vehicle_classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5738
- Accuracy: 0.8467
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 147 | 1.4917 | 0.7785 |
| No log | 2.0 | 294 | 1.0285 | 0.8160 |
| No log | 3.0 | 441 | 0.8369 | 0.8177 |
| 1.294 | 4.0 | 588 | 0.7112 | 0.8399 |
| 1.294 | 5.0 | 735 | 0.6621 | 0.8313 |
| 1.294 | 6.0 | 882 | 0.5977 | 0.8450 |
| 0.4624 | 7.0 | 1029 | 0.5856 | 0.8518 |
| 0.4624 | 8.0 | 1176 | 0.6511 | 0.8160 |
| 0.4624 | 9.0 | 1323 | 0.6450 | 0.8365 |
| 0.4624 | 10.0 | 1470 | 0.6241 | 0.8296 |
| 0.2619 | 11.0 | 1617 | 0.6217 | 0.8382 |
| 0.2619 | 12.0 | 1764 | 0.6504 | 0.8177 |
| 0.2619 | 13.0 | 1911 | 0.5994 | 0.8433 |
| 0.1776 | 14.0 | 2058 | 0.5969 | 0.8433 |
| 0.1776 | 15.0 | 2205 | 0.5693 | 0.8569 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2