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results
wuru330/results
results is a image classification model from wuru330. 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
- Jul 9, 2023
- Updated
- Jul 16, 2023
- SHA
- f1a165dc
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. -->
results
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8129
- Accuracy: 0.5969
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9759 | 1.0 | 37 | 0.9392 | 0.5408 |
| 0.8313 | 2.0 | 74 | 0.8845 | 0.6122 |
| 0.8032 | 3.0 | 111 | 0.8459 | 0.6122 |
| 0.7375 | 4.0 | 148 | 0.8693 | 0.5782 |
| 0.635 | 5.0 | 185 | 0.8724 | 0.6344 |
| 0.578 | 6.0 | 222 | 0.9932 | 0.5629 |
| 0.3875 | 7.0 | 259 | 1.0738 | 0.5952 |
| 0.3544 | 8.0 | 296 | 1.1359 | 0.6156 |
| 0.407 | 9.0 | 333 | 1.3020 | 0.5493 |
| 0.2329 | 10.0 | 370 | 1.2567 | 0.6020 |
| 0.2305 | 11.0 | 407 | 1.3148 | 0.6156 |
| 0.2098 | 12.0 | 444 | 1.2928 | 0.6241 |
| 0.1595 | 13.0 | 481 | 1.5325 | 0.5629 |
| 0.1515 | 14.0 | 518 | 1.4402 | 0.6156 |
| 0.1429 | 15.0 | 555 | 1.4456 | 0.6276 |
| 0.1812 | 16.0 | 592 | 1.5088 | 0.5663 |
| 0.1169 | 17.0 | 629 | 1.6266 | 0.5850 |
| 0.1375 | 18.0 | 666 | 1.5252 | 0.6173 |
| 0.0907 | 19.0 | 703 | 1.6055 | 0.6088 |
| 0.1003 | 20.0 | 740 | 1.5785 | 0.6003 |
| 0.0756 | 21.0 | 777 | 1.6485 | 0.5850 |
| 0.0641 | 22.0 | 814 | 1.6257 | 0.6190 |
| 0.0387 | 23.0 | 851 | 1.6758 | 0.6105 |
| 0.0341 | 24.0 | 888 | 1.7239 | 0.6088 |
| 0.0227 | 25.0 | 925 | 1.7956 | 0.6020 |
| 0.0247 | 26.0 | 962 | 1.7542 | 0.6037 |
| 0.014 | 27.0 | 999 | 1.7693 | 0.6139 |
| 0.0152 | 28.0 | 1036 | 1.8133 | 0.5969 |
| 0.0125 | 29.0 | 1073 | 1.8082 | 0.6037 |
| 0.0116 | 30.0 | 1110 | 1.8129 | 0.5969 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jul 9, 2023
- Updated
- Jul 16, 2023