AI-Lab-Makerere/beans
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How to use sjdata/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="sjdata/vit-base-beans")
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("sjdata/vit-base-beans")
model = AutoModelForImageClassification.from_pretrained("sjdata/vit-base-beans")This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1595 | 1.54 | 100 | 0.1212 | 0.9699 |
| 0.014 | 3.08 | 200 | 0.0138 | 1.0 |