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

# Segments

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9830
- Mean Iou: 0.1931
- Mean Accuracy: 0.2401
- Overall Accuracy: 0.7586
- Accuracy Unlabeled: nan
- Accuracy Flat-road: 0.7259
- Accuracy Flat-sidewalk: 0.9518
- Accuracy Flat-crosswalk: 0.5588
- Accuracy Flat-cyclinglane: 0.5550
- Accuracy Flat-parkingdriveway: 0.1159
- Accuracy Flat-railtrack: nan
- Accuracy Flat-curb: 0.1277
- Accuracy Human-person: 0.0990
- Accuracy Human-rider: 0.0
- Accuracy Vehicle-car: 0.9049
- Accuracy Vehicle-truck: 0.0
- Accuracy Vehicle-bus: 0.0
- Accuracy Vehicle-tramtrain: nan
- Accuracy Vehicle-motorcycle: 0.0
- Accuracy Vehicle-bicycle: 0.0
- Accuracy Vehicle-caravan: 0.0
- Accuracy Vehicle-cartrailer: 0.0
- Accuracy Construction-building: 0.8590
- Accuracy Construction-door: 0.0
- Accuracy Construction-wall: 0.0013
- Accuracy Construction-fenceguardrail: 0.0
- Accuracy Construction-bridge: 0.0
- Accuracy Construction-tunnel: nan
- Accuracy Construction-stairs: 0.0
- Accuracy Object-pole: 0.0088
- Accuracy Object-trafficsign: 0.0
- Accuracy Object-trafficlight: 0.0
- Accuracy Nature-vegetation: 0.9206
- Accuracy Nature-terrain: 0.7756
- Accuracy Sky: 0.8391
- Accuracy Void-ground: 0.0
- Accuracy Void-dynamic: 0.0
- Accuracy Void-static: 0.0
- Accuracy Void-unclear: 0.0
- Iou Unlabeled: nan
- Iou Flat-road: 0.5951
- Iou Flat-sidewalk: 0.7822
- Iou Flat-crosswalk: 0.5498
- Iou Flat-cyclinglane: 0.4666
- Iou Flat-parkingdriveway: 0.1001
- Iou Flat-railtrack: nan
- Iou Flat-curb: 0.1078
- Iou Human-person: 0.0979
- Iou Human-rider: 0.0
- Iou Vehicle-car: 0.6265
- Iou Vehicle-truck: 0.0
- Iou Vehicle-bus: 0.0
- Iou Vehicle-tramtrain: nan
- Iou Vehicle-motorcycle: 0.0
- Iou Vehicle-bicycle: 0.0
- Iou Vehicle-caravan: 0.0
- Iou Vehicle-cartrailer: 0.0
- Iou Construction-building: 0.4997
- Iou Construction-door: 0.0
- Iou Construction-wall: 0.0013
- Iou Construction-fenceguardrail: 0.0
- Iou Construction-bridge: 0.0
- Iou Construction-tunnel: nan
- Iou Construction-stairs: 0.0
- Iou Object-pole: 0.0088
- Iou Object-trafficsign: 0.0
- Iou Object-trafficlight: 0.0
- Iou Nature-vegetation: 0.7405
- Iou Nature-terrain: 0.6034
- Iou Sky: 0.8052
- Iou Void-ground: 0.0
- Iou Void-dynamic: 0.0
- Iou Void-static: 0.0
- Iou Void-unclear: 0.0

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results



### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3