hushem_1x_beit_base_rms_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: 0.5862
- Accuracy: 0.8372
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.3652 | 0.2558 |
| 1.4655 | 2.0 | 12 | 0.9320 | 0.6512 |
| 1.4655 | 3.0 | 18 | 0.5733 | 0.7907 |
| 0.6613 | 4.0 | 24 | 0.3842 | 0.8605 |
| 0.1719 | 5.0 | 30 | 0.4268 | 0.8605 |
| 0.1719 | 6.0 | 36 | 0.3122 | 0.8837 |
| 0.0362 | 7.0 | 42 | 0.5635 | 0.7907 |
| 0.0362 | 8.0 | 48 | 0.2839 | 0.8837 |
| 0.0103 | 9.0 | 54 | 0.3515 | 0.9070 |
| 0.0048 | 10.0 | 60 | 0.4717 | 0.8837 |
| 0.0048 | 11.0 | 66 | 0.4775 | 0.8372 |
| 0.0038 | 12.0 | 72 | 0.5321 | 0.7907 |
| 0.0038 | 13.0 | 78 | 0.4659 | 0.8372 |
| 0.0022 | 14.0 | 84 | 0.5318 | 0.8140 |
| 0.0017 | 15.0 | 90 | 0.5328 | 0.8605 |
| 0.0017 | 16.0 | 96 | 0.4991 | 0.8372 |
| 0.0025 | 17.0 | 102 | 0.5203 | 0.8372 |
| 0.0025 | 18.0 | 108 | 0.5439 | 0.8372 |
| 0.0011 | 19.0 | 114 | 0.5049 | 0.8372 |
| 0.0014 | 20.0 | 120 | 0.5023 | 0.8372 |
| 0.0014 | 21.0 | 126 | 0.5748 | 0.8372 |
| 0.0013 | 22.0 | 132 | 0.5341 | 0.8372 |
| 0.0013 | 23.0 | 138 | 0.4866 | 0.8372 |
| 0.0011 | 24.0 | 144 | 0.5270 | 0.8372 |
| 0.0012 | 25.0 | 150 | 0.5889 | 0.8372 |
| 0.0012 | 26.0 | 156 | 0.6180 | 0.8372 |
| 0.0013 | 27.0 | 162 | 0.6227 | 0.8372 |
| 0.0013 | 28.0 | 168 | 0.6125 | 0.8372 |
| 0.0007 | 29.0 | 174 | 0.5708 | 0.8605 |
| 0.0004 | 30.0 | 180 | 0.5729 | 0.8372 |
| 0.0004 | 31.0 | 186 | 0.5789 | 0.8372 |
| 0.001 | 32.0 | 192 | 0.5842 | 0.8140 |
| 0.001 | 33.0 | 198 | 0.5989 | 0.8372 |
| 0.0008 | 34.0 | 204 | 0.5775 | 0.8140 |
| 0.0013 | 35.0 | 210 | 0.5738 | 0.8372 |
| 0.0013 | 36.0 | 216 | 0.5742 | 0.8140 |
| 0.0006 | 37.0 | 222 | 0.6172 | 0.8140 |
| 0.0006 | 38.0 | 228 | 0.5958 | 0.8140 |
| 0.0026 | 39.0 | 234 | 0.5884 | 0.8140 |
| 0.0006 | 40.0 | 240 | 0.5885 | 0.8140 |
| 0.0006 | 41.0 | 246 | 0.5863 | 0.8372 |
| 0.0008 | 42.0 | 252 | 0.5862 | 0.8372 |
| 0.0008 | 43.0 | 258 | 0.5862 | 0.8372 |
| 0.0006 | 44.0 | 264 | 0.5862 | 0.8372 |
| 0.0004 | 45.0 | 270 | 0.5862 | 0.8372 |
| 0.0004 | 46.0 | 276 | 0.5862 | 0.8372 |
| 0.0006 | 47.0 | 282 | 0.5862 | 0.8372 |
| 0.0006 | 48.0 | 288 | 0.5862 | 0.8372 |
| 0.0005 | 49.0 | 294 | 0.5862 | 0.8372 |
| 0.0004 | 50.0 | 300 | 0.5862 | 0.8372 |
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