Birdsclassification
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: 0.3057
- Accuracy: 0.9307
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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 16
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.42 | 1.0 | 262 | 3.6698 | 0.7571 |
| 1.7968 | 2.0 | 525 | 0.9179 | 0.8396 |
| 0.6598 | 3.0 | 787 | 0.6370 | 0.8654 |
| 0.4867 | 4.0 | 1050 | 0.5493 | 0.8765 |
| 0.4055 | 5.0 | 1312 | 0.5093 | 0.8833 |
| 0.3513 | 6.0 | 1575 | 0.4602 | 0.8892 |
| 0.3053 | 7.0 | 1837 | 0.4350 | 0.8977 |
| 0.2692 | 8.0 | 2100 | 0.4130 | 0.9021 |
| 0.2446 | 9.0 | 2362 | 0.4218 | 0.9018 |
| 0.2267 | 10.0 | 2625 | 0.3667 | 0.9130 |
| 0.2018 | 11.0 | 2887 | 0.3632 | 0.9154 |
| 0.1842 | 12.0 | 3150 | 0.3533 | 0.9154 |
| 0.1636 | 13.0 | 3412 | 0.3396 | 0.9206 |
| 0.1511 | 14.0 | 3675 | 0.3125 | 0.9266 |
| 0.1411 | 15.0 | 3937 | 0.2833 | 0.9329 |
| 0.1259 | 15.97 | 4192 | 0.3057 | 0.9307 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2