Image Classification
Transformers
TensorBoard
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use embunna/resnet-18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use embunna/resnet-18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="embunna/resnet-18") 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("embunna/resnet-18") model = AutoModelForImageClassification.from_pretrained("embunna/resnet-18") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 0.2857142857142857, | |
| "best_model_checkpoint": "resnet-18/checkpoint-5", | |
| "epoch": 2.7272727272727275, | |
| "eval_steps": 500, | |
| "global_step": 15, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.9090909090909091, | |
| "eval_accuracy": 0.2857142857142857, | |
| "eval_loss": 1.142593873281104e+31, | |
| "eval_runtime": 0.3831, | |
| "eval_samples_per_second": 200.981, | |
| "eval_steps_per_second": 7.83, | |
| "step": 5 | |
| }, | |
| { | |
| "epoch": 1.8181818181818183, | |
| "grad_norm": 19.20919418334961, | |
| "learning_rate": 1.923076923076923e-05, | |
| "loss": 1.08768806515315e+31, | |
| "step": 10 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.2857142857142857, | |
| "eval_loss": 1.142593873281104e+31, | |
| "eval_runtime": 0.2161, | |
| "eval_samples_per_second": 356.345, | |
| "eval_steps_per_second": 13.884, | |
| "step": 11 | |
| }, | |
| { | |
| "epoch": 2.7272727272727275, | |
| "eval_accuracy": 0.2857142857142857, | |
| "eval_loss": 1.142593873281104e+31, | |
| "eval_runtime": 0.2381, | |
| "eval_samples_per_second": 323.413, | |
| "eval_steps_per_second": 12.601, | |
| "step": 15 | |
| }, | |
| { | |
| "epoch": 2.7272727272727275, | |
| "step": 15, | |
| "total_flos": 1.912117618678579e+16, | |
| "train_loss": 1.0846118163935475e+31, | |
| "train_runtime": 12.9408, | |
| "train_samples_per_second": 160.191, | |
| "train_steps_per_second": 1.159 | |
| } | |
| ], | |
| "logging_steps": 10, | |
| "max_steps": 15, | |
| "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": 1.912117618678579e+16, | |
| "train_batch_size": 32, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |