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This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the defect dataset. It achieves the following results on the evaluation set:
- Loss: 0.0012
- Accuracy: 1.0
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: 0.0002
- train_batch_size: 10
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2249 | 1.25 | 10 | 0.0323 | 1.0 |
| 0.0177 | 2.5 | 20 | 0.0112 | 1.0 |
| 0.0086 | 3.75 | 30 | 0.0075 | 1.0 |
| 0.0063 | 5.0 | 40 | 0.0059 | 1.0 |
| 0.0051 | 6.25 | 50 | 0.0050 | 1.0 |
| 0.0045 | 7.5 | 60 | 0.0044 | 1.0 |
| 0.004 | 8.75 | 70 | 0.0040 | 1.0 |
| 0.0036 | 10.0 | 80 | 0.0036 | 1.0 |
| 0.0033 | 11.25 | 90 | 0.0034 | 1.0 |
| 0.0031 | 12.5 | 100 | 0.0031 | 1.0 |
| 0.0028 | 13.75 | 110 | 0.0029 | 1.0 |
| 0.0026 | 15.0 | 120 | 0.0027 | 1.0 |
| 0.0025 | 16.25 | 130 | 0.0025 | 1.0 |
| 0.0023 | 17.5 | 140 | 0.0024 | 1.0 |
| 0.0022 | 18.75 | 150 | 0.0023 | 1.0 |
| 0.0021 | 20.0 | 160 | 0.0021 | 1.0 |
| 0.002 | 21.25 | 170 | 0.0020 | 1.0 |
| 0.0019 | 22.5 | 180 | 0.0019 | 1.0 |
| 0.0018 | 23.75 | 190 | 0.0019 | 1.0 |
| 0.0017 | 25.0 | 200 | 0.0018 | 1.0 |
| 0.0016 | 26.25 | 210 | 0.0017 | 1.0 |
| 0.0016 | 27.5 | 220 | 0.0017 | 1.0 |
| 0.0015 | 28.75 | 230 | 0.0016 | 1.0 |
| 0.0015 | 30.0 | 240 | 0.0015 | 1.0 |
| 0.0014 | 31.25 | 250 | 0.0015 | 1.0 |
| 0.0014 | 32.5 | 260 | 0.0015 | 1.0 |
| 0.0013 | 33.75 | 270 | 0.0014 | 1.0 |
| 0.0013 | 35.0 | 280 | 0.0014 | 1.0 |
| 0.0013 | 36.25 | 290 | 0.0014 | 1.0 |
| 0.0013 | 37.5 | 300 | 0.0013 | 1.0 |
| 0.0012 | 38.75 | 310 | 0.0013 | 1.0 |
| 0.0012 | 40.0 | 320 | 0.0013 | 1.0 |
| 0.0012 | 41.25 | 330 | 0.0013 | 1.0 |
| 0.0012 | 42.5 | 340 | 0.0013 | 1.0 |
| 0.0012 | 43.75 | 350 | 0.0012 | 1.0 |
| 0.0012 | 45.0 | 360 | 0.0012 | 1.0 |
| 0.0011 | 46.25 | 370 | 0.0012 | 1.0 |
| 0.0012 | 47.5 | 380 | 0.0012 | 1.0 |
| 0.0011 | 48.75 | 390 | 0.0012 | 1.0 |
| 0.0011 | 50.0 | 400 | 0.0012 | 1.0 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
