vehicle_classification
This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0269
- Accuracy: 0.9917
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0356 | 1.0 | 245 | 0.0432 | 0.9869 |
| 0.0036 | 2.0 | 490 | 0.0403 | 0.9869 |
| 0.0004 | 3.0 | 735 | 0.0275 | 0.9905 |
| 0.0002 | 4.0 | 980 | 0.0260 | 0.9917 |
| 0.0002 | 5.0 | 1225 | 0.0261 | 0.9917 |
| 0.0001 | 6.0 | 1470 | 0.0264 | 0.9917 |
| 0.0001 | 7.0 | 1715 | 0.0267 | 0.9917 |
| 0.0001 | 8.0 | 1960 | 0.0269 | 0.9917 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Model tree for Tianmu28/vit_google_vehicle_classification_model
Base model
google/vit-base-patch16-224