---
library_name: transformers
license: other
base_model: nvidia/segformer-b2-finetuned-cityscapes-1024-1024
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: SegFormer_b2
  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_b2

This model is a fine-tuned version of [nvidia/segformer-b2-finetuned-cityscapes-1024-1024](https://huggingface.co/nvidia/segformer-b2-finetuned-cityscapes-1024-1024) on the Cityscapes dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2516
- eval_mean_iou: 0.3875
- eval_mean_accuracy: 0.5066
- eval_overall_accuracy: 0.9043
- eval_accuracy_unlabeled: nan
- eval_accuracy_ego vehicle: nan
- eval_accuracy_rectification border: nan
- eval_accuracy_out of roi: nan
- eval_accuracy_static: nan
- eval_accuracy_dynamic: nan
- eval_accuracy_ground: nan
- eval_accuracy_road: 0.9832
- eval_accuracy_sidewalk: 0.8421
- eval_accuracy_parking: nan
- eval_accuracy_rail track: nan
- eval_accuracy_building: 0.9158
- eval_accuracy_wall: 0.0
- eval_accuracy_fence: 0.0
- eval_accuracy_guard rail: nan
- eval_accuracy_bridge: nan
- eval_accuracy_tunnel: nan
- eval_accuracy_pole: 0.5362
- eval_accuracy_polegroup: nan
- eval_accuracy_traffic light: 0.5814
- eval_accuracy_traffic sign: 0.7376
- eval_accuracy_vegetation: 0.9188
- eval_accuracy_terrain: 0.6737
- eval_accuracy_sky: 0.9746
- eval_accuracy_person: 0.7788
- eval_accuracy_rider: 0.0
- eval_accuracy_car: 0.9354
- eval_accuracy_truck: 0.0
- eval_accuracy_bus: 0.0
- eval_accuracy_caravan: nan
- eval_accuracy_trailer: nan
- eval_accuracy_train: 0.0
- eval_accuracy_motorcycle: 0.0
- eval_accuracy_bicycle: 0.7472
- eval_accuracy_license plate: nan
- eval_iou_unlabeled: nan
- eval_iou_ego vehicle: nan
- eval_iou_rectification border: nan
- eval_iou_out of roi: nan
- eval_iou_static: 0.0
- eval_iou_dynamic: nan
- eval_iou_ground: nan
- eval_iou_road: 0.9649
- eval_iou_sidewalk: 0.7403
- eval_iou_parking: nan
- eval_iou_rail track: nan
- eval_iou_building: 0.8430
- eval_iou_wall: 0.0
- eval_iou_fence: 0.0
- eval_iou_guard rail: nan
- eval_iou_bridge: nan
- eval_iou_tunnel: nan
- eval_iou_pole: 0.3619
- eval_iou_polegroup: nan
- eval_iou_traffic light: 0.4506
- eval_iou_traffic sign: 0.5317
- eval_iou_vegetation: 0.8647
- eval_iou_terrain: 0.4610
- eval_iou_sky: 0.8806
- eval_iou_person: 0.5967
- eval_iou_rider: 0.0
- eval_iou_car: 0.8756
- eval_iou_truck: 0.0
- eval_iou_bus: 0.0
- eval_iou_caravan: nan
- eval_iou_trailer: nan
- eval_iou_train: 0.0
- eval_iou_motorcycle: 0.0
- eval_iou_bicycle: 0.5665
- eval_iou_license plate: 0.0
- eval_runtime: 185.4692
- eval_samples_per_second: 2.696
- eval_steps_per_second: 0.674
- epoch: 20.4301
- step: 3800

## 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: 0.0006
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0