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wbc-100-pretrain-20-epoch
This model is a fine-tuned version of koobear/masked-pretraining-20-epoch on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0493
- Accuracy: 0.9884
- F1: 0.9884
- Precision: 0.9884
- Recall: 0.9884
- Balanced Acc: 0.9762
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Balanced Acc |
---|---|---|---|---|---|---|---|---|
0.5865 | 1.0 | 132 | 0.2601 | 0.9606 | 0.9609 | 0.9634 | 0.9606 | 0.9431 |
0.2703 | 2.0 | 264 | 0.1383 | 0.9821 | 0.9821 | 0.9822 | 0.9821 | 0.9750 |
0.1952 | 3.0 | 396 | 0.1149 | 0.9809 | 0.9812 | 0.9818 | 0.9809 | 0.9811 |
0.18 | 4.0 | 528 | 0.0914 | 0.9873 | 0.9872 | 0.9873 | 0.9873 | 0.9771 |
0.1475 | 5.0 | 660 | 0.0819 | 0.9873 | 0.9874 | 0.9878 | 0.9873 | 0.9837 |
0.1556 | 6.0 | 792 | 0.0796 | 0.9855 | 0.9857 | 0.9861 | 0.9855 | 0.9830 |
0.1276 | 7.0 | 924 | 0.0746 | 0.9878 | 0.9878 | 0.9879 | 0.9878 | 0.9728 |
0.1205 | 8.0 | 1056 | 0.0689 | 0.9873 | 0.9872 | 0.9874 | 0.9873 | 0.9702 |
0.1196 | 9.0 | 1188 | 0.0680 | 0.9855 | 0.9856 | 0.9862 | 0.9855 | 0.9775 |
0.1111 | 10.0 | 1320 | 0.0605 | 0.9873 | 0.9873 | 0.9875 | 0.9873 | 0.9832 |
0.1052 | 11.0 | 1452 | 0.0522 | 0.9902 | 0.9902 | 0.9902 | 0.9902 | 0.9845 |
0.1015 | 12.0 | 1584 | 0.0545 | 0.9896 | 0.9896 | 0.9896 | 0.9896 | 0.9809 |
0.1044 | 13.0 | 1716 | 0.0529 | 0.9896 | 0.9896 | 0.9896 | 0.9896 | 0.9780 |
0.097 | 14.0 | 1848 | 0.0521 | 0.9878 | 0.9878 | 0.9879 | 0.9878 | 0.9708 |
0.0943 | 15.0 | 1980 | 0.0468 | 0.9902 | 0.9902 | 0.9905 | 0.9902 | 0.9875 |
0.0884 | 16.0 | 2112 | 0.0454 | 0.9919 | 0.9919 | 0.9920 | 0.9919 | 0.9889 |
0.0767 | 17.0 | 2244 | 0.0465 | 0.9896 | 0.9896 | 0.9896 | 0.9896 | 0.9816 |
0.0834 | 18.0 | 2376 | 0.0512 | 0.9896 | 0.9895 | 0.9896 | 0.9896 | 0.9731 |
0.0819 | 19.0 | 2508 | 0.0497 | 0.9890 | 0.9890 | 0.9890 | 0.9890 | 0.9767 |
0.0822 | 20.0 | 2640 | 0.0493 | 0.9884 | 0.9884 | 0.9884 | 0.9884 | 0.9762 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3