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---
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
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