segcrack9k_conglomerate_segformer_aug

This model is a fine-tuned version of nvidia/mit-b5 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0362
  • Mean Iou: 0.3412
  • Mean Accuracy: 0.6823
  • Overall Accuracy: 0.6823
  • Accuracy Background: nan
  • Accuracy Crack: 0.6823
  • Iou Background: 0.0
  • Iou Crack: 0.6823

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Background Accuracy Crack Iou Background Iou Crack
0.0323 0.14 1000 0.0445 0.3573 0.7146 0.7146 nan 0.7146 0.0 0.7146
0.0222 0.27 2000 0.0394 0.3591 0.7181 0.7181 nan 0.7181 0.0 0.7181
0.0335 0.41 3000 0.0404 0.2907 0.5813 0.5813 nan 0.5813 0.0 0.5813
0.013 0.54 4000 0.0384 0.3244 0.6489 0.6489 nan 0.6489 0.0 0.6489
0.0159 0.68 5000 0.0382 0.3088 0.6176 0.6176 nan 0.6176 0.0 0.6176
0.0608 0.81 6000 0.0366 0.3251 0.6502 0.6502 nan 0.6502 0.0 0.6502
0.1738 0.95 7000 0.0362 0.3412 0.6823 0.6823 nan 0.6823 0.0 0.6823

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.3
  • Tokenizers 0.13.3
Downloads last month
13
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for varcoder/segcrack9k_conglomerate_segformer_aug

Base model

nvidia/mit-b5
Finetuned
(42)
this model