---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-sidewalk-10k-steps
  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-finetuned-sidewalk-10k-steps

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the fuji12345/sample-segmentation_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1181
- Mean Iou: 0.0
- Mean Accuracy: nan
- Overall Accuracy: nan
- Accuracy Hallucination: nan
- Accuracy Normal: nan
- Iou Hallucination: 0.0
- Iou Normal: 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: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: polynomial
- training_steps: 200

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Hallucination | Accuracy Normal | Iou Hallucination | Iou Normal |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------:|:---------------:|:-----------------:|:----------:|
| No log        | 1.0    | 21   | 0.4468          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| No log        | 2.0    | 42   | 0.2196          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| No log        | 3.0    | 63   | 0.2136          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| No log        | 4.0    | 84   | 0.1816          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| 0.3217        | 5.0    | 105  | 0.1449          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| 0.3217        | 6.0    | 126  | 0.1380          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| 0.3217        | 7.0    | 147  | 0.1239          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| 0.3217        | 8.0    | 168  | 0.1247          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| 0.3217        | 9.0    | 189  | 0.1163          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |
| 0.1596        | 9.5238 | 200  | 0.1181          | 0.0      | nan           | nan              | nan                    | nan             | 0.0               | 0.0        |


### Framework versions

- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1