vit-base-patch16-224-ethos
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: 0.2506
- Accuracy: 0.96
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: 0.0002
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8696 | 5 | 0.4608 | 0.87 |
| 0.5337 | 1.9130 | 11 | 0.2743 | 0.91 |
| 0.5337 | 2.9565 | 17 | 0.2239 | 0.94 |
| 0.2275 | 4.0 | 23 | 0.3780 | 0.88 |
| 0.2275 | 4.8696 | 28 | 0.3501 | 0.88 |
| 0.1107 | 5.9130 | 34 | 0.2420 | 0.92 |
| 0.0528 | 6.9565 | 40 | 0.2752 | 0.94 |
| 0.0528 | 8.0 | 46 | 0.3932 | 0.9 |
| 0.0465 | 8.8696 | 51 | 0.2496 | 0.94 |
| 0.0465 | 9.9130 | 57 | 0.3151 | 0.93 |
| 0.0516 | 10.9565 | 63 | 0.1837 | 0.96 |
| 0.0516 | 12.0 | 69 | 0.1885 | 0.95 |
| 0.0317 | 12.8696 | 74 | 0.3941 | 0.92 |
| 0.0463 | 13.9130 | 80 | 0.2577 | 0.95 |
| 0.0463 | 14.9565 | 86 | 0.2128 | 0.95 |
| 0.018 | 16.0 | 92 | 0.2342 | 0.96 |
| 0.018 | 16.8696 | 97 | 0.2483 | 0.96 |
| 0.0179 | 17.3913 | 100 | 0.2506 | 0.96 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1