hushem_5x_beit_base_sgd_00001_fold3
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.5681
- Accuracy: 0.2558
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5838 | 1.0 | 28 | 1.5858 | 0.2558 |
| 1.5323 | 2.0 | 56 | 1.5850 | 0.2558 |
| 1.5483 | 3.0 | 84 | 1.5842 | 0.2558 |
| 1.4864 | 4.0 | 112 | 1.5834 | 0.2558 |
| 1.5286 | 5.0 | 140 | 1.5827 | 0.2558 |
| 1.5129 | 6.0 | 168 | 1.5819 | 0.2558 |
| 1.6083 | 7.0 | 196 | 1.5812 | 0.2558 |
| 1.5405 | 8.0 | 224 | 1.5806 | 0.2558 |
| 1.5045 | 9.0 | 252 | 1.5799 | 0.2558 |
| 1.4827 | 10.0 | 280 | 1.5793 | 0.2558 |
| 1.5466 | 11.0 | 308 | 1.5787 | 0.2558 |
| 1.502 | 12.0 | 336 | 1.5780 | 0.2558 |
| 1.5701 | 13.0 | 364 | 1.5775 | 0.2558 |
| 1.5522 | 14.0 | 392 | 1.5769 | 0.2558 |
| 1.6273 | 15.0 | 420 | 1.5763 | 0.2558 |
| 1.5496 | 16.0 | 448 | 1.5758 | 0.2558 |
| 1.5263 | 17.0 | 476 | 1.5753 | 0.2558 |
| 1.5326 | 18.0 | 504 | 1.5748 | 0.2558 |
| 1.5229 | 19.0 | 532 | 1.5744 | 0.2558 |
| 1.6308 | 20.0 | 560 | 1.5739 | 0.2558 |
| 1.5402 | 21.0 | 588 | 1.5734 | 0.2558 |
| 1.5767 | 22.0 | 616 | 1.5730 | 0.2558 |
| 1.546 | 23.0 | 644 | 1.5726 | 0.2558 |
| 1.4997 | 24.0 | 672 | 1.5722 | 0.2558 |
| 1.5699 | 25.0 | 700 | 1.5719 | 0.2558 |
| 1.5518 | 26.0 | 728 | 1.5715 | 0.2558 |
| 1.5078 | 27.0 | 756 | 1.5712 | 0.2558 |
| 1.509 | 28.0 | 784 | 1.5709 | 0.2558 |
| 1.5496 | 29.0 | 812 | 1.5706 | 0.2558 |
| 1.5569 | 30.0 | 840 | 1.5704 | 0.2558 |
| 1.5113 | 31.0 | 868 | 1.5701 | 0.2558 |
| 1.5157 | 32.0 | 896 | 1.5699 | 0.2558 |
| 1.5362 | 33.0 | 924 | 1.5696 | 0.2558 |
| 1.4946 | 34.0 | 952 | 1.5694 | 0.2558 |
| 1.6128 | 35.0 | 980 | 1.5692 | 0.2558 |
| 1.4515 | 36.0 | 1008 | 1.5691 | 0.2558 |
| 1.4956 | 37.0 | 1036 | 1.5689 | 0.2558 |
| 1.5189 | 38.0 | 1064 | 1.5688 | 0.2558 |
| 1.571 | 39.0 | 1092 | 1.5687 | 0.2558 |
| 1.549 | 40.0 | 1120 | 1.5685 | 0.2558 |
| 1.524 | 41.0 | 1148 | 1.5684 | 0.2558 |
| 1.5138 | 42.0 | 1176 | 1.5684 | 0.2558 |
| 1.4952 | 43.0 | 1204 | 1.5683 | 0.2558 |
| 1.5406 | 44.0 | 1232 | 1.5682 | 0.2558 |
| 1.6126 | 45.0 | 1260 | 1.5682 | 0.2558 |
| 1.5484 | 46.0 | 1288 | 1.5682 | 0.2558 |
| 1.5268 | 47.0 | 1316 | 1.5681 | 0.2558 |
| 1.4882 | 48.0 | 1344 | 1.5681 | 0.2558 |
| 1.5345 | 49.0 | 1372 | 1.5681 | 0.2558 |
| 1.5815 | 50.0 | 1400 | 1.5681 | 0.2558 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
microsoft/beit-base-patch16-224