--- license: other tags: - generated_from_trainer model-index: - name: parking-utcustom-train-SF-RGB-b0_7 results: [] --- # parking-utcustom-train-SF-RGB-b0_7 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3553 - Mean Iou: 1.0 - Mean Accuracy: 1.0 - Overall Accuracy: 1.0 - Accuracy Unlabeled: nan - Accuracy Parking: nan - Accuracy Unparking: 1.0 - Iou Unlabeled: nan - Iou Parking: nan - Iou Unparking: 1.0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 120 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Parking | Accuracy Unparking | Iou Unlabeled | Iou Parking | Iou Unparking | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:| | 0.8356 | 20.0 | 20 | 0.8943 | 0.3246 | 0.9737 | 0.9737 | nan | nan | 0.9737 | 0.0 | 0.0 | 0.9737 | | 0.6536 | 40.0 | 40 | 0.6398 | 0.3294 | 0.9881 | 0.9881 | nan | nan | 0.9881 | 0.0 | 0.0 | 0.9881 | | 0.5476 | 60.0 | 60 | 0.4690 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | | 0.4559 | 80.0 | 80 | 0.3922 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | | 0.4311 | 100.0 | 100 | 0.3626 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | | 0.399 | 120.0 | 120 | 0.3553 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | ### Framework versions - Transformers 4.30.2 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3