---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: custom-object-test6
  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-test6

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the sungile/custom-object-masking5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3457
- Mean Iou: 0.3368
- Mean Accuracy: 0.6736
- Overall Accuracy: 0.6736
- Accuracy Unknown: nan
- Accuracy Background: 0.6736
- Accuracy Object: nan
- Iou Unknown: 0.0
- Iou Background: 0.6736
- 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: 3

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------:|:-------------------:|:---------------:|:-----------:|:--------------:|:----------:|
| 0.7667        | 0.25  | 20   | 1.0272          | 0.3026   | 0.9079        | 0.9079           | nan              | 0.9079              | nan             | 0.0         | 0.9079         | 0.0        |
| 0.8127        | 0.5   | 40   | 0.8213          | 0.2803   | 0.8409        | 0.8409           | nan              | 0.8409              | nan             | 0.0         | 0.8409         | 0.0        |
| 0.5588        | 0.75  | 60   | 0.7310          | 0.4304   | 0.8608        | 0.8608           | nan              | 0.8608              | nan             | 0.0         | 0.8608         | nan        |
| 0.6156        | 1.0   | 80   | 0.5317          | 0.3130   | 0.6261        | 0.6261           | nan              | 0.6261              | nan             | 0.0         | 0.6261         | nan        |
| 0.5077        | 1.25  | 100  | 0.4617          | 0.3482   | 0.6964        | 0.6964           | nan              | 0.6964              | nan             | 0.0         | 0.6964         | nan        |
| 0.5612        | 1.5   | 120  | 0.4336          | 0.3341   | 0.6683        | 0.6683           | nan              | 0.6683              | nan             | 0.0         | 0.6683         | nan        |
| 0.4468        | 1.75  | 140  | 0.3946          | 0.3442   | 0.6883        | 0.6883           | nan              | 0.6883              | nan             | 0.0         | 0.6883         | nan        |
| 0.292         | 2.0   | 160  | 0.3554          | 0.3041   | 0.6081        | 0.6081           | nan              | 0.6081              | nan             | 0.0         | 0.6081         | nan        |
| 0.3769        | 2.25  | 180  | 0.3798          | 0.3402   | 0.6805        | 0.6805           | nan              | 0.6805              | nan             | 0.0         | 0.6805         | nan        |
| 0.3386        | 2.5   | 200  | 0.3493          | 0.3147   | 0.6293        | 0.6293           | nan              | 0.6293              | nan             | 0.0         | 0.6293         | nan        |
| 0.2689        | 2.75  | 220  | 0.3736          | 0.3492   | 0.6984        | 0.6984           | nan              | 0.6984              | nan             | 0.0         | 0.6984         | nan        |
| 0.2539        | 3.0   | 240  | 0.3457          | 0.3368   | 0.6736        | 0.6736           | nan              | 0.6736              | nan             | 0.0         | 0.6736         | nan        |


### Framework versions

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