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: segformer-b0-finetuned-arabidopsis-roots-v02
  results: []
---

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# segformer-b0-finetuned-arabidopsis-roots-v02

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the jacquelinegrimm/arabidopsis-roots-v02 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0500
- Mean Iou: 0.4449
- Mean Accuracy: 0.8899
- Overall Accuracy: 0.8899
- Accuracy Background: nan
- Accuracy Seedling: 0.8899
- Iou Background: 0.0
- Iou Seedling: 0.8899

## 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: 4
- eval_batch_size: 4
- 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 Background | Accuracy Seedling | Iou Background | Iou Seedling |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-----------------:|:--------------:|:------------:|
| 0.4792        | 1.0   | 20   | 0.5681          | 0.4482   | 0.8964        | 0.8964           | nan                 | 0.8964            | 0.0            | 0.8964       |
| 0.3118        | 2.0   | 40   | 0.3829          | 0.4641   | 0.9282        | 0.9282           | nan                 | 0.9282            | 0.0            | 0.9282       |
| 0.2481        | 3.0   | 60   | 0.2563          | 0.4722   | 0.9445        | 0.9445           | nan                 | 0.9445            | 0.0            | 0.9445       |
| 0.2159        | 4.0   | 80   | 0.2402          | 0.4695   | 0.9389        | 0.9389           | nan                 | 0.9389            | 0.0            | 0.9389       |
| 0.1721        | 5.0   | 100  | 0.1644          | 0.4627   | 0.9254        | 0.9254           | nan                 | 0.9254            | 0.0            | 0.9254       |
| 0.1494        | 6.0   | 120  | 0.1407          | 0.4595   | 0.9189        | 0.9189           | nan                 | 0.9189            | 0.0            | 0.9189       |
| 0.1286        | 7.0   | 140  | 0.1213          | 0.4616   | 0.9233        | 0.9233           | nan                 | 0.9233            | 0.0            | 0.9233       |
| 0.1233        | 8.0   | 160  | 0.1097          | 0.4469   | 0.8939        | 0.8939           | nan                 | 0.8939            | 0.0            | 0.8939       |
| 0.108         | 9.0   | 180  | 0.0963          | 0.4419   | 0.8837        | 0.8837           | nan                 | 0.8837            | 0.0            | 0.8837       |
| 0.0968        | 10.0  | 200  | 0.0998          | 0.4491   | 0.8983        | 0.8983           | nan                 | 0.8983            | 0.0            | 0.8983       |
| 0.1041        | 11.0  | 220  | 0.0849          | 0.4354   | 0.8708        | 0.8708           | nan                 | 0.8708            | 0.0            | 0.8708       |
| 0.0842        | 12.0  | 240  | 0.0795          | 0.4444   | 0.8888        | 0.8888           | nan                 | 0.8888            | 0.0            | 0.8888       |
| 0.0896        | 13.0  | 260  | 0.0756          | 0.4402   | 0.8803        | 0.8803           | nan                 | 0.8803            | 0.0            | 0.8803       |
| 0.077         | 14.0  | 280  | 0.0797          | 0.4484   | 0.8968        | 0.8968           | nan                 | 0.8968            | 0.0            | 0.8968       |
| 0.0767        | 15.0  | 300  | 0.0690          | 0.4389   | 0.8779        | 0.8779           | nan                 | 0.8779            | 0.0            | 0.8779       |
| 0.0776        | 16.0  | 320  | 0.0665          | 0.4355   | 0.8710        | 0.8710           | nan                 | 0.8710            | 0.0            | 0.8710       |
| 0.0789        | 17.0  | 340  | 0.0680          | 0.4450   | 0.8901        | 0.8901           | nan                 | 0.8901            | 0.0            | 0.8901       |
| 0.071         | 18.0  | 360  | 0.0660          | 0.4424   | 0.8848        | 0.8848           | nan                 | 0.8848            | 0.0            | 0.8848       |
| 0.0661        | 19.0  | 380  | 0.0677          | 0.4371   | 0.8742        | 0.8742           | nan                 | 0.8742            | 0.0            | 0.8742       |
| 0.0784        | 20.0  | 400  | 0.0639          | 0.4402   | 0.8805        | 0.8805           | nan                 | 0.8805            | 0.0            | 0.8805       |
| 0.0789        | 21.0  | 420  | 0.0602          | 0.4369   | 0.8737        | 0.8737           | nan                 | 0.8737            | 0.0            | 0.8737       |
| 0.0756        | 22.0  | 440  | 0.0595          | 0.4313   | 0.8627        | 0.8627           | nan                 | 0.8627            | 0.0            | 0.8627       |
| 0.0563        | 23.0  | 460  | 0.0581          | 0.4420   | 0.8839        | 0.8839           | nan                 | 0.8839            | 0.0            | 0.8839       |
