Downloads · 30 days
10
2% of all-time downloads
moon-detector-v5.b
ppicazo/moon-detector-v5.b
moon-detector-v5.b is a image classification model from ppicazo. 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
575
Public
Parameters
85.8M
2.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin343 MB · 50%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- May 19, 2023
- Updated
- Jan 30, 2025
- SHA
- fa4ea517
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. -->
moon-detector-v5.b
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0866
- Accuracy: 0.9798
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: 1338
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0246 | 1.0 | 281 | 0.1017 | 0.9773 |
| 0.0223 | 2.0 | 562 | 0.1100 | 0.9723 |
| 0.061 | 3.0 | 843 | 0.0889 | 0.9798 |
| 0.0143 | 4.0 | 1124 | 0.0878 | 0.9824 |
| 0.01 | 5.0 | 1405 | 0.0866 | 0.9798 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- May 19, 2023
- Updated
- Jan 30, 2025