Image Classification
timm
Safetensors
PyTorch
Turkish
English
timm-image-classification
efficientnetv2
vehicle-classification
car-body-type
Eval Results (legacy)
Instructions to use ryan12345441/car-body-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use ryan12345441/car-body-classifier with timm:
import timm model = timm.create_model("hf_hub:ryan12345441/car-body-classifier", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "arch_key": "efficientnetv2_s", | |
| "timm_id": "tf_efficientnetv2_s", | |
| "role": "active", | |
| "class_names": [ | |
| "SUV", | |
| "VAN", | |
| "STATION_WAGON", | |
| "MICRO", | |
| "ACIK_TEKERLEKLI_F1_ARACLARI", | |
| "SEDAN", | |
| "HATCHBACK", | |
| "PICK_UP" | |
| ], | |
| "num_classes": 8, | |
| "seed": 20260506, | |
| "best_epoch": 13, | |
| "best_val_f1_macro": 0.957292, | |
| "best_val_accuracy": 0.970439, | |
| "best_val_f1_weighted": 0.970565, | |
| "per_class_val_f1": { | |
| "SUV": 0.972405, | |
| "VAN": 0.988434, | |
| "STATION_WAGON": 0.960352, | |
| "MICRO": 0.887417, | |
| "ACIK_TEKERLEKLI_F1_ARACLARI": 0.996005, | |
| "SEDAN": 0.976542, | |
| "HATCHBACK": 0.927184, | |
| "PICK_UP": 0.95 | |
| }, | |
| "hyperparameters": { | |
| "batch_size": 32, | |
| "epochs_configured": 30, | |
| "epochs_executed": 30, | |
| "learning_rate": 0.0003, | |
| "optimizer": "adamw", | |
| "weight_decay": 0.0001, | |
| "label_smoothing": 0.05, | |
| "early_stopping_patience": 7, | |
| "checkpoint_metric": "val_f1_macro" | |
| }, | |
| "imbalance_handling": { | |
| "strategy": "class_weight", | |
| "class_counts": { | |
| "SUV": 7682, | |
| "VAN": 6319, | |
| "STATION_WAGON": 1077, | |
| "MICRO": 386, | |
| "ACIK_TEKERLEKLI_F1_ARACLARI": 1801, | |
| "SEDAN": 7010, | |
| "HATCHBACK": 3006, | |
| "PICK_UP": 5115 | |
| }, | |
| "minority_classes": { | |
| "STATION_WAGON": 1077, | |
| "MICRO": 386, | |
| "ACIK_TEKERLEKLI_F1_ARACLARI": 1801, | |
| "HATCHBACK": 3006 | |
| }, | |
| "weighted_sampler_used": false, | |
| "class_weight_used": true | |
| }, | |
| "augmentation_policy": { | |
| "mixup_alpha": 0.0, | |
| "cutmix_alpha": 0.0, | |
| "remix_enabled": false, | |
| "use_mixup": false, | |
| "use_cutmix": false | |
| }, | |
| "pretrained_weights": "imagenet", | |
| "fully_fine_tune": true, | |
| "precision_policy": "fp32", | |
| "preprocessing_config": "preprocessing_current.json", | |
| "preprocessing_config_hash": "9351c46b59ab9820", | |
| "train_manifest": "data/manifests/splits/train_manifest.jsonl", | |
| "train_manifest_hash": "495ce3be11faa67f", | |
| "val_manifest": "data/manifests/splits/val_manifest.jsonl", | |
| "val_manifest_hash": "0ff8b5181f266ef6", | |
| "param_count": 20187736, | |
| "approx_mb_fp32": 86, | |
| "artifact_path": "artifacts/models/efficientnetv2_s_best.pt", | |
| "artifact_bytes": 81653138, | |
| "artifact_mb": 77.87, | |
| "artifact_sha256": "2e8f2810d10c9b56042abe0f65aef28c514e76c0830dd418f96e1e4b41c7392d", | |
| "is_dry_run": false, | |
| "is_final": true, | |
| "training_log_path": "artifacts/training/training_log.jsonl", | |
| "packaged_as": "final_calibrated", | |
| "model_file": "efficientnetv2_s_best.pt", | |
| "calibration_file": "calibration.json", | |
| "calibration": { | |
| "method": "temperature_scaling", | |
| "temperature": 0.565484, | |
| "fit_split": "validation", | |
| "apply_at_inference": "probs = softmax(logits / temperature)" | |
| }, | |
| "test_metrics_raw": { | |
| "accuracy": 0.96663, | |
| "f1_macro": 0.954043, | |
| "f1_weighted": 0.966779, | |
| "nll": 0.248412, | |
| "brier": 0.078886, | |
| "ece_15_bins": 0.126878, | |
| "mean_confidence": 0.839925 | |
| }, | |
| "test_metrics_calibrated": { | |
| "accuracy": 0.96663, | |
| "f1_macro": 0.954043, | |
| "f1_weighted": 0.966779, | |
| "nll": 0.152494, | |
| "brier": 0.055011, | |
| "ece_15_bins": 0.009874, | |
| "mean_confidence": 0.968902 | |
| } | |
| } |