microsoft/cats_vs_dogs
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How to use cppgohan/resnet-50-finetuned-dog-vs-cat with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="cppgohan/resnet-50-finetuned-dog-vs-cat")
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("cppgohan/resnet-50-finetuned-dog-vs-cat")
model = AutoModelForImageClassification.from_pretrained("cppgohan/resnet-50-finetuned-dog-vs-cat")This model is a fine-tuned version of microsoft/resnet-50 on the cats_vs_dogs 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 |
|---|---|---|---|---|
| 0.3357 | 1.0 | 164 | 0.2255 | 0.9868 |
| 0.1683 | 2.0 | 329 | 0.0577 | 0.9919 |
| 0.1448 | 2.99 | 492 | 0.0460 | 0.9919 |
Base model
microsoft/resnet-50