transformers tensorboard safetensors segformer vision image-segmentation generated_from_trainer base_model:nvidia/mit-b0 license:other endpoints_compatible region:us
---
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: datadome-slider-b0-finetuned-segments-missing-puzzle-mar-1
  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. -->

# datadome-slider-b0-finetuned-segments-missing-puzzle-mar-1

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the bfwggggg/image-with-puzzle dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2458
- Mean Iou: 0.0
- Mean Accuracy: nan
- Overall Accuracy: nan
- Accuracy Missing-puzzle: nan
- Iou Missing-puzzle: 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: 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Missing-puzzle | Iou Missing-puzzle |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------------------:|:------------------:|
| 0.4987        | 5.0   | 20   | 0.6323          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.388         | 10.0  | 40   | 0.4734          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.3014        | 15.0  | 60   | 0.3631          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.3179        | 20.0  | 80   | 0.3405          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.2963        | 25.0  | 100  | 0.2696          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.2458        | 30.0  | 120  | 0.2803          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.2757        | 35.0  | 140  | 0.2635          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.2519        | 40.0  | 160  | 0.2522          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.2349        | 45.0  | 180  | 0.2474          | 0.0      | nan           | nan              | nan                     | 0.0                |
| 0.212         | 50.0  | 200  | 0.2458          | 0.0      | nan           | nan              | nan                     | 0.0                |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
