vit-base-patch16-224-finetuned-eurosat
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: 0.7387
- Accuracy: 0.7947
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: 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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0852 | 0.9362 | 11 | 1.6028 | 0.4263 |
| 1.2089 | 1.9574 | 23 | 1.1012 | 0.6789 |
| 0.7539 | 2.9787 | 35 | 0.9159 | 0.7158 |
| 0.4935 | 4.0 | 47 | 0.8390 | 0.7368 |
| 0.3742 | 4.9362 | 58 | 0.7865 | 0.7632 |
| 0.2641 | 5.6170 | 66 | 0.7387 | 0.7947 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224