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vit-base-patch32-224-in21-leicester_binary
This model is a fine-tuned version of google/vit-base-patch32-224-in21k on the davanstrien/leicester_loaded_annotations_binary dataset. It achieves the following results on the evaluation set:
- Loss: 0.0628
- F1: 0.9873
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 7 | 0.4529 | 0.8608 |
| 0.5024 | 2.0 | 14 | 0.3989 | 0.8608 |
| 0.3533 | 3.0 | 21 | 0.3741 | 0.8608 |
| 0.3533 | 4.0 | 28 | 0.3161 | 0.8608 |
| 0.285 | 5.0 | 35 | 0.2824 | 0.8608 |
| 0.2491 | 6.0 | 42 | 0.2701 | 0.8608 |
| 0.2491 | 7.0 | 49 | 0.2062 | 0.9114 |
| 0.2032 | 8.0 | 56 | 0.2050 | 0.9494 |
| 0.157 | 9.0 | 63 | 0.2013 | 0.9494 |
| 0.1127 | 10.0 | 70 | 0.1960 | 0.9367 |
| 0.1127 | 11.0 | 77 | 0.1417 | 0.9494 |
| 0.0903 | 12.0 | 84 | 0.1307 | 0.9494 |
| 0.0922 | 13.0 | 91 | 0.0870 | 0.9873 |
| 0.0922 | 14.0 | 98 | 0.2048 | 0.9241 |
| 0.0595 | 15.0 | 105 | 0.1204 | 0.9620 |
| 0.0527 | 16.0 | 112 | 0.2553 | 0.9367 |
| 0.0527 | 17.0 | 119 | 0.1675 | 0.9367 |
| 0.0477 | 18.0 | 126 | 0.2265 | 0.9241 |
| 0.0411 | 19.0 | 133 | 0.1901 | 0.9367 |
| 0.0299 | 20.0 | 140 | 0.2423 | 0.9241 |
| 0.0299 | 21.0 | 147 | 0.0639 | 0.9873 |
| 0.0487 | 22.0 | 154 | 0.1255 | 0.9494 |
| 0.0359 | 23.0 | 161 | 0.1213 | 0.9494 |
| 0.0359 | 24.0 | 168 | 0.0727 | 0.9747 |
| 0.0302 | 25.0 | 175 | 0.1116 | 0.9494 |
| 0.0304 | 26.0 | 182 | 0.1062 | 0.9494 |
| 0.0304 | 27.0 | 189 | 0.2097 | 0.9241 |
| 0.0274 | 28.0 | 196 | 0.1276 | 0.9494 |
| 0.0291 | 29.0 | 203 | 0.0967 | 0.9494 |
| 0.0202 | 30.0 | 210 | 0.0765 | 0.9747 |
| 0.0202 | 31.0 | 217 | 0.0628 | 0.9873 |
| 0.0232 | 32.0 | 224 | 0.1388 | 0.9494 |
| 0.0264 | 33.0 | 231 | 0.1062 | 0.9494 |
| 0.0264 | 34.0 | 238 | 0.1320 | 0.9494 |
| 0.0219 | 35.0 | 245 | 0.1528 | 0.9494 |
| 0.0194 | 36.0 | 252 | 0.1746 | 0.9494 |
| 0.0194 | 37.0 | 259 | 0.1609 | 0.9494 |
| 0.0204 | 38.0 | 266 | 0.1482 | 0.9494 |
| 0.0217 | 39.0 | 273 | 0.1522 | 0.9494 |
| 0.0216 | 40.0 | 280 | 0.1499 | 0.9494 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
