ecc_segformerv3 / README.md
rishitunu's picture
End of training
fa56bfe
metadata
license: other
base_model: nvidia/mit-b5
tags:
  - image-segmentation
  - vision
  - generated_from_trainer
model-index:
  - name: ecc_segformerv3
    results: []

ecc_segformerv3

This model is a fine-tuned version of nvidia/mit-b5 on the rishitunu/ecc_crackdetector_dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1344
  • Mean Iou: 0.0005
  • Mean Accuracy: 0.0010
  • Overall Accuracy: 0.0010
  • Accuracy Background: nan
  • Accuracy Crack: 0.0010
  • Iou Background: 0.0
  • Iou Crack: 0.0010

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: 0.0006
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Background Accuracy Crack Iou Background Iou Crack
0.1306 1.0 1001 0.1114 0.0 0.0 0.0 nan 0.0 0.0 0.0
0.107 2.0 2002 0.1238 0.0000 0.0000 0.0000 nan 0.0000 0.0 0.0000
0.1285 3.0 3003 0.1631 0.0024 0.0049 0.0049 nan 0.0049 0.0 0.0048
0.0887 4.0 4004 0.1083 0.0002 0.0003 0.0003 nan 0.0003 0.0 0.0003
0.0828 5.0 5000 0.1344 0.0005 0.0010 0.0010 nan 0.0010 0.0 0.0010

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cpu
  • Datasets 2.14.4
  • Tokenizers 0.13.3