convnext-tiny-224-finetuned-main-gpu-20e-final
This model is a fine-tuned version of facebook/convnext-tiny-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0349
- Accuracy: 0.9875
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6197 | 1.0 | 551 | 0.5899 | 0.7440 |
| 0.3906 | 2.0 | 1102 | 0.3245 | 0.8717 |
| 0.3161 | 3.0 | 1653 | 0.2228 | 0.9135 |
| 0.2323 | 4.0 | 2204 | 0.1481 | 0.9446 |
| 0.2049 | 5.0 | 2755 | 0.1100 | 0.9589 |
| 0.1453 | 6.0 | 3306 | 0.0887 | 0.9671 |
| 0.1786 | 7.0 | 3857 | 0.0796 | 0.9702 |
| 0.1576 | 8.0 | 4408 | 0.0635 | 0.9767 |
| 0.1584 | 9.0 | 4959 | 0.0563 | 0.9798 |
| 0.122 | 10.0 | 5510 | 0.0570 | 0.9793 |
| 0.1138 | 11.0 | 6061 | 0.0526 | 0.9819 |
| 0.1116 | 12.0 | 6612 | 0.0498 | 0.9832 |
| 0.0876 | 13.0 | 7163 | 0.0497 | 0.9830 |
| 0.0956 | 14.0 | 7714 | 0.0403 | 0.9855 |
| 0.0892 | 15.0 | 8265 | 0.0414 | 0.9855 |
| 0.0807 | 16.0 | 8816 | 0.0425 | 0.9861 |
| 0.0959 | 17.0 | 9367 | 0.0397 | 0.9866 |
| 0.0847 | 18.0 | 9918 | 0.0373 | 0.9874 |
| 0.0962 | 19.0 | 10469 | 0.0356 | 0.9870 |
| 0.0731 | 20.0 | 11020 | 0.0349 | 0.9875 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2