---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-test
  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-test

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:
- eval_loss: 0.2053
- eval_mean_iou: 0.5448
- eval_mean_accuracy: 0.6296
- eval_overall_accuracy: 0.9130
- eval_accuracy_Structure (dimensional): nan
- eval_accuracy_Impervious (planiform): 0.9578
- eval_accuracy_Fences: 0.3758
- eval_accuracy_Water Storage/Tank: nan
- eval_accuracy_Pool < 100 sqft: 0.0
- eval_accuracy_Pool > 100 sqft: 0.8208
- eval_accuracy_Irrigated Planiform: 0.8708
- eval_accuracy_Irrigated Dimensional Low: 0.6817
- eval_accuracy_Irrigated Dimensional High: 0.9472
- eval_accuracy_Irrigated Bare: 0.4827
- eval_accuracy_Irrigable Planiform: 0.6668
- eval_accuracy_Irrigable Dimensional Low: 0.6013
- eval_accuracy_Irrigable Dimensional High: 0.7902
- eval_accuracy_Irrigable Bare: 0.5657
- eval_accuracy_Native Planiform: 0.9093
- eval_accuracy_Native Dimensional Low: 0.0
- eval_accuracy_Native Dimensional High: 0.0961
- eval_accuracy_Native Bare: 0.9332
- eval_accuracy_UDL: nan
- eval_accuracy_Open Water: 0.6613
- eval_accuracy_Artificial Turf: 0.9720
- eval_iou_Structure (dimensional): 0.0
- eval_iou_Impervious (planiform): 0.8964
- eval_iou_Fences: 0.3104
- eval_iou_Water Storage/Tank: nan
- eval_iou_Pool < 100 sqft: 0.0
- eval_iou_Pool > 100 sqft: 0.8199
- eval_iou_Irrigated Planiform: 0.7563
- eval_iou_Irrigated Dimensional Low: 0.5480
- eval_iou_Irrigated Dimensional High: 0.8920
- eval_iou_Irrigated Bare: 0.4053
- eval_iou_Irrigable Planiform: 0.6007
- eval_iou_Irrigable Dimensional Low: 0.5083
- eval_iou_Irrigable Dimensional High: 0.7595
- eval_iou_Irrigable Bare: 0.5106
- eval_iou_Native Planiform: 0.8678
- eval_iou_Native Dimensional Low: 0.0
- eval_iou_Native Dimensional High: 0.0961
- eval_iou_Native Bare: 0.8293
- eval_iou_UDL: nan
- eval_iou_Open Water: 0.5929
- eval_iou_Artificial Turf: 0.9584
- eval_runtime: 6.2852
- eval_samples_per_second: 15.91
- eval_steps_per_second: 1.114
- epoch: 10.8
- step: 270

## 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
- num_epochs: 20

### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1