vit-base-patch16-224-Trial007-YEL_STEM1
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0269
- 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: 5e-05
- train_batch_size: 60
- eval_batch_size: 60
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 240
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.8443 | 0.89 | 2 | 0.7813 | 0.3148 |
0.7501 | 1.78 | 4 | 0.7087 | 0.5556 |
0.6312 | 2.67 | 6 | 0.5306 | 0.9074 |
0.4329 | 4.0 | 9 | 0.3618 | 0.9074 |
0.4438 | 4.89 | 11 | 0.2699 | 0.9444 |
0.3858 | 5.78 | 13 | 0.3650 | 0.7963 |
0.339 | 6.67 | 15 | 0.1911 | 0.9630 |
0.2852 | 8.0 | 18 | 0.1611 | 0.9630 |
0.1866 | 8.89 | 20 | 0.1516 | 0.9444 |
0.1748 | 9.78 | 22 | 0.1333 | 0.9630 |
0.1996 | 10.67 | 24 | 0.1188 | 0.9630 |
0.1604 | 12.0 | 27 | 0.1169 | 0.9444 |
0.1319 | 12.89 | 29 | 0.0835 | 0.9815 |
0.141 | 13.78 | 31 | 0.0704 | 0.9815 |
0.123 | 14.67 | 33 | 0.0574 | 0.9815 |
0.0678 | 16.0 | 36 | 0.0604 | 0.9815 |
0.1208 | 16.89 | 38 | 0.0385 | 0.9815 |
0.0942 | 17.78 | 40 | 0.0269 | 1.0 |
0.0822 | 18.67 | 42 | 0.0169 | 1.0 |
0.0578 | 20.0 | 45 | 0.0175 | 1.0 |
0.0611 | 20.89 | 47 | 0.0220 | 1.0 |
0.1053 | 21.78 | 49 | 0.0098 | 1.0 |
0.1713 | 22.67 | 51 | 0.0156 | 1.0 |
0.0515 | 24.0 | 54 | 0.0111 | 1.0 |
0.1227 | 24.89 | 56 | 0.0166 | 1.0 |
0.0891 | 25.78 | 58 | 0.0093 | 1.0 |
0.0768 | 26.67 | 60 | 0.0090 | 1.0 |
0.0755 | 28.0 | 63 | 0.0108 | 1.0 |
0.0798 | 28.89 | 65 | 0.0201 | 1.0 |
0.1005 | 29.78 | 67 | 0.0118 | 1.0 |
0.1113 | 30.67 | 69 | 0.0131 | 1.0 |
0.1034 | 32.0 | 72 | 0.0171 | 1.0 |
0.0857 | 32.89 | 74 | 0.0158 | 1.0 |
0.0864 | 33.78 | 76 | 0.0141 | 1.0 |
0.1241 | 34.67 | 78 | 0.0127 | 1.0 |
0.0868 | 36.0 | 81 | 0.0118 | 1.0 |
0.0704 | 36.89 | 83 | 0.0113 | 1.0 |
0.0938 | 37.78 | 85 | 0.0109 | 1.0 |
0.1181 | 38.67 | 87 | 0.0120 | 1.0 |
0.0509 | 40.0 | 90 | 0.0149 | 1.0 |
0.0684 | 40.89 | 92 | 0.0155 | 1.0 |
0.0625 | 41.78 | 94 | 0.0151 | 1.0 |
0.0746 | 42.67 | 96 | 0.0143 | 1.0 |
0.1062 | 44.0 | 99 | 0.0133 | 1.0 |
0.0579 | 44.44 | 100 | 0.0132 | 1.0 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 1.12.1
- Datasets 2.12.0
- Tokenizers 0.13.1
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