---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: segformer-b5-finetuned-ce-head-batch2
  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-b5-finetuned-ce-head-batch2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0575
- Mean Iou: 0.7701
- Mean Accuracy: 0.8473
- Overall Accuracy: 0.9774
- Accuracy Bg: 0.9891
- Accuracy Head: 0.7054
- Iou Bg: 0.9768
- Iou Head: 0.5634

## 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: 2
- eval_batch_size: 2
- seed: 42
- 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
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Bg | Accuracy Head | Iou Bg | Iou Head |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------:|:-------------:|:------:|:--------:|
| 0.0192        | 2.9412  | 100  | 0.0164          | 0.8513   | 0.9095        | 0.9934           | 0.9968      | 0.8221        | 0.9933 | 0.7094   |
| 0.0071        | 5.8824  | 200  | 0.0197          | 0.8495   | 0.8819        | 0.9933           | 0.9982      | 0.7656        | 0.9932 | 0.7058   |
| 0.0345        | 8.8235  | 300  | 0.0154          | 0.8745   | 0.9312        | 0.9940           | 0.9968      | 0.8657        | 0.9939 | 0.7551   |
| 0.0056        | 11.7647 | 400  | 0.0158          | 0.8668   | 0.9375        | 0.9937           | 0.9961      | 0.8789        | 0.9936 | 0.7401   |
| 0.0217        | 14.7059 | 500  | 0.0149          | 0.8736   | 0.9306        | 0.9936           | 0.9966      | 0.8646        | 0.9934 | 0.7538   |
| 0.0924        | 17.6471 | 600  | 0.0133          | 0.8738   | 0.9438        | 0.9943           | 0.9963      | 0.8913        | 0.9942 | 0.7534   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3