---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: earthquake
  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. -->

# earthquake

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the gokceKy/earthquake dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6395
- Mean Iou: 0.1763
- Mean Accuracy: 0.4255
- Overall Accuracy: 0.6211
- Accuracy Background: nan
- Accuracy Car: nan
- Accuracy Earthquake-roads: 0.4591
- Accuracy Other: 0.8175
- Accuracy Road: 0.0
- Accuracy Road-cracks: nan
- Accuracy Sky: nan
- Accuracy Wall: nan
- Iou Background: 0.0
- Iou Car: 0.0
- Iou Earthquake-roads: 0.4499
- Iou Other: 0.7841
- Iou Road: 0.0
- Iou Road-cracks: 0.0
- Iou Sky: 0.0
- Iou Wall: nan

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Car | Accuracy Earthquake-roads | Accuracy Other | Accuracy Road | Accuracy Road-cracks | Accuracy Sky | Accuracy Wall | Iou Background | Iou Car | Iou Earthquake-roads | Iou Other | Iou Road | Iou Road-cracks | Iou Sky | Iou Wall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------:|:-------------------------:|:--------------:|:-------------:|:--------------------:|:------------:|:-------------:|:--------------:|:-------:|:--------------------:|:---------:|:--------:|:---------------:|:-------:|:--------:|
| 1.0736        | 2.5   | 5    | 1.6917          | 0.1818   | 0.3763        | 0.5984           | nan                 | nan          | 0.3113                    | 0.8176         | 0.0           | nan                  | nan          | nan           | 0.0            | 0.0     | 0.3077               | 0.7830    | 0.0      | 0.0             | nan     | nan      |
| 0.8949        | 5.0   | 10   | 1.6395          | 0.1763   | 0.4255        | 0.6211           | nan                 | nan          | 0.4591                    | 0.8175         | 0.0           | nan                  | nan          | nan           | 0.0            | 0.0     | 0.4499               | 0.7841    | 0.0      | 0.0             | 0.0     | nan      |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.4.1+cpu
- Datasets 3.1.0
- Tokenizers 0.20.3