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vit-large-patch16-224-dungeon-geo-morphs-0-4-28Nov24-005
griffio/vit-large-patch16-224-dungeon-geo-morphs-0-4-28Nov24-005
vit-large-patch16-224-dungeon-geo-morphs-0-4-28Nov24-005 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
- cb95b1fa
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-0-4-28Nov24-005
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: 0.1168
- Accuracy: 0.9804
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: 35
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5698 | 4.0 | 10 | 1.2316 | 0.6214 |
| 0.7717 | 8.0 | 20 | 0.6293 | 0.8696 |
| 0.2702 | 12.0 | 30 | 0.3256 | 0.9571 |
| 0.0817 | 16.0 | 40 | 0.2082 | 0.9679 |
| 0.0301 | 20.0 | 50 | 0.1580 | 0.9661 |
| 0.0123 | 24.0 | 60 | 0.1168 | 0.9804 |
| 0.0074 | 28.0 | 70 | 0.1133 | 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