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vit-base-patch16-224-finetuned-eurosat
barten/vit-base-patch16-224-finetuned-eurosat
vit-base-patch16-224-finetuned-eurosat is a image classification model from barten. 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
- Oct 22, 2023
- Updated
- Nov 14, 2023
- SHA
- da436ed3
Base models
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-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: 0.5725
- Accuracy: 0.8394
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 |
|---|---|---|---|---|
| 0.1364 | 0.99 | 53 | 0.5924 | 0.8217 |
| 0.0876 | 2.0 | 107 | 0.5917 | 0.8252 |
| 0.0874 | 2.99 | 160 | 0.6156 | 0.8239 |
| 0.0779 | 4.0 | 214 | 0.5792 | 0.8363 |
| 0.0747 | 4.95 | 265 | 0.5725 | 0.8394 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Oct 22, 2023
- Updated
- Nov 14, 2023