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

# baseline_plantorgans_model

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the jpodivin/plantorgans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5639
- Mean Iou: 0.1095
- Mean Accuracy: 0.1373
- Overall Accuracy: 0.1858
- Accuracy Void: nan
- Accuracy Fruit: 0.5208
- Accuracy Leaf: 0.0197
- Accuracy Flower: 0.0
- Accuracy Stem: 0.0087
- Iou Void: 0.0
- Iou Fruit: 0.5192
- Iou Leaf: 0.0197
- Iou Flower: 0.0
- Iou Stem: 0.0087

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Void | Accuracy Fruit | Accuracy Leaf | Accuracy Flower | Accuracy Stem | Iou Void | Iou Fruit | Iou Leaf | Iou Flower | Iou Stem |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------:|:--------------:|:-------------:|:---------------:|:-------------:|:--------:|:---------:|:--------:|:----------:|:--------:|
| 0.8673        | 1.0   | 719  | 0.4827          | 0.1301   | 0.1639        | 0.2227           | nan           | 0.6188         | 0.0271        | 0.0             | 0.0098        | 0.0      | 0.6135    | 0.0271   | 0.0        | 0.0098   |
| 0.4457        | 2.0   | 1438 | 0.5555          | 0.1130   | 0.1416        | 0.1927           | nan           | 0.5224         | 0.0305        | 0.0             | 0.0135        | 0.0      | 0.5209    | 0.0305   | 0.0        | 0.0135   |
| 0.3272        | 3.0   | 2157 | 0.5639          | 0.1095   | 0.1373        | 0.1858           | nan           | 0.5208         | 0.0197        | 0.0             | 0.0087        | 0.0      | 0.5192    | 0.0197   | 0.0        | 0.0087   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0