segformer-finetuned-biofilm_MRCNNv1_halfjoin

This model is a fine-tuned version of nvidia/mit-b0 on the heroza/biofilm_MRCNNv1_halfjoin dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0208
  • Mean Iou: 0.4961
  • Mean Accuracy: 0.9923
  • Overall Accuracy: 0.9923
  • Accuracy Background: 0.9923
  • Accuracy Biofilm: nan
  • Iou Background: 0.9923
  • Iou Biofilm: 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 Biofilm Iou Background Iou Biofilm
0.0713 1.0 478 0.0381 0.4953 0.9906 0.9906 0.9906 nan 0.9906 0.0
0.044 2.0 956 0.0202 0.4975 0.9949 0.9949 0.9949 nan 0.9949 0.0
0.041 3.0 1434 0.0181 0.4972 0.9945 0.9945 0.9945 nan 0.9945 0.0
0.0361 4.0 1912 0.0203 0.4963 0.9926 0.9926 0.9926 nan 0.9926 0.0
0.0357 5.0 2390 0.0163 0.4971 0.9942 0.9942 0.9942 nan 0.9942 0.0
0.0336 6.0 2868 0.0340 0.4958 0.9915 0.9915 0.9915 nan 0.9915 0.0
0.0295 7.0 3346 0.0126 0.4978 0.9955 0.9955 0.9955 nan 0.9955 0.0
0.0251 8.0 3824 0.0220 0.4957 0.9915 0.9915 0.9915 nan 0.9915 0.0
0.0265 9.0 4302 0.0182 0.4966 0.9933 0.9933 0.9933 nan 0.9933 0.0
0.0238 10.0 4780 0.0155 0.4970 0.9940 0.9940 0.9940 nan 0.9940 0.0
0.0258 11.0 5258 0.0181 0.4966 0.9931 0.9931 0.9931 nan 0.9931 0.0
0.0264 12.0 5736 0.0179 0.4969 0.9938 0.9938 0.9938 nan 0.9938 0.0
0.0265 13.0 6214 0.0222 0.4959 0.9917 0.9917 0.9917 nan 0.9917 0.0
0.0219 14.0 6692 0.0200 0.4962 0.9925 0.9925 0.9925 nan 0.9925 0.0
0.0213 15.0 7170 0.0234 0.4958 0.9916 0.9916 0.9916 nan 0.9916 0.0
0.0192 16.0 7648 0.0199 0.4961 0.9922 0.9922 0.9922 nan 0.9922 0.0
0.0232 17.0 8126 0.0208 0.4961 0.9923 0.9923 0.9923 nan 0.9923 0.0
0.0219 18.0 8604 0.0245 0.4955 0.9909 0.9909 0.9909 nan 0.9909 0.0
0.0201 19.0 9082 0.0211 0.4961 0.9922 0.9922 0.9922 nan 0.9922 0.0
0.0192 20.0 9560 0.0207 0.4962 0.9923 0.9923 0.9923 nan 0.9923 0.0
0.0175 20.92 10000 0.0208 0.4961 0.9923 0.9923 0.9923 nan 0.9923 0.0

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.14.4
  • Tokenizers 0.15.1
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