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vit-large-patch16-224-finetuned-eurosat
Goranmk20/vit-large-patch16-224-finetuned-eurosat
vit-large-patch16-224-finetuned-eurosat is a image classification model from Goranmk20. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Mar 15, 2025
- Updated
- Jun 4, 2025
- SHA
- e5948499
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
vit-large-patch16-224-finetuned-eurosat
This model is a fine-tuned version of google/vit-large-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4947
- Accuracy: 0.875
- Precision: 0.8796
- Recall: 0.8760
- F1: 0.8715
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use 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: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 2.0089 | 1.0 | 10 | 1.4560 | 0.6188 | 0.6505 | 0.6232 | 0.6086 |
| 0.8976 | 2.0 | 20 | 0.4947 | 0.875 | 0.8796 | 0.8760 | 0.8715 |
| 0.3555 | 3.0 | 30 | 0.4390 | 0.8313 | 0.8272 | 0.8339 | 0.8274 |
| 0.1709 | 4.0 | 40 | 0.4177 | 0.85 | 0.8506 | 0.8559 | 0.8484 |
| 0.0882 | 5.0 | 50 | 0.4561 | 0.8625 | 0.8630 | 0.8610 | 0.8592 |
| 0.1136 | 6.0 | 60 | 0.5954 | 0.8375 | 0.8494 | 0.8346 | 0.8231 |
| 0.0863 | 7.0 | 70 | 0.5323 | 0.8375 | 0.8353 | 0.8373 | 0.8349 |
| 0.0637 | 8.0 | 80 | 0.4966 | 0.8438 | 0.8579 | 0.8470 | 0.8476 |
| 0.0536 | 9.0 | 90 | 0.6577 | 0.8375 | 0.8598 | 0.8423 | 0.8383 |
| 0.1069 | 10.0 | 100 | 0.5586 | 0.8438 | 0.8417 | 0.8429 | 0.8387 |
| 0.0446 | 11.0 | 110 | 0.5196 | 0.85 | 0.8703 | 0.8520 | 0.8520 |
| 0.0401 | 12.0 | 120 | 0.4480 | 0.8625 | 0.8651 | 0.8653 | 0.8632 |
| 0.0333 | 13.0 | 130 | 0.4955 | 0.8375 | 0.8441 | 0.8422 | 0.8393 |
| 0.036 | 14.0 | 140 | 0.5074 | 0.8438 | 0.8515 | 0.8477 | 0.8469 |
| 0.0288 | 15.0 | 150 | 0.5466 | 0.8438 | 0.8465 | 0.8441 | 0.8426 |
| 0.0141 | 16.0 | 160 | 0.6208 | 0.8313 | 0.8400 | 0.8324 | 0.8299 |
| 0.0145 | 17.0 | 170 | 0.5696 | 0.8438 | 0.8547 | 0.8458 | 0.8449 |
| 0.0194 | 18.0 | 180 | 0.5469 | 0.8562 | 0.8606 | 0.8575 | 0.8566 |
| 0.0139 | 19.0 | 190 | 0.5600 | 0.8625 | 0.8658 | 0.8670 | 0.8634 |
| 0.0184 | 20.0 | 200 | 0.5611 | 0.8625 | 0.8658 | 0.8675 | 0.8638 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 15, 2025
- Updated
- Jun 4, 2025