Downloads · 30 days
18
3% of all-time downloads
plant-seedlings-model-aug-2
carolinetfls/plant-seedlings-model-aug-2
plant-seedlings-model-aug-2 is a image classification model from carolinetfls. 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
557
Public
Repo size
7.2 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin343 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Apr 18, 2023
- Updated
- Apr 18, 2023
- SHA
- 4ed6d9f7
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. -->
plant-seedlings-model-aug-2
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: 0.2879
- Accuracy: 0.9490
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: 16
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3968 | 0.8 | 100 | 0.2863 | 0.8975 |
| 0.3388 | 1.6 | 200 | 0.3517 | 0.8847 |
| 0.1707 | 2.4 | 300 | 0.3517 | 0.9083 |
| 0.0475 | 3.2 | 400 | 0.4085 | 0.8828 |
| 0.0823 | 4.0 | 500 | 0.2900 | 0.9274 |
| 0.0428 | 4.8 | 600 | 0.3437 | 0.9229 |
| 0.0691 | 5.6 | 700 | 0.2896 | 0.9363 |
| 0.0217 | 6.4 | 800 | 0.3413 | 0.9299 |
| 0.0341 | 7.2 | 900 | 0.2692 | 0.9471 |
| 0.0006 | 8.0 | 1000 | 0.2734 | 0.9471 |
| 0.0005 | 8.8 | 1100 | 0.2686 | 0.9503 |
| 0.0001 | 9.6 | 1200 | 0.2918 | 0.9471 |
| 0.0001 | 10.4 | 1300 | 0.2827 | 0.9490 |
| 0.0001 | 11.2 | 1400 | 0.2838 | 0.9497 |
| 0.0001 | 12.0 | 1500 | 0.2850 | 0.9490 |
| 0.0001 | 12.8 | 1600 | 0.2861 | 0.9490 |
| 0.0001 | 13.6 | 1700 | 0.2868 | 0.9490 |
| 0.0001 | 14.4 | 1800 | 0.2874 | 0.9490 |
| 0.0001 | 15.2 | 1900 | 0.2878 | 0.9490 |
| 0.0001 | 16.0 | 2000 | 0.2879 | 0.9490 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Apr 18, 2023
- Updated
- Apr 18, 2023