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