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-multi
  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. -->

# segformer-b0-finetuned-arabidopsis-roots-multi

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the jacquelinegrimm/arabidopsis-roots-multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0675
- Mean Iou: 0.5272
- Mean Accuracy: 0.7048
- Overall Accuracy: 0.6874
- Accuracy Background: nan
- Accuracy Main root: 0.6670
- Accuracy Lateral root: 0.6181
- Accuracy Shoot: 0.7576
- Accuracy Botrytis: 0.7765
- Iou Background: 0.0
- Iou Main root: 0.6256
- Iou Lateral root: 0.5603
- Iou Shoot: 0.6767
- Iou Botrytis: 0.7734

## 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: 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 Main root | Accuracy Lateral root | Accuracy Shoot | Accuracy Botrytis | Iou Background | Iou Main root | Iou Lateral root | Iou Shoot | Iou Botrytis |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------------:|:---------------------:|:--------------:|:-----------------:|:--------------:|:-------------:|:----------------:|:---------:|:------------:|
| 1.1832        | 1.0   | 20   | 1.2347          | 0.3383   | 0.4952        | 0.4799           | nan                 | 0.1614             | 0.7764                | 0.1747         | 0.8683            | 0.0            | 0.1377        | 0.5355           | 0.1700    | 0.8484       |
| 0.901         | 2.0   | 40   | 0.7864          | 0.3051   | 0.4105        | 0.3438           | nan                 | 0.0062             | 0.3933                | 0.3166         | 0.9258            | 0.0            | 0.0061        | 0.3238           | 0.2853    | 0.9101       |
| 0.7161        | 3.0   | 60   | 0.6386          | 0.3059   | 0.4133        | 0.3430           | nan                 | 0.0271             | 0.3389                | 0.3349         | 0.9523            | 0.0            | 0.0270        | 0.2919           | 0.2847    | 0.9261       |
| 0.6358        | 4.0   | 80   | 0.6021          | 0.3155   | 0.4225        | 0.3502           | nan                 | 0.0390             | 0.3338                | 0.3713         | 0.9458            | 0.0            | 0.0387        | 0.2878           | 0.3241    | 0.9271       |
| 0.5111        | 5.0   | 100  | 0.4770          | 0.2871   | 0.3779        | 0.3175           | nan                 | 0.0567             | 0.2880                | 0.2798         | 0.8871            | 0.0            | 0.0562        | 0.2493           | 0.2571    | 0.8728       |
| 0.4842        | 6.0   | 120  | 0.4069          | 0.2422   | 0.3232        | 0.2792           | nan                 | 0.1142             | 0.2559                | 0.3734         | 0.5495            | 0.0            | 0.1112        | 0.2290           | 0.3240    | 0.5470       |
| 0.3631        | 7.0   | 140  | 0.3527          | 0.2692   | 0.3581        | 0.3537           | nan                 | 0.3382             | 0.3411                | 0.3353         | 0.4179            | 0.0            | 0.3168        | 0.3021           | 0.3093    | 0.4179       |
| 0.3316        | 8.0   | 160  | 0.2986          | 0.4239   | 0.5731        | 0.5496           | nan                 | 0.4712             | 0.5003                | 0.5306         | 0.7904            | 0.0            | 0.4372        | 0.4333           | 0.4719    | 0.7773       |
| 0.3074        | 9.0   | 180  | 0.2755          | 0.3755   | 0.5061        | 0.4932           | nan                 | 0.4440             | 0.4876                | 0.5202         | 0.5727            | 0.0            | 0.4129        | 0.4281           | 0.4679    | 0.5687       |
| 0.3216        | 10.0  | 200  | 0.2317          | 0.4262   | 0.5762        | 0.5625           | nan                 | 0.5676             | 0.4656                | 0.5853         | 0.6864            | 0.0            | 0.5153        | 0.4206           | 0.5142    | 0.6811       |
| 0.2426        | 11.0  | 220  | 0.2022          | 0.4659   | 0.6319        | 0.5981           | nan                 | 0.5068             | 0.5241                | 0.6682         | 0.8285            | 0.0            | 0.4766        | 0.4531           | 0.5856    | 0.8139       |
| 0.2063        | 12.0  | 240  | 0.1752          | 0.4274   | 0.5759        | 0.5627           | nan                 | 0.5756             | 0.4687                | 0.6275         | 0.6319            | 0.0            | 0.5259        | 0.4287           | 0.5547    | 0.6277       |
| 0.1811        | 13.0  | 260  | 0.1542          | 0.4608   | 0.6216        | 0.6022           | nan                 | 0.5509             | 0.5639                | 0.6604         | 0.7113            | 0.0            | 0.5166        | 0.4893           | 0.5899    | 0.7083       |
| 0.1738        | 14.0  | 280  | 0.1396          | 0.4393   | 0.5926        | 0.5781           | nan                 | 0.6143             | 0.4492                | 0.6755         | 0.6314            | 0.0            | 0.5544        | 0.4218           | 0.5914    | 0.6291       |
