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vit-base-patch16-224-finetuned-eurosat
alexavsatov/vit-base-patch16-224-finetuned-eurosat
vit-base-patch16-224-finetuned-eurosat is a image classification model from alexavsatov. Use it when you need a label for an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- Model type
- vit
- Access
- Public
- Created
- Nov 27, 2023
- Updated
- Dec 2, 2023
- SHA
- 76f163a0
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 food101 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6541
- Accuracy: 0.8389
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0843 | 1.0 | 266 | 0.9241 | 0.7967 |
| 0.8596 | 2.0 | 533 | 0.7022 | 0.8322 |
| 0.6834 | 2.99 | 798 | 0.6541 | 0.8389 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- Created
- Nov 27, 2023
- Updated
- Dec 2, 2023