AI-Lab-Makerere/beans
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How to use bgoldfe2/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="bgoldfe2/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("bgoldfe2/vit-base-beans")
model = AutoModelForImageClassification.from_pretrained("bgoldfe2/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 |
|---|---|---|---|---|
| 0.9983 | 1.0 | 17 | 0.8032 | 0.9323 |
| 0.6984 | 2.0 | 34 | 0.5943 | 0.9549 |
| 0.5056 | 3.0 | 51 | 0.4566 | 0.9624 |
| 0.4601 | 4.0 | 68 | 0.3892 | 0.9624 |
| 0.3883 | 5.0 | 85 | 0.3674 | 0.9699 |
Base model
google/vit-base-patch16-224-in21k