| 0.2094        | 15.0  | 300  | 0.1193          | 0.4422   | 0.5906        | 0.5683           | nan                 | 0.5321             | 0.4922                | 0.6475         | 0.6907            | 0.0            | 0.4953        | 0.4505           | 0.5760    | 0.6891       |
| 0.129         | 16.0  | 320  | 0.1200          | 0.4816   | 0.6520        | 0.6415           | nan                 | 0.6646             | 0.5644                | 0.7487         | 0.6303            | 0.0            | 0.6072        | 0.5158           | 0.6552    | 0.6298       |
| 0.1326        | 17.0  | 340  | 0.1109          | 0.4622   | 0.6200        | 0.6005           | nan                 | 0.5568             | 0.5628                | 0.7030         | 0.6576            | 0.0            | 0.5257        | 0.5029           | 0.6270    | 0.6555       |
| 0.0935        | 18.0  | 360  | 0.1043          | 0.5018   | 0.6743        | 0.6542           | nan                 | 0.5992             | 0.6207                | 0.7253         | 0.7519            | 0.0            | 0.5665        | 0.5412           | 0.6523    | 0.7490       |
| 0.0862        | 19.0  | 380  | 0.1044          | 0.4790   | 0.6435        | 0.6272           | nan                 | 0.5848             | 0.6080                | 0.7212         | 0.6600            | 0.0            | 0.5538        | 0.5333           | 0.6492    | 0.6586       |
| 0.122         | 20.0  | 400  | 0.0940          | 0.5244   | 0.7048        | 0.6846           | nan                 | 0.6428             | 0.6277                | 0.7498         | 0.7987            | 0.0            | 0.6000        | 0.5576           | 0.6708    | 0.7939       |
| 0.0886        | 21.0  | 420  | 0.0945          | 0.5390   | 0.7263        | 0.7016           | nan                 | 0.6253             | 0.6676                | 0.7686         | 0.8439            | 0.0            | 0.5912        | 0.5754           | 0.6902    | 0.8382       |
| 0.0742        | 22.0  | 440  | 0.0933          | 0.4919   | 0.6620        | 0.6407           | nan                 | 0.6001             | 0.5945                | 0.7732         | 0.6803            | 0.0            | 0.5677        | 0.5301           | 0.6829    | 0.6788       |
| 0.0727        | 23.0  | 460  | 0.0886          | 0.4711   | 0.6279        | 0.6139           | nan                 | 0.6072             | 0.5489                | 0.6892         | 0.6664            | 0.0            | 0.5695        | 0.5005           | 0.6199    | 0.6656       |
| 0.0708        | 24.0  | 480  | 0.0854          | 0.4966   | 0.6684        | 0.6574           | nan                 | 0.6409             | 0.6351                | 0.7520         | 0.6454            | 0.0            | 0.6040        | 0.5612           | 0.6737    | 0.6443       |
| 0.0614        | 25.0  | 500  | 0.0857          | 0.4882   | 0.6563        | 0.6405           | nan                 | 0.6005             | 0.6244                | 0.7464         | 0.6541            | 0.0            | 0.5691        | 0.5524           | 0.6658    | 0.6535       |
| 0.151         | 26.0  | 520  | 0.0834          | 0.5106   | 0.6852        | 0.6667           | nan                 | 0.6271             | 0.6253                | 0.7566         | 0.7320            | 0.0            | 0.5918        | 0.5566           | 0.6762    | 0.7284       |
| 0.0658        | 27.0  | 540  | 0.0823          | 0.5055   | 0.6768        | 0.6636           | nan                 | 0.6741             | 0.5807                | 0.7498         | 0.7027            | 0.0            | 0.6250        | 0.5332           | 0.6673    | 0.7017       |
| 0.0643        | 28.0  | 560  | 0.0797          | 0.4959   | 0.6636        | 0.6481           | nan                 | 0.6315             | 0.5930                | 0.7399         | 0.6901            | 0.0            | 0.5921        | 0.5366           | 0.6619    | 0.6889       |
| 0.059         | 29.0  | 580  | 0.0782          | 0.5115   | 0.6845        | 0.6682           | nan                 | 0.6490             | 0.6092                | 0.7531         | 0.7265            | 0.0            | 0.6100        | 0.5472           | 0.6769    | 0.7234       |
| 0.1726        | 30.0  | 600  | 0.0786          | 0.5235   | 0.7039        | 0.6846           | nan                 | 0.6190             | 0.6734                | 0.7552         | 0.7679            | 0.0            | 0.5905        | 0.5825           | 0.6807    | 0.7639       |
| 0.0546        | 31.0  | 620  | 0.0745          | 0.5116   | 0.6843        | 0.6654           | nan                 | 0.6337             | 0.6072                | 0.7468         | 0.7494            | 0.0            | 0.5956        | 0.5467           | 0.6701    | 0.7457       |
| 0.1096        | 32.0  | 640  | 0.0746          | 0.5093   | 0.6814        | 0.6590           | nan                 | 0.5992             | 0.6202                | 0.7427         | 0.7634            | 0.0            | 0.5666        | 0.5550           | 0.6656    | 0.7595       |
