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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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<!-- 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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# daigram_detr_r50_albumentations_finetuning |
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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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## 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: 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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### Training results |
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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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### Framework versions |
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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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