---
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-docboundary-nov-13
  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-finetuned-segments-docboundary-nov-13

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the vigneshgs7/doc-boundary dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2806
- Mean Iou: 0.4886
- Mean Accuracy: 0.9771
- Overall Accuracy: 0.9771
- Accuracy Page: nan
- Accuracy Surface: 0.9771
- Iou Page: 0.0
- Iou Surface: 0.9771

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Page | Accuracy Surface | Iou Page | Iou Surface |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------:|:----------------:|:--------:|:-----------:|
| 0.4191        | 2.22  | 20   | 0.5643          | 0.4651   | 0.9301        | 0.9301           | nan           | 0.9301           | 0.0      | 0.9301      |
| 0.3141        | 4.44  | 40   | 0.3959          | 0.4866   | 0.9733        | 0.9733           | nan           | 0.9733           | 0.0      | 0.9733      |
| 0.2865        | 6.67  | 60   | 0.2889          | 0.4870   | 0.9740        | 0.9740           | nan           | 0.9740           | 0.0      | 0.9740      |
| 0.3955        | 8.89  | 80   | 0.2806          | 0.4886   | 0.9771        | 0.9771           | nan           | 0.9771           | 0.0      | 0.9771      |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1