Instructions to use jvadlamudi2/convnext-tiny-224-jvadlamudi2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jvadlamudi2/convnext-tiny-224-jvadlamudi2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jvadlamudi2/convnext-tiny-224-jvadlamudi2") 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("jvadlamudi2/convnext-tiny-224-jvadlamudi2") model = AutoModelForImageClassification.from_pretrained("jvadlamudi2/convnext-tiny-224-jvadlamudi2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 0.6160714285714286, | |
| "best_model_checkpoint": "convnext-tiny-224-jvadlamudi2/checkpoint-24", | |
| "epoch": 3.0, | |
| "global_step": 24, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.5535714285714286, | |
| "eval_loss": 0.6731433272361755, | |
| "eval_runtime": 0.8011, | |
| "eval_samples_per_second": 139.814, | |
| "eval_steps_per_second": 4.993, | |
| "step": 8 | |
| }, | |
| { | |
| "epoch": 1.25, | |
| "learning_rate": 3.3333333333333335e-05, | |
| "loss": 0.6901, | |
| "step": 10 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.5982142857142857, | |
| "eval_loss": 0.6700941920280457, | |
| "eval_runtime": 0.9327, | |
| "eval_samples_per_second": 120.086, | |
| "eval_steps_per_second": 4.289, | |
| "step": 16 | |
| }, | |
| { | |
| "epoch": 2.5, | |
| "learning_rate": 9.523809523809523e-06, | |
| "loss": 0.6819, | |
| "step": 20 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.6160714285714286, | |
| "eval_loss": 0.6697055697441101, | |
| "eval_runtime": 0.846, | |
| "eval_samples_per_second": 132.395, | |
| "eval_steps_per_second": 4.728, | |
| "step": 24 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "step": 24, | |
| "total_flos": 7.553368114429133e+16, | |
| "train_loss": 0.6847228904565176, | |
| "train_runtime": 88.414, | |
| "train_samples_per_second": 33.999, | |
| "train_steps_per_second": 0.271 | |
| } | |
| ], | |
| "max_steps": 24, | |
| "num_train_epochs": 3, | |
| "total_flos": 7.553368114429133e+16, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |