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---
license: other
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-lane-1k-steps
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-finetuned-lane-1k-steps
This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-cityscapes-512-1024](https://huggingface.co/nvidia/segformer-b0-finetuned-cityscapes-512-1024) on the Efferbach/lane_master dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0548
- Mean Iou: 0.0708
- Mean Accuracy: 0.1236
- Overall Accuracy: 0.1217
- Accuracy Background: nan
- Accuracy Left: 0.1893
- Accuracy Right: 0.0578
- Iou Background: 0.0
- Iou Left: 0.1581
- Iou Right: 0.0544
## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Left | Accuracy Right | Iou Background | Iou Left | Iou Right |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:--------------:|:--------------:|:--------:|:---------:|
| 0.1 | 1.0 | 308 | 0.0862 | 0.0008 | 0.0013 | 0.0012 | nan | 0.0025 | 0.0 | 0.0 | 0.0025 | 0.0 |
| 0.0596 | 2.0 | 616 | 0.0597 | 0.0712 | 0.1126 | 0.1132 | nan | 0.0940 | 0.1313 | 0.0 | 0.0907 | 0.1228 |
| 0.0506 | 3.0 | 924 | 0.0551 | 0.0682 | 0.1171 | 0.1152 | nan | 0.1805 | 0.0536 | 0.0 | 0.1539 | 0.0508 |
| 0.0494 | 3.25 | 1000 | 0.0548 | 0.0708 | 0.1236 | 0.1217 | nan | 0.1893 | 0.0578 | 0.0 | 0.1581 | 0.0544 |
### Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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