| 0.0713        | 24.0  | 480  | 0.0570          | 0.4438   | 0.8875        | 0.8875           | nan                 | 0.8875            | 0.0            | 0.8875       |
| 0.0594        | 25.0  | 500  | 0.0579          | 0.4478   | 0.8955        | 0.8955           | nan                 | 0.8955            | 0.0            | 0.8955       |
| 0.0636        | 26.0  | 520  | 0.0582          | 0.4523   | 0.9046        | 0.9046           | nan                 | 0.9046            | 0.0            | 0.9046       |
| 0.053         | 27.0  | 540  | 0.0558          | 0.4431   | 0.8863        | 0.8863           | nan                 | 0.8863            | 0.0            | 0.8863       |
| 0.0688        | 28.0  | 560  | 0.0561          | 0.4470   | 0.8939        | 0.8939           | nan                 | 0.8939            | 0.0            | 0.8939       |
| 0.0564        | 29.0  | 580  | 0.0542          | 0.4442   | 0.8885        | 0.8885           | nan                 | 0.8885            | 0.0            | 0.8885       |
| 0.0671        | 30.0  | 600  | 0.0537          | 0.4445   | 0.8891        | 0.8891           | nan                 | 0.8891            | 0.0            | 0.8891       |
| 0.0699        | 31.0  | 620  | 0.0530          | 0.4397   | 0.8794        | 0.8794           | nan                 | 0.8794            | 0.0            | 0.8794       |
| 0.0648        | 32.0  | 640  | 0.0535          | 0.4423   | 0.8845        | 0.8845           | nan                 | 0.8845            | 0.0            | 0.8845       |
| 0.058         | 33.0  | 660  | 0.0535          | 0.4467   | 0.8934        | 0.8934           | nan                 | 0.8934            | 0.0            | 0.8934       |
| 0.0582        | 34.0  | 680  | 0.0536          | 0.4513   | 0.9025        | 0.9025           | nan                 | 0.9025            | 0.0            | 0.9025       |
| 0.0561        | 35.0  | 700  | 0.0525          | 0.4444   | 0.8888        | 0.8888           | nan                 | 0.8888            | 0.0            | 0.8888       |
| 0.0731        | 36.0  | 720  | 0.0520          | 0.4439   | 0.8878        | 0.8878           | nan                 | 0.8878            | 0.0            | 0.8878       |
| 0.0503        | 37.0  | 740  | 0.0528          | 0.4484   | 0.8968        | 0.8968           | nan                 | 0.8968            | 0.0            | 0.8968       |
| 0.0895        | 38.0  | 760  | 0.0505          | 0.4388   | 0.8777        | 0.8777           | nan                 | 0.8777            | 0.0            | 0.8777       |
| 0.064         | 39.0  | 780  | 0.0508          | 0.4418   | 0.8836        | 0.8836           | nan                 | 0.8836            | 0.0            | 0.8836       |
| 0.0481        | 40.0  | 800  | 0.0512          | 0.4474   | 0.8949        | 0.8949           | nan                 | 0.8949            | 0.0            | 0.8949       |
| 0.0497        | 41.0  | 820  | 0.0533          | 0.4503   | 0.9006        | 0.9006           | nan                 | 0.9006            | 0.0            | 0.9006       |
| 0.06          | 42.0  | 840  | 0.0511          | 0.4447   | 0.8893        | 0.8893           | nan                 | 0.8893            | 0.0            | 0.8893       |
| 0.0543        | 43.0  | 860  | 0.0504          | 0.4441   | 0.8882        | 0.8882           | nan                 | 0.8882            | 0.0            | 0.8882       |
| 0.0539        | 44.0  | 880  | 0.0515          | 0.4421   | 0.8843        | 0.8843           | nan                 | 0.8843            | 0.0            | 0.8843       |
| 0.0461        | 45.0  | 900  | 0.0506          | 0.4461   | 0.8921        | 0.8921           | nan                 | 0.8921            | 0.0            | 0.8921       |
| 0.0554        | 46.0  | 920  | 0.0501          | 0.4453   | 0.8907        | 0.8907           | nan                 | 0.8907            | 0.0            | 0.8907       |
| 0.0475        | 47.0  | 940  | 0.0503          | 0.4471   | 0.8942        | 0.8942           | nan                 | 0.8942            | 0.0            | 0.8942       |
| 0.0645        | 48.0  | 960  | 0.0506          | 0.4463   | 0.8926        | 0.8926           | nan                 | 0.8926            | 0.0            | 0.8926       |
| 0.045         | 49.0  | 980  | 0.0510          | 0.4471   | 0.8942        | 0.8942           | nan                 | 0.8942            | 0.0            | 0.8942       |
| 0.0576        | 50.0  | 1000 | 0.0500          | 0.4449   | 0.8899        | 0.8899           | nan                 | 0.8899            | 0.0            | 0.8899       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
