Instructions to use karim155/convnext-tiny-224-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karim155/convnext-tiny-224-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="karim155/convnext-tiny-224-finetuned") 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("karim155/convnext-tiny-224-finetuned") model = AutoModelForImageClassification.from_pretrained("karim155/convnext-tiny-224-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 1.3130167722702026, | |
| "best_model_checkpoint": "convnext-tiny-224-finetuned/checkpoint-18", | |
| "epoch": 2.88, | |
| "eval_steps": 500, | |
| "global_step": 18, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.96, | |
| "eval_accuracy": { | |
| "accuracy": 0.42 | |
| }, | |
| "eval_logLoss": 1.4662960767745972, | |
| "eval_loss": 1.4662964344024658, | |
| "eval_runtime": 71.93, | |
| "eval_samples_per_second": 2.78, | |
| "eval_steps_per_second": 0.097, | |
| "step": 6 | |
| }, | |
| { | |
| "epoch": 1.6, | |
| "grad_norm": 2.0363504886627197, | |
| "learning_rate": 2.5e-05, | |
| "loss": 1.4937, | |
| "step": 10 | |
| }, | |
| { | |
| "epoch": 1.92, | |
| "eval_accuracy": { | |
| "accuracy": 0.445 | |
| }, | |
| "eval_logLoss": 1.3507485389709473, | |
| "eval_loss": 1.3507485389709473, | |
| "eval_runtime": 4.9957, | |
| "eval_samples_per_second": 40.034, | |
| "eval_steps_per_second": 1.401, | |
| "step": 12 | |
| }, | |
| { | |
| "epoch": 2.88, | |
| "eval_accuracy": { | |
| "accuracy": 0.43 | |
| }, | |
| "eval_logLoss": 1.3130167722702026, | |
| "eval_loss": 1.3130167722702026, | |
| "eval_runtime": 6.5823, | |
| "eval_samples_per_second": 30.385, | |
| "eval_steps_per_second": 1.063, | |
| "step": 18 | |
| }, | |
| { | |
| "epoch": 2.88, | |
| "step": 18, | |
| "total_flos": 5.789887959505306e+16, | |
| "train_loss": 1.4178554217020671, | |
| "train_runtime": 455.1681, | |
| "train_samples_per_second": 5.273, | |
| "train_steps_per_second": 0.04 | |
| } | |
| ], | |
| "logging_steps": 10, | |
| "max_steps": 18, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 3, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 5.789887959505306e+16, | |
| "train_batch_size": 32, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |