uoft-cs/cifar10
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How to use ahmedALM1221/convnext-tiny-224-finetuned-eurosat with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="ahmedALM1221/convnext-tiny-224-finetuned-eurosat")
pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ahmedALM1221/convnext-tiny-224-finetuned-eurosat")
model = AutoModelForImageClassification.from_pretrained("ahmedALM1221/convnext-tiny-224-finetuned-eurosat", device_map="auto")This model is a fine-tuned version of facebook/convnext-tiny-224 on the cifar10 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 |
|---|---|---|---|---|
| 0.5799 | 1.0 | 351 | 0.2682 | 0.934 |
| 0.4018 | 2.0 | 703 | 0.1629 | 0.9546 |
| 0.3728 | 2.99 | 1053 | 0.1396 | 0.9618 |