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vit-base-patch16-224-in21k-eurosat
polejowska/vit-base-patch16-224-in21k-eurosat
vit-base-patch16-224-in21k-eurosat is a image classification model from polejowska. 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
- Dec 11, 2022
- Updated
- Dec 11, 2022
- SHA
- 28a3eaf7
Datasets
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-base-patch16-224-in21k-eurosat
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3394
- Accuracy: 0.9802
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7076 | 0.98 | 33 | 0.6119 | 0.9696 |
| 0.4469 | 1.98 | 66 | 0.4190 | 0.9788 |
| 0.3497 | 2.98 | 99 | 0.3555 | 0.9788 |
| 0.3048 | 3.98 | 132 | 0.3394 | 0.9802 |
| 0.2983 | 4.98 | 165 | 0.3394 | 0.9802 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Dec 11, 2022
- Updated
- Dec 11, 2022