dinov2-small-finetuned-eurosat
This model is a fine-tuned version of facebook/dinov2-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1476
- Accuracy: 0.9519
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 8 | 0.1869 | 0.9519 |
| 0.1069 | 2.0 | 16 | 0.1015 | 0.9615 |
| 0.0811 | 3.0 | 24 | 0.1934 | 0.9519 |
| 0.064 | 4.0 | 32 | 0.2220 | 0.9423 |
| 0.0188 | 5.0 | 40 | 0.1476 | 0.9519 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1