| 0.0552        | 33.0  | 660  | 0.0750          | 0.5358   | 0.7160        | 0.6944           | nan                 | 0.6520             | 0.6285                | 0.7572         | 0.8262            | 0.0            | 0.6147        | 0.5639           | 0.6783    | 0.8223       |
| 0.0557        | 34.0  | 680  | 0.0731          | 0.5123   | 0.6878        | 0.6709           | nan                 | 0.6271             | 0.6496                | 0.7669         | 0.7076            | 0.0            | 0.5955        | 0.5745           | 0.6853    | 0.7060       |
| 0.0516        | 35.0  | 700  | 0.0733          | 0.5307   | 0.7108        | 0.6929           | nan                 | 0.6696             | 0.6260                | 0.7665         | 0.7813            | 0.0            | 0.6276        | 0.5654           | 0.6825    | 0.7781       |
| 0.105         | 36.0  | 720  | 0.0717          | 0.5242   | 0.7020        | 0.6823           | nan                 | 0.6365             | 0.6397                | 0.7633         | 0.7684            | 0.0            | 0.6029        | 0.5682           | 0.6841    | 0.7660       |
| 0.1305        | 37.0  | 740  | 0.0713          | 0.5232   | 0.7002        | 0.6845           | nan                 | 0.6739             | 0.6137                | 0.7624         | 0.7510            | 0.0            | 0.6289        | 0.5585           | 0.6794    | 0.7490       |
| 0.0479        | 38.0  | 760  | 0.0707          | 0.5196   | 0.6944        | 0.6763           | nan                 | 0.6517             | 0.6116                | 0.7556         | 0.7588            | 0.0            | 0.6125        | 0.5532           | 0.6754    | 0.7567       |
| 0.0552        | 39.0  | 780  | 0.0705          | 0.5198   | 0.6977        | 0.6837           | nan                 | 0.6561             | 0.6543                | 0.7664         | 0.7139            | 0.0            | 0.6209        | 0.5803           | 0.6852    | 0.7124       |
| 0.0997        | 40.0  | 800  | 0.0699          | 0.5219   | 0.6968        | 0.6789           | nan                 | 0.6586             | 0.6057                | 0.7478         | 0.7752            | 0.0            | 0.6180        | 0.5504           | 0.6680    | 0.7729       |
| 0.0774        | 41.0  | 820  | 0.0708          | 0.5171   | 0.6900        | 0.6727           | nan                 | 0.6592             | 0.5927                | 0.7395         | 0.7686            | 0.0            | 0.6163        | 0.5402           | 0.6635    | 0.7656       |
| 0.0899        | 42.0  | 840  | 0.0692          | 0.5324   | 0.7125        | 0.6927           | nan                 | 0.6683             | 0.6169                | 0.7765         | 0.7883            | 0.0            | 0.6265        | 0.5601           | 0.6902    | 0.7851       |
| 0.0492        | 43.0  | 860  | 0.0682          | 0.5390   | 0.7216        | 0.7043           | nan                 | 0.6740             | 0.6497                | 0.7676         | 0.7950            | 0.0            | 0.6348        | 0.5793           | 0.6891    | 0.7918       |
| 0.0712        | 44.0  | 880  | 0.0690          | 0.5121   | 0.6844        | 0.6692           | nan                 | 0.6570             | 0.6071                | 0.7533         | 0.7204            | 0.0            | 0.6153        | 0.5524           | 0.6743    | 0.7186       |
| 0.1034        | 45.0  | 900  | 0.0685          | 0.5503   | 0.7379        | 0.7191           | nan                 | 0.6822             | 0.6645                | 0.7832         | 0.8215            | 0.0            | 0.6439        | 0.5905           | 0.6994    | 0.8175       |
| 0.0478        | 46.0  | 920  | 0.0681          | 0.5365   | 0.7179        | 0.6998           | nan                 | 0.6726             | 0.6369                | 0.7719         | 0.7902            | 0.0            | 0.6326        | 0.5728           | 0.6901    | 0.7869       |
| 0.0452        | 47.0  | 940  | 0.0682          | 0.5341   | 0.7157        | 0.6993           | nan                 | 0.6723             | 0.6495                | 0.7765         | 0.7647            | 0.0            | 0.6346        | 0.5803           | 0.6935    | 0.7621       |
| 0.0542        | 48.0  | 960  | 0.0675          | 0.5382   | 0.7206        | 0.7021           | nan                 | 0.6695             | 0.6444                | 0.7726         | 0.7961            | 0.0            | 0.6313        | 0.5772           | 0.6899    | 0.7928       |
| 0.0738        | 49.0  | 980  | 0.0680          | 0.5360   | 0.7168        | 0.6977           | nan                 | 0.6714             | 0.6254                | 0.7666         | 0.8040            | 0.0            | 0.6302        | 0.5658           | 0.6838    | 0.8004       |
| 0.1169        | 50.0  | 1000 | 0.0675          | 0.5272   | 0.7048        | 0.6874           | nan                 | 0.6670             | 0.6181                | 0.7576         | 0.7765            | 0.0            | 0.6256        | 0.5603           | 0.6767    | 0.7734       |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
