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vit-base-patch16-224-Trial006-YEL_STEM3
sbaner24/vit-base-patch16-224-Trial006-YEL_STEM3
vit-base-patch16-224-Trial006-YEL_STEM3 is a image classification model from sbaner24. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Jun 21, 2023
- Updated
- Nov 14, 2023
- SHA
- b5d4d2cc
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
vit-base-patch16-224-Trial006-YEL_STEM3
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: 0.0370
- 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 |
|---|---|---|---|---|
| 0.7214 | 1.0 | 2 | 0.6865 | 0.625 |
| 0.6538 | 2.0 | 4 | 0.6506 | 0.6875 |
| 0.5973 | 3.0 | 6 | 0.5406 | 0.7708 |
| 0.5867 | 4.0 | 8 | 0.4452 | 0.8125 |
| 0.4882 | 5.0 | 10 | 0.3944 | 0.9167 |
| 0.3508 | 6.0 | 12 | 0.3255 | 0.8125 |
| 0.3367 | 7.0 | 14 | 0.2000 | 0.9375 |
| 0.2721 | 8.0 | 16 | 0.1377 | 0.9792 |
| 0.2401 | 9.0 | 18 | 0.0991 | 0.9792 |
| 0.242 | 10.0 | 20 | 0.0952 | 0.9583 |
| 0.2074 | 11.0 | 22 | 0.1278 | 0.9375 |
| 0.2048 | 12.0 | 24 | 0.0370 | 1.0 |
| 0.1933 | 13.0 | 26 | 0.1006 | 0.9375 |
| 0.1869 | 14.0 | 28 | 0.0348 | 1.0 |
| 0.2057 | 15.0 | 30 | 0.1574 | 0.9375 |
| 0.2368 | 16.0 | 32 | 0.0518 | 0.9792 |
| 0.1114 | 17.0 | 34 | 0.0149 | 1.0 |
| 0.1486 | 18.0 | 36 | 0.0187 | 1.0 |
| 0.1161 | 19.0 | 38 | 0.0083 | 1.0 |
| 0.1133 | 20.0 | 40 | 0.0062 | 1.0 |
| 0.1085 | 21.0 | 42 | 0.0108 | 1.0 |
| 0.1349 | 22.0 | 44 | 0.0148 | 1.0 |
| 0.1076 | 23.0 | 46 | 0.0080 | 1.0 |
| 0.1178 | 24.0 | 48 | 0.0137 | 1.0 |
| 0.1566 | 25.0 | 50 | 0.0074 | 1.0 |
| 0.1578 | 26.0 | 52 | 0.0064 | 1.0 |
| 0.1039 | 27.0 | 54 | 0.0077 | 1.0 |
| 0.1585 | 28.0 | 56 | 0.0058 | 1.0 |
| 0.1299 | 29.0 | 58 | 0.0130 | 1.0 |
| 0.1059 | 30.0 | 60 | 0.0075 | 1.0 |
| 0.1162 | 31.0 | 62 | 0.0151 | 1.0 |
| 0.1147 | 32.0 | 64 | 0.0100 | 1.0 |
| 0.1226 | 33.0 | 66 | 0.0581 | 0.9792 |
| 0.1264 | 34.0 | 68 | 0.1029 | 0.9792 |
| 0.0858 | 35.0 | 70 | 0.0594 | 0.9792 |
| 0.0671 | 36.0 | 72 | 0.0119 | 1.0 |
| 0.1381 | 37.0 | 74 | 0.0084 | 1.0 |
| 0.1054 | 38.0 | 76 | 0.0121 | 1.0 |
| 0.0969 | 39.0 | 78 | 0.0273 | 0.9792 |
| 0.1168 | 40.0 | 80 | 0.0203 | 0.9792 |
| 0.1065 | 41.0 | 82 | 0.0061 | 1.0 |
| 0.14 | 42.0 | 84 | 0.0041 | 1.0 |
| 0.1186 | 43.0 | 86 | 0.0088 | 1.0 |
| 0.0818 | 44.0 | 88 | 0.0214 | 0.9792 |
| 0.0676 | 45.0 | 90 | 0.0148 | 1.0 |
| 0.043 | 46.0 | 92 | 0.0105 | 1.0 |
| 0.0731 | 47.0 | 94 | 0.0085 | 1.0 |
| 0.1297 | 48.0 | 96 | 0.0082 | 1.0 |
| 0.1191 | 49.0 | 98 | 0.0086 | 1.0 |
| 0.0657 | 50.0 | 100 | 0.0090 | 1.0 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 1.12.1
- Datasets 2.12.0
- Tokenizers 0.13.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 21, 2023
- Updated
- Nov 14, 2023