---
license: other
base_model: nvidia/mit-b5
tags:
- generated_from_trainer
model-index:
- name: Augmented-MIT-b5
  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. -->

# Augmented-MIT-b5

This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0371
- Mean Iou: 0.3355
- Mean Accuracy: 0.6711
- Overall Accuracy: 0.6711
- Accuracy Background: nan
- Accuracy Crack: 0.6711
- Iou Background: 0.0
- Iou Crack: 0.6711

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:--------------:|:--------------:|:---------:|
| 0.0365        | 0.14  | 1000 | 0.0446          | 0.3813   | 0.7627        | 0.7627           | nan                 | 0.7627         | 0.0            | 0.7627    |
| 0.0114        | 0.27  | 2000 | 0.0411          | 0.3691   | 0.7381        | 0.7381           | nan                 | 0.7381         | 0.0            | 0.7381    |
| 0.0148        | 0.41  | 3000 | 0.0400          | 0.3224   | 0.6448        | 0.6448           | nan                 | 0.6448         | 0.0            | 0.6448    |
| 0.0134        | 0.54  | 4000 | 0.0413          | 0.2819   | 0.5638        | 0.5638           | nan                 | 0.5638         | 0.0            | 0.5638    |
| 0.013         | 0.68  | 5000 | 0.0392          | 0.3618   | 0.7235        | 0.7235           | nan                 | 0.7235         | 0.0            | 0.7235    |
| 0.0532        | 0.81  | 6000 | 0.0373          | 0.3355   | 0.6710        | 0.6710           | nan                 | 0.6710         | 0.0            | 0.6710    |
| 0.0508        | 0.95  | 7000 | 0.0371          | 0.3355   | 0.6711        | 0.6711           | nan                 | 0.6711         | 0.0            | 0.6711    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3