---
library_name: transformers
license: other
base_model: nvidia/segformer-b2-finetuned-cityscapes-1024-1024
tags:
- generated_from_trainer
model-index:
- name: SegFormer_b2_10
  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_10

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 an unknown dataset.
It achieves the following results on the evaluation set:
- epoch: 14.5161
- eval_accuracy_bicycle: 0.8914
- eval_accuracy_building: 0.9612
- eval_accuracy_bus: 0.9483
- eval_accuracy_car: 0.9763
- eval_accuracy_fence: 0.7181
- eval_accuracy_motorcycle: 0.7986
- eval_accuracy_person: 0.9057
- eval_accuracy_pole: 0.7198
- eval_accuracy_rider: 0.7552
- eval_accuracy_road: 0.9902
- eval_accuracy_sidewalk: 0.9345
- eval_accuracy_sky: 0.9831
- eval_accuracy_terrain: 0.7525
- eval_accuracy_traffic light: 0.8652
- eval_accuracy_traffic sign: 0.8838
- eval_accuracy_train: 0.8680
- eval_accuracy_truck: 0.8765
- eval_accuracy_vegetation: 0.9637
- eval_accuracy_wall: 0.7237
- eval_iou_bicycle: 0.7541
- eval_iou_building: 0.9244
- eval_iou_bus: 0.8603
- eval_iou_car: 0.9482
- eval_iou_fence: 0.6075
- eval_iou_motorcycle: 0.6289
- eval_iou_person: 0.7921
- eval_iou_pole: 0.5893
- eval_iou_rider: 0.5955
- eval_iou_road: 0.9835
- eval_iou_sidewalk: 0.8649
- eval_iou_sky: 0.9465
- eval_iou_terrain: 0.6534
- eval_iou_traffic light: 0.6718
- eval_iou_traffic sign: 0.7801
- eval_iou_train: 0.8124
- eval_iou_truck: 0.8174
- eval_iou_vegetation: 0.9245
- eval_iou_wall: 0.6499
- eval_loss: 0.8030
- eval_mean_accuracy: 0.8693
- eval_mean_iou: 0.7792
- eval_overall_accuracy: 0.9609
- eval_runtime: 202.8122
- eval_samples_per_second: 2.465
- eval_steps_per_second: 0.616
- step: 2700

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.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: 1000
- num_epochs: 20
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.48.1
- Pytorch 2.1.2+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0