DamarJati/GreenLabel-Waste-Types
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How to use DamarJati/GreenLabel-Waste-Types with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="DamarJati/GreenLabel-Waste-Types")
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("DamarJati/GreenLabel-Waste-Types")
model = AutoModelForImageClassification.from_pretrained("DamarJati/GreenLabel-Waste-Types")This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder 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 |
|---|---|---|---|---|
| 0.5566 | 0.98 | 11 | 0.1846 | 0.975 |
| 0.1031 | 1.96 | 22 | 0.0150 | 1.0 |
| 0.0345 | 2.93 | 33 | 0.0031 | 1.0 |
| 0.0117 | 4.0 | 45 | 0.0008 | 1.0 |
| 0.0256 | 4.98 | 56 | 0.0008 | 1.0 |
| 0.0136 | 5.87 | 66 | 0.0007 | 1.0 |
Base model
microsoft/swin-tiny-patch4-window7-224