metadata
license: apache-2.0
base_model: WinKawaks/vit-small-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-small-patch16-224-finetuned-eurosat
results: []
vit-small-patch16-224-finetuned-eurosat
This model is a fine-tuned version of WinKawaks/vit-small-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0415
- Accuracy: 0.9858
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2917 | 1.0 | 351 | 0.0685 | 0.978 |
| 0.2336 | 2.0 | 703 | 0.0490 | 0.9846 |
| 0.1666 | 2.99 | 1053 | 0.0415 | 0.9858 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2