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convnext-small-224-leicester_binary
This model is a fine-tuned version of facebook/convnext-small-224 on the davanstrien/leicester_loaded_annotations_binary dataset. It achieves the following results on the evaluation set:
- Loss: 0.1283
- F1: 0.9620
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: 30.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
No log | 1.0 | 7 | 0.5143 | 0.8608 |
0.5872 | 2.0 | 14 | 0.4215 | 0.8608 |
0.3903 | 3.0 | 21 | 0.4127 | 0.8608 |
0.3903 | 4.0 | 28 | 0.3605 | 0.8608 |
0.3163 | 5.0 | 35 | 0.3152 | 0.8608 |
0.2942 | 6.0 | 42 | 0.2942 | 0.8608 |
0.2942 | 7.0 | 49 | 0.2669 | 0.8608 |
0.2755 | 8.0 | 56 | 0.2316 | 0.8608 |
0.2281 | 9.0 | 63 | 0.2104 | 0.8608 |
0.2076 | 10.0 | 70 | 0.1938 | 0.8608 |
0.2076 | 11.0 | 77 | 0.1803 | 0.8608 |
0.1832 | 12.0 | 84 | 0.1704 | 0.8608 |
0.1758 | 13.0 | 91 | 0.1650 | 0.8608 |
0.1758 | 14.0 | 98 | 0.1714 | 0.8608 |
0.167 | 15.0 | 105 | 0.1575 | 0.8608 |
0.1519 | 16.0 | 112 | 0.1549 | 0.8608 |
0.1519 | 17.0 | 119 | 0.1705 | 0.8608 |
0.1422 | 18.0 | 126 | 0.1478 | 0.8608 |
0.1444 | 19.0 | 133 | 0.1437 | 0.8608 |
0.1396 | 20.0 | 140 | 0.1398 | 0.8608 |
0.1396 | 21.0 | 147 | 0.1351 | 0.8608 |
0.1293 | 22.0 | 154 | 0.1370 | 0.8987 |
0.1361 | 23.0 | 161 | 0.1335 | 0.8987 |
0.1361 | 24.0 | 168 | 0.1311 | 0.9367 |
0.1246 | 25.0 | 175 | 0.1289 | 0.9620 |
0.1211 | 26.0 | 182 | 0.1283 | 0.9620 |
0.1211 | 27.0 | 189 | 0.1294 | 0.9620 |
0.1182 | 28.0 | 196 | 0.1306 | 0.9620 |
0.1172 | 29.0 | 203 | 0.1312 | 0.9620 |
0.1102 | 30.0 | 210 | 0.1318 | 0.9620 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2