---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: mit-b0_whitefly
  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. -->

# mit-b0_whitefly

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2644
- Mean Iou: 0.4948
- Mean Accuracy: 0.4968
- Overall Accuracy: 0.9893
- Accuracy Background: 0.9907
- Accuracy Whitefly: 0.0029
- Iou Background: 0.9893
- Iou Whitefly: 0.0004

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Whitefly | Iou Background | Iou Whitefly |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-----------------:|:--------------:|:------------:|
| 0.6275        | 0.4   | 20   | 0.6849          | 0.3529   | 0.4550        | 0.7049           | 0.7056              | 0.2044            | 0.7048         | 0.0010       |
| 0.4423        | 0.8   | 40   | 0.5826          | 0.4745   | 0.5157        | 0.9468           | 0.9480              | 0.0834            | 0.9468         | 0.0022       |
| 0.3793        | 1.2   | 60   | 0.4444          | 0.4868   | 0.4927        | 0.9731           | 0.9744              | 0.0110            | 0.9731         | 0.0006       |
| 0.3102        | 1.6   | 80   | 0.3347          | 0.4976   | 0.4986        | 0.9949           | 0.9963              | 0.0009            | 0.9949         | 0.0002       |
| 0.272         | 2.0   | 100  | 0.3100          | 0.4983   | 0.4991        | 0.9963           | 0.9977              | 0.0004            | 0.9963         | 0.0002       |
| 0.3003        | 2.4   | 120  | 0.2579          | 0.4983   | 0.4991        | 0.9965           | 0.9979              | 0.0003            | 0.9965         | 0.0001       |
| 0.2558        | 2.8   | 140  | 0.2644          | 0.4948   | 0.4968        | 0.9893           | 0.9907              | 0.0029            | 0.9893         | 0.0004       |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.6.0+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1