test_trainer
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8643
- Accuracy: 0.915
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: 8
- eval_batch_size: 8
- 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 |
---|---|---|---|---|
No log | 1.0 | 125 | 3.6903 | 0.517 |
No log | 2.0 | 250 | 2.7990 | 0.553 |
No log | 3.0 | 375 | 2.3198 | 0.57 |
3.1391 | 4.0 | 500 | 2.0210 | 0.632 |
3.1391 | 5.0 | 625 | 1.8298 | 0.638 |
3.1391 | 6.0 | 750 | 1.6753 | 0.683 |
3.1391 | 7.0 | 875 | 1.5446 | 0.708 |
1.7309 | 8.0 | 1000 | 1.4338 | 0.751 |
1.7309 | 9.0 | 1125 | 1.3318 | 0.777 |
1.7309 | 10.0 | 1250 | 1.2387 | 0.807 |
1.7309 | 11.0 | 1375 | 1.1828 | 0.806 |
1.2855 | 12.0 | 1500 | 1.1052 | 0.843 |
1.2855 | 13.0 | 1625 | 1.0620 | 0.862 |
1.2855 | 14.0 | 1750 | 1.0029 | 0.87 |
1.2855 | 15.0 | 1875 | 0.9611 | 0.895 |
1.0212 | 16.0 | 2000 | 0.9314 | 0.905 |
1.0212 | 17.0 | 2125 | 0.9041 | 0.905 |
1.0212 | 18.0 | 2250 | 0.8840 | 0.913 |
1.0212 | 19.0 | 2375 | 0.8730 | 0.921 |
0.8953 | 20.0 | 2500 | 0.8639 | 0.92 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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