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metadata
license: other
tags:
  - image-segmentation
  - vision
  - generated_from_trainer
model-index:
  - name: mobilenet_v2_1-10k-steps
    results: []

mobilenet_v2_1-10k-steps

This model is a fine-tuned version of google/mobilenet_v2_1.0_224 on the Efferbach/lane_master2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0827
  • Mean Iou: 0.0
  • Mean Accuracy: 0.0
  • Overall Accuracy: 0.0
  • Accuracy Background: nan
  • Accuracy Left: 0.0
  • Accuracy Right: 0.0
  • Iou Background: 0.0
  • Iou Left: 0.0
  • Iou Right: 0.0

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: 6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • training_steps: 10000

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Background Accuracy Left Accuracy Right Iou Background Iou Left Iou Right
0.3253 1.0 385 0.0989 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.128 2.0 770 0.1518 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1212 3.0 1155 0.1852 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.117 4.0 1540 0.1446 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1148 5.0 1925 0.1087 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1167 6.0 2310 0.1502 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1128 7.0 2695 0.0882 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1156 8.0 3080 0.1005 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1164 9.0 3465 0.0844 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1128 10.0 3850 0.1497 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1151 11.0 4235 0.1024 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1112 12.0 4620 0.0869 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1093 13.0 5005 0.0940 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1102 14.0 5390 0.0914 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1111 15.0 5775 0.1047 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1087 16.0 6160 0.1104 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1105 17.0 6545 0.0970 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1083 18.0 6930 0.0868 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1077 19.0 7315 0.1121 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1115 20.0 7700 0.2092 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1102 21.0 8085 0.0850 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1077 22.0 8470 0.1011 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1111 23.0 8855 0.1136 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1099 24.0 9240 0.1001 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1086 25.0 9625 0.0997 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0
0.1066 25.97 10000 0.0827 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.28.0.dev0
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3