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---
library_name: transformers
license: other
base_model: nvidia/segformer-b2-finetuned-cityscapes-1024-1024
tags:
- generated_from_trainer
model-index:
- name: SegFormer_b2_mappillary_
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_mappillary_
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:
- eval_loss: 0.9598
- eval_mean_iou: 0.6780
- eval_mean_accuracy: 0.7951
- eval_overall_accuracy: 0.9391
- eval_accuracy_construction--barrier--fence: 0.6674
- eval_accuracy_construction--barrier--guard-rail: 0.7787
- eval_accuracy_construction--barrier--other-barrier: 0.7093
- eval_accuracy_construction--barrier--wall: 0.6692
- eval_accuracy_construction--flat--road: 0.9505
- eval_accuracy_construction--flat--service-lane: 0.5410
- eval_accuracy_construction--flat--sidewalk: 0.9029
- eval_accuracy_construction--structure--building: 0.9494
- eval_accuracy_human--person: 0.8428
- eval_accuracy_human--rider--bicyclist: 0.7374
- eval_accuracy_marking--crosswalk-zebra: 0.8275
- eval_accuracy_marking--general: 0.6969
- eval_accuracy_nature--sky: 0.9902
- eval_accuracy_nature--terrain: 0.8238
- eval_accuracy_nature--vegetation: 0.9447
- eval_accuracy_object--support--pole: 0.5732
- eval_accuracy_object--support--traffic-sign-frame: 0.6710
- eval_accuracy_object--traffic-light: 0.7524
- eval_accuracy_object--traffic-sign--front: 0.8163
- eval_accuracy_object--vehicle--bicycle: 0.7771
- eval_accuracy_object--vehicle--bus: 0.8829
- eval_accuracy_object--vehicle--car: 0.9659
- eval_accuracy_object--vehicle--truck: 0.8158
- eval_iou_construction--barrier--fence: 0.5508
- eval_iou_construction--barrier--guard-rail: 0.6288
- eval_iou_construction--barrier--other-barrier: 0.5638
- eval_iou_construction--barrier--wall: 0.5354
- eval_iou_construction--flat--road: 0.9129
- eval_iou_construction--flat--service-lane: 0.4333
- eval_iou_construction--flat--sidewalk: 0.7696
- eval_iou_construction--structure--building: 0.8821
- eval_iou_human--person: 0.6700
- eval_iou_human--rider--bicyclist: 0.5363
- eval_iou_marking--crosswalk-zebra: 0.7082
- eval_iou_marking--general: 0.5822
- eval_iou_nature--sky: 0.9811
- eval_iou_nature--terrain: 0.6964
- eval_iou_nature--vegetation: 0.8935
- eval_iou_object--support--pole: 0.4515
- eval_iou_object--support--traffic-sign-frame: 0.5508
- eval_iou_object--traffic-light: 0.5782
- eval_iou_object--traffic-sign--front: 0.7134
- eval_iou_object--vehicle--bicycle: 0.5514
- eval_iou_object--vehicle--bus: 0.7858
- eval_iou_object--vehicle--car: 0.9004
- eval_iou_object--vehicle--truck: 0.7182
- eval_runtime: 1416.4555
- eval_samples_per_second: 1.412
- eval_steps_per_second: 0.706
- epoch: 14.0
- step: 31500
## 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: 9e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 30
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.48.1
- Pytorch 2.1.2+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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