convnext_flyswot
This model is a fine-tuned version of facebook/convnext-base-224-22k on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1441
- F1: 0.9592
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: 32
- eval_batch_size: 32
- seed: 666
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 52 | 0.6833 | 0.7484 |
| No log | 2.0 | 104 | 0.3666 | 0.8750 |
| No log | 3.0 | 156 | 0.2090 | 0.9321 |
| No log | 4.0 | 208 | 0.1478 | 0.9449 |
| No log | 5.0 | 260 | 0.1002 | 0.9518 |
| No log | 6.0 | 312 | 0.1053 | 0.9506 |
| No log | 7.0 | 364 | 0.1182 | 0.9616 |
| No log | 8.0 | 416 | 0.1102 | 0.9592 |
| No log | 9.0 | 468 | 0.1262 | 0.9616 |
| 0.203 | 10.0 | 520 | 0.1286 | 0.9616 |
| 0.203 | 11.0 | 572 | 0.1355 | 0.9592 |
| 0.203 | 12.0 | 624 | 0.1299 | 0.9592 |
| 0.203 | 13.0 | 676 | 0.1154 | 0.9592 |
| 0.203 | 14.0 | 728 | 0.1385 | 0.9580 |
| 0.203 | 15.0 | 780 | 0.1330 | 0.9592 |
| 0.203 | 16.0 | 832 | 0.1390 | 0.9592 |
| 0.203 | 17.0 | 884 | 0.1386 | 0.9592 |
| 0.203 | 18.0 | 936 | 0.1390 | 0.9592 |
| 0.203 | 19.0 | 988 | 0.1409 | 0.9592 |
| 0.0006 | 20.0 | 1040 | 0.1411 | 0.9592 |
| 0.0006 | 21.0 | 1092 | 0.1413 | 0.9592 |
| 0.0006 | 22.0 | 1144 | 0.1415 | 0.9592 |
| 0.0006 | 23.0 | 1196 | 0.1426 | 0.9592 |
| 0.0006 | 24.0 | 1248 | 0.1435 | 0.9592 |
| 0.0006 | 25.0 | 1300 | 0.1438 | 0.9592 |
| 0.0006 | 26.0 | 1352 | 0.1434 | 0.9592 |
| 0.0006 | 27.0 | 1404 | 0.1437 | 0.9592 |
| 0.0006 | 28.0 | 1456 | 0.1441 | 0.9592 |
| 0.0002 | 29.0 | 1508 | 0.1440 | 0.9592 |
| 0.0002 | 30.0 | 1560 | 0.1441 | 0.9592 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6