Downloads · 30 days
3
5% of all-time downloads
vit-base-patch16-224-RX1-24
Augusto777/vit-base-patch16-224-RX1-24
vit-base-patch16-224-RX1-24 is a image classification model from Augusto777. 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
56
Public
Parameters
85.8M
1.4 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
- Jun 10, 2024
- Updated
- Jun 10, 2024
- SHA
- 6687328e
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-base-patch16-224-RX1-24
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5687
- Accuracy: 0.8431
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: 5.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 24
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.93 | 7 | 1.3485 | 0.4706 |
| 1.3674 | 2.0 | 15 | 1.2284 | 0.5490 |
| 1.2414 | 2.93 | 22 | 1.1307 | 0.6471 |
| 1.1146 | 4.0 | 30 | 1.0230 | 0.6471 |
| 1.1146 | 4.93 | 37 | 0.9251 | 0.6863 |
| 0.9522 | 6.0 | 45 | 0.9122 | 0.6471 |
| 0.8247 | 6.93 | 52 | 0.9374 | 0.6275 |
| 0.6825 | 8.0 | 60 | 0.8320 | 0.6863 |
| 0.6825 | 8.93 | 67 | 0.8286 | 0.6667 |
| 0.6191 | 10.0 | 75 | 0.8418 | 0.6667 |
| 0.5312 | 10.93 | 82 | 0.7836 | 0.8235 |
| 0.454 | 12.0 | 90 | 0.7356 | 0.8039 |
| 0.454 | 12.93 | 97 | 0.6117 | 0.8235 |
| 0.3752 | 14.0 | 105 | 0.6014 | 0.8235 |
| 0.3269 | 14.93 | 112 | 0.6102 | 0.8039 |
| 0.2733 | 16.0 | 120 | 0.6404 | 0.8039 |
| 0.2733 | 16.93 | 127 | 0.5687 | 0.8431 |
| 0.2711 | 18.0 | 135 | 0.6120 | 0.8235 |
| 0.2519 | 18.93 | 142 | 0.6250 | 0.8431 |
| 0.2484 | 20.0 | 150 | 0.6086 | 0.7843 |
| 0.2484 | 20.93 | 157 | 0.6229 | 0.8235 |
| 0.2258 | 22.0 | 165 | 0.6390 | 0.7843 |
| 0.2258 | 22.4 | 168 | 0.6337 | 0.8039 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 10, 2024
- Updated
- Jun 10, 2024