ecc_segformerv1

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

• Loss: 0.0351
• Mean Iou: 0.9171
• Mean Accuracy: 0.8041
• Overall Accuracy: 0.8041
• Accuracy Background: nan
• Accuracy Crack: 0.8041
• Iou Background: 0.0
• Iou Crack: 0.9171

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: 1337
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: polynomial
• training_steps: 10000

Framework versions

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