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---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: custom-object-test3
  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. -->

# custom-object-test3

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the sungile/custom-object-masking3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6728
- Mean Iou: nan
- Mean Accuracy: nan
- Overall Accuracy: nan
- Accuracy Unknown: nan
- Accuracy Background: nan
- Accuracy Object: nan
- Iou Unknown: nan
- Iou Background: nan
- Iou Object: 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unknown | Accuracy Background | Accuracy Object | Iou Unknown | Iou Background | Iou Object |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------:|:-------------------:|:---------------:|:-----------:|:--------------:|:----------:|
| 1.4981        | 0.25  | 20   | 1.5526          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |
| 1.2809        | 0.5   | 40   | 1.4961          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |
| 1.025         | 0.75  | 60   | 1.3031          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |
| 0.9376        | 1.0   | 80   | 0.9104          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |
| 0.8413        | 1.25  | 100  | 0.8012          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |
| 0.7648        | 1.5   | 120  | 0.7258          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |
| 0.7118        | 1.75  | 140  | 0.7015          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |
| 0.6699        | 2.0   | 160  | 0.6728          | nan      | nan           | nan              | nan              | nan                 | nan             | nan         | nan            | nan        |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.1.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0