Image Classification
Transformers
PyTorch
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use varcoder/resnet-101-finetuned-CivilEng11k-newDS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/resnet-101-finetuned-CivilEng11k-newDS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="varcoder/resnet-101-finetuned-CivilEng11k-newDS") 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("varcoder/resnet-101-finetuned-CivilEng11k-newDS") model = AutoModelForImageClassification.from_pretrained("varcoder/resnet-101-finetuned-CivilEng11k-newDS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 10.81, | |
| "eval_accuracy": 0.9932203389830508, | |
| "eval_loss": 0.4541185200214386, | |
| "eval_runtime": 27.7932, | |
| "eval_samples_per_second": 10.614, | |
| "eval_steps_per_second": 0.36 | |
| } |