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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: kacper-cierzniewski/daigram_detr_r50_albumentations
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - bpmn-shapes
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+ model-index:
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+ - name: daigram_detr_r50_albumentations_finetuning
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+ results: []
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+ ---
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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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+
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+ # daigram_detr_r50_albumentations_finetuning
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+
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+ This model is a fine-tuned version of [kacper-cierzniewski/daigram_detr_r50_albumentations](https://huggingface.co/kacper-cierzniewski/daigram_detr_r50_albumentations) on the bpmn-shapes dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9817
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 48
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+ - eval_batch_size: 48
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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: 500
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.9457 | 12.5 | 50 | 1.0238 |
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+ | 0.9717 | 25.0 | 100 | 1.0411 |
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+ | 0.9823 | 37.5 | 150 | 1.0269 |
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+ | 0.9524 | 50.0 | 200 | 1.0518 |
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+ | 0.9886 | 62.5 | 250 | 1.0548 |
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+ | 0.9638 | 75.0 | 300 | 1.0454 |
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+ | 0.948 | 87.5 | 350 | 1.0240 |
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+ | 0.9312 | 100.0 | 400 | 1.0281 |
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+ | 0.9183 | 112.5 | 450 | 1.0112 |
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+ | 0.9219 | 125.0 | 500 | 1.0110 |
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+ | 0.9285 | 137.5 | 550 | 1.0325 |
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+ | 0.9177 | 150.0 | 600 | 1.0009 |
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+ | 0.9323 | 162.5 | 650 | 1.0124 |
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+ | 0.9333 | 175.0 | 700 | 1.0154 |
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+ | 0.9386 | 187.5 | 750 | 1.0188 |
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+ | 0.9586 | 200.0 | 800 | 0.9978 |
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+ | 0.894 | 212.5 | 850 | 1.0087 |
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+ | 0.8999 | 225.0 | 900 | 1.0055 |
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+ | 0.9324 | 237.5 | 950 | 1.0185 |
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+ | 0.9313 | 250.0 | 1000 | 0.9840 |
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+ | 0.9177 | 262.5 | 1050 | 0.9785 |
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+ | 0.8918 | 275.0 | 1100 | 0.9874 |
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+ | 0.9145 | 287.5 | 1150 | 0.9802 |
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+ | 0.89 | 300.0 | 1200 | 0.9879 |
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+ | 0.8818 | 312.5 | 1250 | 0.9857 |
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+ | 0.9256 | 325.0 | 1300 | 0.9951 |
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+ | 0.9028 | 337.5 | 1350 | 1.0001 |
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+ | 0.9252 | 350.0 | 1400 | 1.0033 |
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+ | 0.9017 | 362.5 | 1450 | 0.9916 |
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+ | 0.8783 | 375.0 | 1500 | 0.9858 |
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+ | 0.911 | 387.5 | 1550 | 0.9758 |
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+ | 0.8797 | 400.0 | 1600 | 0.9810 |
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+ | 0.8995 | 412.5 | 1650 | 0.9840 |
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+ | 0.8781 | 425.0 | 1700 | 0.9843 |
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+ | 0.8897 | 437.5 | 1750 | 0.9745 |
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+ | 0.905 | 450.0 | 1800 | 0.9825 |
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+ | 0.8961 | 462.5 | 1850 | 0.9781 |
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+ | 0.8865 | 475.0 | 1900 | 0.9781 |
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+ | 0.8824 | 487.5 | 1950 | 0.9794 |
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+ | 0.8836 | 500.0 | 2000 | 0.9817 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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