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vit-large-patch16-224-dungeon-geo-morphs-0-4-28Nov24-006
griffio/vit-large-patch16-224-dungeon-geo-morphs-0-4-28Nov24-006
vit-large-patch16-224-dungeon-geo-morphs-0-4-28Nov24-006 is a image classification model from griffio. 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
- Nov 28, 2024
- Updated
- Nov 28, 2024
- SHA
- 1005e6ac
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-large-patch16-224-dungeon-geo-morphs-0-4-28Nov24-006
This model is a fine-tuned version of google/vit-large-patch16-224 on the dungeon-geo-morphs dataset. It achieves the following results on the evaluation set:
- Loss: 0.0747
- Accuracy: 0.9821
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6194 | 4.0 | 10 | 1.2322 | 0.6214 |
| 0.7978 | 8.0 | 20 | 0.5919 | 0.925 |
| 0.2576 | 12.0 | 30 | 0.2721 | 0.9679 |
| 0.0723 | 16.0 | 40 | 0.1548 | 0.9786 |
| 0.0202 | 20.0 | 50 | 0.1066 | 0.9768 |
| 0.0067 | 24.0 | 60 | 0.0747 | 0.9821 |
| 0.0035 | 28.0 | 70 | 0.0754 | 0.9768 |
| 0.0027 | 32.0 | 80 | 0.0730 | 0.9786 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 28, 2024
- Updated
- Nov 28, 2024