---
license: other
base_model: nvidia/mit-b5
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: ecc_segformerv3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ecc_segformerv3

This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/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