image_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: 1.1383
- Accuracy: 0.6312
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 |
|---|---|---|---|---|
| 0.925 | 1.0 | 10 | 1.3570 | 0.4688 |
| 0.8379 | 2.0 | 20 | 1.1685 | 0.5875 |
| 0.6737 | 3.0 | 30 | 1.1795 | 0.6 |
| 0.4606 | 4.0 | 40 | 1.1383 | 0.6312 |
| 0.3416 | 5.0 | 50 | 1.2393 | 0.5687 |
| 0.2493 | 6.0 | 60 | 1.3971 | 0.5938 |
| 0.2341 | 7.0 | 70 | 1.3546 | 0.6062 |
| 0.1797 | 8.0 | 80 | 1.3681 | 0.5938 |
| 0.1221 | 9.0 | 90 | 1.6936 | 0.525 |
| 0.1077 | 10.0 | 100 | 1.7008 | 0.5375 |
| 0.0966 | 11.0 | 110 | 1.7380 | 0.525 |
| 0.1073 | 12.0 | 120 | 1.5617 | 0.575 |
| 0.0849 | 13.0 | 130 | 1.6178 | 0.6125 |
| 0.0704 | 14.0 | 140 | 1.6144 | 0.6125 |
| 0.0568 | 15.0 | 150 | 1.6111 | 0.6188 |
| 0.0555 | 16.0 | 160 | 1.5946 | 0.6 |
| 0.0498 | 17.0 | 170 | 1.6291 | 0.625 |
| 0.0464 | 18.0 | 180 | 1.6574 | 0.6188 |
| 0.0443 | 19.0 | 190 | 1.6740 | 0.6125 |
| 0.0429 | 20.0 | 200 | 1.6781 | 0.6125 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224-in21k