---
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_trainer
datasets:
- scene_parse_150
model-index:
- name: segformer-b0-scene-parse-150
  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. -->

# segformer-b0-scene-parse-150

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the scene_parse_150 dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9476
- Mean Iou: 0.0059
- Mean Accuracy: 0.0467
- Overall Accuracy: 0.0792
- Per Category Iou: [0.015290646787191019, 0.0, 0.0, 0.29707155265364804, 0.0, 0.08276914236227738, 0.0, 0.0, 0.0, 0.0, 0.012636310927907107, 0.0, 0.0, 0.0, 0.08227787105184403, 0.0, 0.0, 0.0, 0.02964898714815463, 0.0, 0.0, nan, 0.001510992695378508, nan, 0.0, 0.0, 0.0, 0.0008937418640346616, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0006580782683957911, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.15182749560810285, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 4.8507583352197394e-05, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.09386101051905502, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
- Per Category Accuracy: [0.015300257646825658, nan, nan, 0.3063194873378629, nan, 0.4663087217719412, nan, nan, 0.0, nan, 0.015581846316572973, nan, nan, nan, 0.09177343204121063, 0.0, nan, nan, 0.040619224731872905, 0.0, nan, nan, 0.00745248489659126, nan, 0.0, nan, nan, 0.0011775849269129355, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0006601654719106768, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.1750304681339164, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 5.521201413427562e-05, nan, nan, nan, nan, nan, nan, 0.18748493024857915, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 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: 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 | Per Category Iou                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         | Per Category Accuracy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| 4.8424        | 1.0   | 20   | 4.9476          | 0.0059   | 0.0467        | 0.0792           | [0.015290646787191019, 0.0, 0.0, 0.29707155265364804, 0.0, 0.08276914236227738, 0.0, 0.0, 0.0, 0.0, 0.012636310927907107, 0.0, 0.0, 0.0, 0.08227787105184403, 0.0, 0.0, 0.0, 0.02964898714815463, 0.0, 0.0, nan, 0.001510992695378508, nan, 0.0, 0.0, 0.0, 0.0008937418640346616, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0006580782683957911, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.15182749560810285, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 4.8507583352197394e-05, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.09386101051905502, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] | [0.015300257646825658, nan, nan, 0.3063194873378629, nan, 0.4663087217719412, nan, nan, 0.0, nan, 0.015581846316572973, nan, nan, nan, 0.09177343204121063, 0.0, nan, nan, 0.040619224731872905, 0.0, nan, nan, 0.00745248489659126, nan, 0.0, nan, nan, 0.0011775849269129355, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0006601654719106768, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.1750304681339164, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 5.521201413427562e-05, nan, nan, nan, nan, nan, nan, 0.18748493024857915, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan] |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1