vit-base-patch16-224-finetuned-landscape-test
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: 0.1536
- Accuracy: 0.9524
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8077 | 0.9684 | 23 | 0.2954 | 0.9273 |
| 0.2325 | 1.9789 | 47 | 0.1675 | 0.9445 |
| 0.1987 | 2.9895 | 71 | 0.1601 | 0.9511 |
| 0.1641 | 4.0 | 95 | 0.1565 | 0.9498 |
| 0.1497 | 4.8421 | 115 | 0.1536 | 0.9524 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1