Instructions to use stoerpas/vit-mushroom-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stoerpas/vit-mushroom-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="stoerpas/vit-mushroom-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("stoerpas/vit-mushroom-classifier") model = AutoModelForImageClassification.from_pretrained("stoerpas/vit-mushroom-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
vit-mushroom-classifier
This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2514
- Accuracy: 0.9236
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 85 | 0.2258 | 0.9178 |
| No log | 2.0 | 170 | 0.2539 | 0.9075 |
| No log | 3.0 | 255 | 0.2457 | 0.9178 |
| No log | 4.0 | 340 | 0.2478 | 0.9236 |
| No log | 5.0 | 425 | 0.2514 | 0.9236 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Downloads last month
- 34
Model tree for stoerpas/vit-mushroom-classifier
Base model
google/vit-base-patch16-224