Image Classification
Transformers
TensorBoard
Safetensors
dinov2
Generated from Trainer
Eval Results (legacy)
Instructions to use LuGot16/spermatogenesis-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LuGot16/spermatogenesis-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="LuGot16/spermatogenesis-classifier") 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("LuGot16/spermatogenesis-classifier") model = AutoModelForImageClassification.from_pretrained("LuGot16/spermatogenesis-classifier") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_loss": 0.3150061070919037, | |
| "eval_accuracy": 0.8910256410256411, | |
| "eval_f1": 0.8896300082346593, | |
| "eval_acc_I-IV": 0.8709677419354839, | |
| "eval_acc_IX-X": 0.9047619047619048, | |
| "eval_acc_V-VI": 0.851063829787234, | |
| "eval_acc_VII-VII": 0.9714285714285714, | |
| "eval_acc_XI- XII": 0.8636363636363636, | |
| "eval_runtime": 47.9961, | |
| "eval_samples_per_second": 3.25, | |
| "eval_steps_per_second": 0.208, | |
| "epoch": 20.0 | |
| } |