Downloads · 30 days
4
12% of all-time downloads
swinv2-tiny-patch4-window8-256-dmae-humeda-DAV24
RobertoSonic/swinv2-tiny-patch4-window8-256-dmae-humeda-DAV24
swinv2-tiny-patch4-window8-256-dmae-humeda-DAV24 is a image classification model from RobertoSonic. 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
34
Public
Parameters
27.6M
2.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors110 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- swinv2
- Access
- Public
- Created
- Jan 24, 2025
- Updated
- Jan 24, 2025
- SHA
- ec6d3bef
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. -->
swinv2-tiny-patch4-window8-256-dmae-humeda-DAV24
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8851
- Accuracy: 0.7059
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.5614 | 1.0 | 17 | 1.6096 | 0.3176 |
| 6.1279 | 2.0 | 34 | 1.5651 | 0.3176 |
| 5.5089 | 3.0 | 51 | 1.3188 | 0.5529 |
| 4.453 | 4.0 | 68 | 1.0195 | 0.6353 |
| 3.3808 | 5.0 | 85 | 0.9741 | 0.5882 |
| 2.7707 | 6.0 | 102 | 0.8365 | 0.6353 |
| 2.3091 | 7.0 | 119 | 0.7725 | 0.6588 |
| 1.9831 | 8.0 | 136 | 0.8312 | 0.6588 |
| 1.8284 | 9.0 | 153 | 0.8473 | 0.7059 |
| 1.511 | 10.0 | 170 | 0.7539 | 0.7176 |
| 1.2827 | 11.0 | 187 | 0.8067 | 0.7176 |
| 1.2072 | 12.0 | 204 | 0.7927 | 0.7176 |
| 1.2069 | 13.0 | 221 | 0.8184 | 0.6824 |
| 0.9242 | 14.0 | 238 | 0.8548 | 0.7059 |
| 0.9772 | 15.0 | 255 | 0.8374 | 0.7294 |
| 0.8412 | 16.0 | 272 | 0.8340 | 0.7176 |
| 0.8921 | 17.0 | 289 | 0.8729 | 0.6941 |
| 0.7975 | 18.0 | 306 | 0.9115 | 0.7059 |
| 0.8107 | 19.0 | 323 | 0.8830 | 0.6941 |
| 0.7131 | 20.0 | 340 | 0.9049 | 0.6941 |
| 0.6777 | 21.0 | 357 | 0.8895 | 0.7059 |
| 0.6557 | 22.0 | 374 | 0.8831 | 0.7059 |
| 0.6555 | 23.0 | 391 | 0.8846 | 0.7059 |
| 0.7766 | 23.5455 | 400 | 0.8851 | 0.7059 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Image Classification
- Library
- transformers
- Type
- swinv2
- License
- apache-2.0
- Created
- Jan 24, 2025
- Updated
- Jan 24, 2025