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Cinnamon-Plant-20-Epochs-Model
Akshay0706/Cinnamon-Plant-20-Epochs-Model
Cinnamon-Plant-20-Epochs-Model is a image classification model from Akshay0706. 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. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023
- SHA
- 58d5908f
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. -->
Rice-Plant-Disease-Detection-Model
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: 0.2929
- Accuracy: 0.8958
- F1: 0.8965
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5517 | 1.0 | 18 | 0.5222 | 0.875 | 0.8754 |
| 0.2996 | 2.0 | 36 | 0.3833 | 0.8542 | 0.8564 |
| 0.1529 | 3.0 | 54 | 0.3152 | 0.875 | 0.8763 |
| 0.0843 | 4.0 | 72 | 0.2929 | 0.8958 | 0.8965 |
| 0.0549 | 5.0 | 90 | 0.2756 | 0.875 | 0.8754 |
| 0.0402 | 6.0 | 108 | 0.2765 | 0.875 | 0.8754 |
| 0.0327 | 7.0 | 126 | 0.2875 | 0.875 | 0.8754 |
| 0.0277 | 8.0 | 144 | 0.2938 | 0.875 | 0.8754 |
| 0.0244 | 9.0 | 162 | 0.2992 | 0.875 | 0.8754 |
| 0.0222 | 10.0 | 180 | 0.2996 | 0.8958 | 0.8960 |
| 0.0203 | 11.0 | 198 | 0.3052 | 0.8958 | 0.8960 |
| 0.019 | 12.0 | 216 | 0.3087 | 0.8958 | 0.8960 |
| 0.018 | 13.0 | 234 | 0.3143 | 0.8958 | 0.8960 |
| 0.0171 | 14.0 | 252 | 0.3206 | 0.8958 | 0.8960 |
| 0.0164 | 15.0 | 270 | 0.3227 | 0.8958 | 0.8960 |
| 0.0158 | 16.0 | 288 | 0.3250 | 0.8958 | 0.8960 |
| 0.0155 | 17.0 | 306 | 0.3257 | 0.8958 | 0.8960 |
| 0.0152 | 18.0 | 324 | 0.3264 | 0.8958 | 0.8960 |
| 0.015 | 19.0 | 342 | 0.3276 | 0.8958 | 0.8960 |
| 0.0149 | 20.0 | 360 | 0.3275 | 0.8958 | 0.8960 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cpu
- Datasets 2.14.5
- Tokenizers 0.14.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023