | |
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| 2.042 | 17.0 | 78302 | 1.6171 | |
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| 2.0306 | 18.0 | 82908 | 1.6062 | |
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| 2.015 | 19.0 | 87514 | 1.5989 | |
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| 2.0084 | 20.0 | 92120 | 1.5992 | |
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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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