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metadata
license: other
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: parking-utcustom-train-SF-RGBD-b0_6
    results: []

parking-utcustom-train-SF-RGBD-b0_6

This model is a fine-tuned version of nvidia/mit-b0 on the sam1120/parking-utcustom-train dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0140
  • 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: 0.0004
  • 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: 150

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
0.3631 20.0 20 0.3717 1.0 1.0 1.0 nan nan 1.0 nan nan 1.0
0.1606 40.0 40 0.0813 1.0 1.0 1.0 nan nan 1.0 nan nan 1.0
0.0988 60.0 60 0.0233 1.0 1.0 1.0 nan nan 1.0 nan nan 1.0
0.08 80.0 80 0.0209 1.0 1.0 1.0 nan nan 1.0 nan nan 1.0
0.0627 100.0 100 0.0161 1.0 1.0 1.0 nan nan 1.0 nan nan 1.0
0.0426 120.0 120 0.0137 1.0 1.0 1.0 nan nan 1.0 nan nan 1.0
0.0374 140.0 140 0.0140 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