|
--- |
|
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 |
|
|