AI-Lab-Makerere/beans
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How to use shubhangikarade/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="shubhangikarade/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("shubhangikarade/vit-base-beans")
model = AutoModelForImageClassification.from_pretrained("shubhangikarade/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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.4885 | 1.0 | 65 | 0.9549 | 0.3982 |
| 0.271 | 2.0 | 130 | 0.9774 | 0.1864 |
| 0.1419 | 3.0 | 195 | 0.9774 | 0.1587 |
| 0.1658 | 4.0 | 260 | 0.9699 | 0.1332 |
| 0.1767 | 5.0 | 325 | 0.9699 | 0.1349 |