Downloads · 30 days
4
9% of all-time downloads
vit-ytr-demo-v2
sharren/vit-ytr-demo-v2
vit-ytr-demo-v2 is a image classification model from sharren. 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
47
Public
Parameters
85.8M
4.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors343 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Feb 23, 2024
- Updated
- Feb 23, 2024
- SHA
- 78868b80
Base models
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-ytr-demo-v2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the SkinCancerClassification dataset. It achieves the following results on the evaluation set:
- Loss: 0.4299
- Accuracy: 0.8497
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7759 | 0.31 | 100 | 0.7807 | 0.7304 |
| 0.6829 | 0.62 | 200 | 0.6997 | 0.7459 |
| 0.8535 | 0.93 | 300 | 0.6830 | 0.7594 |
| 0.6652 | 1.25 | 400 | 0.6186 | 0.7803 |
| 0.5537 | 1.56 | 500 | 0.5893 | 0.7973 |
| 0.5244 | 1.87 | 600 | 0.5723 | 0.7933 |
| 0.4224 | 2.18 | 700 | 0.5234 | 0.8168 |
| 0.516 | 2.49 | 800 | 0.5281 | 0.8028 |
| 0.4097 | 2.8 | 900 | 0.5010 | 0.8293 |
| 0.2422 | 3.12 | 1000 | 0.4585 | 0.8417 |
| 0.1393 | 3.43 | 1100 | 0.4508 | 0.8502 |
| 0.2486 | 3.74 | 1200 | 0.4299 | 0.8497 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Feb 23, 2024
- Updated
- Feb 23, 2024