metadata
license: apache-2.0
base_model: kacper-cierzniewski/daigram_detr_r50_albumentations
tags:
- generated_from_trainer
datasets:
- bpmn-shapes
model-index:
- name: daigram_detr_r50_albumentations_finetuning
results: []
daigram_detr_r50_albumentations_finetuning
This model is a fine-tuned version of kacper-cierzniewski/daigram_detr_r50_albumentations on the bpmn-shapes dataset. It achieves the following results on the evaluation set:
- Loss: 0.9817
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9457 | 12.5 | 50 | 1.0238 |
| 0.9717 | 25.0 | 100 | 1.0411 |
| 0.9823 | 37.5 | 150 | 1.0269 |
| 0.9524 | 50.0 | 200 | 1.0518 |
| 0.9886 | 62.5 | 250 | 1.0548 |
| 0.9638 | 75.0 | 300 | 1.0454 |
| 0.948 | 87.5 | 350 | 1.0240 |
| 0.9312 | 100.0 | 400 | 1.0281 |
| 0.9183 | 112.5 | 450 | 1.0112 |
| 0.9219 | 125.0 | 500 | 1.0110 |
| 0.9285 | 137.5 | 550 | 1.0325 |
| 0.9177 | 150.0 | 600 | 1.0009 |
| 0.9323 | 162.5 | 650 | 1.0124 |
| 0.9333 | 175.0 | 700 | 1.0154 |
| 0.9386 | 187.5 | 750 | 1.0188 |
| 0.9586 | 200.0 | 800 | 0.9978 |
| 0.894 | 212.5 | 850 | 1.0087 |
| 0.8999 | 225.0 | 900 | 1.0055 |
| 0.9324 | 237.5 | 950 | 1.0185 |
| 0.9313 | 250.0 | 1000 | 0.9840 |
| 0.9177 | 262.5 | 1050 | 0.9785 |
| 0.8918 | 275.0 | 1100 | 0.9874 |
| 0.9145 | 287.5 | 1150 | 0.9802 |
| 0.89 | 300.0 | 1200 | 0.9879 |
| 0.8818 | 312.5 | 1250 | 0.9857 |
| 0.9256 | 325.0 | 1300 | 0.9951 |
| 0.9028 | 337.5 | 1350 | 1.0001 |
| 0.9252 | 350.0 | 1400 | 1.0033 |
| 0.9017 | 362.5 | 1450 | 0.9916 |
| 0.8783 | 375.0 | 1500 | 0.9858 |
| 0.911 | 387.5 | 1550 | 0.9758 |
| 0.8797 | 400.0 | 1600 | 0.9810 |
| 0.8995 | 412.5 | 1650 | 0.9840 |
| 0.8781 | 425.0 | 1700 | 0.9843 |
| 0.8897 | 437.5 | 1750 | 0.9745 |
| 0.905 | 450.0 | 1800 | 0.9825 |
| 0.8961 | 462.5 | 1850 | 0.9781 |
| 0.8865 | 475.0 | 1900 | 0.9781 |
| 0.8824 | 487.5 | 1950 | 0.9794 |
| 0.8836 | 500.0 | 2000 | 0.9817 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0