Downloads · 30 days
5
3% of all-time downloads
vit-large-patch16-224-new-dungeon-geo-morphs-009
griffio/vit-large-patch16-224-new-dungeon-geo-morphs-009
vit-large-patch16-224-new-dungeon-geo-morphs-009 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. --
All-time downloads
145
Public
Parameters
303M
10.9 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.2 GB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Nov 16, 2024
- Updated
- Nov 16, 2024
- SHA
- 6a2a6e28
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-new-dungeon-geo-morphs-009
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: 0.0997
- Accuracy: 0.96
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: 2e-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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1702 | 4.4444 | 10 | 0.5499 | 0.94 |
| 0.1925 | 8.8889 | 20 | 0.1645 | 0.94 |
| 0.0112 | 13.3333 | 30 | 0.0997 | 0.96 |
| 0.0011 | 17.7778 | 40 | 0.1255 | 0.96 |
| 0.0005 | 22.2222 | 50 | 0.1313 | 0.96 |
| 0.0004 | 26.6667 | 60 | 0.1238 | 0.96 |
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 16, 2024
- Updated
- Nov 16, 2024