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vit-base-patch-16-384-geoguessr
marcelomoreno26/vit-base-patch-16-384-geoguessr
vit-base-patch-16-384-geoguessr is a image classification model from marcelomoreno26. 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 26, 2024
- Updated
- Mar 26, 2024
- SHA
- 3e913209
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. -->
test-2-geoguessr-55
This model is a fine-tuned version of google/vit-base-patch16-384 on marcelomoreno26/geoguessr dataset. It achieves the following results on the evaluation set:
- Loss: 2.4296
- Accuracy: 0.3881
- F1: 0.1440
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 394 | 3.3218 | 0.1603 | 0.0292 |
| 3.5132 | 2.0 | 788 | 3.1195 | 0.2243 | 0.0494 |
| 3.1361 | 3.0 | 1182 | 2.9820 | 0.2587 | 0.0657 |
| 2.9576 | 4.0 | 1576 | 2.8774 | 0.2906 | 0.0816 |
| 2.9576 | 5.0 | 1970 | 2.7940 | 0.3125 | 0.0950 |
| 2.8298 | 6.0 | 2364 | 2.7271 | 0.3250 | 0.1042 |
| 2.7378 | 7.0 | 2758 | 2.6721 | 0.3366 | 0.1112 |
| 2.6526 | 8.0 | 3152 | 2.6268 | 0.3466 | 0.1156 |
| 2.5971 | 9.0 | 3546 | 2.5882 | 0.3546 | 0.1220 |
| 2.5971 | 10.0 | 3940 | 2.5558 | 0.3630 | 0.1269 |
| 2.5468 | 11.0 | 4334 | 2.5286 | 0.3699 | 0.1321 |
| 2.519 | 12.0 | 4728 | 2.5057 | 0.3721 | 0.1337 |
| 2.4769 | 13.0 | 5122 | 2.4865 | 0.3760 | 0.1359 |
| 2.4528 | 14.0 | 5516 | 2.4706 | 0.3805 | 0.1387 |
| 2.4528 | 15.0 | 5910 | 2.4577 | 0.3820 | 0.1391 |
| 2.4307 | 16.0 | 6304 | 2.4473 | 0.3840 | 0.1410 |
| 2.4207 | 17.0 | 6698 | 2.4395 | 0.3863 | 0.1428 |
| 2.4114 | 18.0 | 7092 | 2.4340 | 0.3874 | 0.1437 |
| 2.4114 | 19.0 | 7486 | 2.4307 | 0.3883 | 0.1440 |
| 2.4 | 20.0 | 7880 | 2.4296 | 0.3881 | 0.1440 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 26, 2024
- Updated
- Mar 26, 2024