AI-Lab-Makerere/beans
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How to use lirongzhang/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="lirongzhang/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("lirongzhang/vit-base-beans")
model = AutoModelForImageClassification.from_pretrained("lirongzhang/vit-base-beans", device_map="auto")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 |
|---|---|---|---|---|
| 0.3167 | 1.0 | 130 | 0.2344 | 0.9624 |
| 0.1621 | 2.0 | 260 | 0.1423 | 0.9699 |
| 0.1493 | 3.0 | 390 | 0.0899 | 0.9774 |
| 0.1087 | 4.0 | 520 | 0.0818 | 0.9850 |
| 0.0589 | 5.0 | 650 | 0.0879 | 0.9850 |
Base model
google/vit-base-patch16-224-in21k