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---
license: mit
base_model: mattmdjaga/segformer_b2_clothes
tags:
- generated_from_trainer
datasets:
- human_parsing_29_mix
model-index:
- name: segformer-b2-human-parse-24
results: []
pipeline_tag: image-segmentation
---
<!-- 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-human-parse-24
This model is a fine-tuned version of [mattmdjaga/segformer_b2_clothes](https://huggingface.co/mattmdjaga/segformer_b2_clothes) on the human_parsing_29_mix dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0818
- Mean Iou: 0.6023
- Mean Accuracy: 0.6321
- Overall Accuracy: 0.9780
- Accuracy Background: 0.9969
- Accuracy Hat: nan
- Accuracy Hair: 0.9646
- Accuracy Glove: 0.0
- Accuracy Glasses: 0.0
- Accuracy Upper Only Torso Region: 0.9747
- Accuracy Dresses Only Torso Region: 0.4939
- Accuracy Coat Only Torso Region: 0.0039
- Accuracy Socks: 0.0
- Accuracy Left Pants: 0.9604
- Accuracy Right Patns: 0.9646
- Accuracy Skin Around Neck Region: 0.9585
- Accuracy Scarf: nan
- Accuracy Skirts: 0.8904
- Accuracy Face: 0.9796
- Accuracy Left Arm: 0.9703
- Accuracy Right Arm: 0.9700
- Accuracy Left Leg: 0.9267
- Accuracy Right Leg: 0.9297
- Accuracy Left Shoe: 0.0
- Accuracy Right Shoe: 0.0
- Accuracy Left Sleeve For Upper: 0.9462
- Accuracy Right Sleeve For Upper: 0.9517
- Accuracy Bag: 0.0234
- Iou Background: 0.9941
- Iou Hat: nan
- Iou Hair: 0.9268
- Iou Glove: 0.0
- Iou Glasses: 0.0
- Iou Upper Only Torso Region: 0.9351
- Iou Dresses Only Torso Region: 0.4059
- Iou Coat Only Torso Region: 0.0035
- Iou Socks: 0.0
- Iou Left Pants: 0.9232
- Iou Right Patns: 0.9217
- Iou Skin Around Neck Region: 0.9227
- Iou Scarf: nan
- Iou Skirts: 0.7887
- Iou Face: 0.9582
- Iou Left Arm: 0.9436
- Iou Right Arm: 0.9426
- Iou Left Leg: 0.8836
- Iou Right Leg: 0.8767
- Iou Left Shoe: 0.0
- Iou Right Shoe: 0.0
- Iou Left Sleeve For Upper: 0.9005
- Iou Right Sleeve For Upper: 0.9012
- Iou Bag: 0.0232
## 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: 16
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Hat | Accuracy Hair | Accuracy Glove | Accuracy Glasses | Accuracy Upper Only Torso Region | Accuracy Dresses Only Torso Region | Accuracy Coat Only Torso Region | Accuracy Socks | Accuracy Left Pants | Accuracy Right Patns | Accuracy Skin Around Neck Region | Accuracy Scarf | Accuracy Skirts | Accuracy Face | Accuracy Left Arm | Accuracy Right Arm | Accuracy Left Leg | Accuracy Right Leg | Accuracy Left Shoe | Accuracy Right Shoe | Accuracy Left Sleeve For Upper | Accuracy Right Sleeve For Upper | Accuracy Bag | Iou Background | Iou Hat | Iou Hair | Iou Glove | Iou Glasses | Iou Upper Only Torso Region | Iou Dresses Only Torso Region | Iou Coat Only Torso Region | Iou Socks | Iou Left Pants | Iou Right Patns | Iou Skin Around Neck Region | Iou Scarf | Iou Skirts | Iou Face | Iou Left Arm | Iou Right Arm | Iou Left Leg | Iou Right Leg | Iou Left Shoe | Iou Right Shoe | Iou Left Sleeve For Upper | Iou Right Sleeve For Upper | Iou Bag |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------:|:-------------:|:--------------:|:----------------:|:--------------------------------:|:----------------------------------:|:-------------------------------:|:--------------:|:-------------------:|:--------------------:|:--------------------------------:|:--------------:|:---------------:|:-------------:|:-----------------:|:------------------:|:-----------------:|:------------------:|:------------------:|:-------------------:|:------------------------------:|:-------------------------------:|:------------:|:--------------:|:-------:|:--------:|:---------:|:-----------:|:---------------------------:|:-----------------------------:|:--------------------------:|:---------:|:--------------:|:---------------:|:---------------------------:|:---------:|:----------:|:--------:|:------------:|:-------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------------------------:|:--------------------------:|:-------:|
| 0.0652 | 1.62 | 1000 | 0.0802 | 0.5857 | 0.6166 | 0.9737 | 0.9963 | nan | 0.9490 | 0.0 | 0.0 | 0.9801 | 0.4034 | 0.0 | 0.0 | 0.9487 | 0.9574 | 0.9272 | nan | 0.8783 | 0.9782 | 0.9628 | 0.9534 | 0.8874 | 0.9012 | 0.0 | 0.0 | 0.9227 | 0.9197 | 0.0 | 0.9926 | nan | 0.9117 | 0.0 | 0.0 | 0.9217 | 0.3541 | 0.0 | 0.0 | 0.9084 | 0.9073 | 0.8963 | nan | 0.7766 | 0.9455 | 0.9210 | 0.9191 | 0.8405 | 0.8496 | 0.0 | 0.0 | 0.8673 | 0.8728 | 0.0 |
| 0.061 | 3.23 | 2000 | 0.0843 | 0.5977 | 0.6335 | 0.9747 | 0.9967 | nan | 0.9580 | 0.0 | 0.0 | 0.9657 | 0.5733 | 0.1504 | 0.0 | 0.9591 | 0.9600 | 0.9497 | nan | 0.8169 | 0.9789 | 0.9667 | 0.9645 | 0.8906 | 0.9165 | 0.0 | 0.0 | 0.9444 | 0.9445 | 0.0003 | 0.9935 | nan | 0.9199 | 0.0 | 0.0 | 0.9273 | 0.4058 | 0.1206 | 0.0 | 0.9131 | 0.9082 | 0.9128 | nan | 0.7330 | 0.9527 | 0.9355 | 0.9343 | 0.8534 | 0.8651 | 0.0 | 0.0 | 0.8860 | 0.8879 | 0.0003 |
| 0.0653 | 4.85 | 3000 | 0.0823 | 0.6000 | 0.6295 | 0.9775 | 0.9967 | nan | 0.9621 | 0.0 | 0.0 | 0.9780 | 0.4991 | 0.0044 | 0.0 | 0.9587 | 0.9649 | 0.9562 | nan | 0.8842 | 0.9769 | 0.9692 | 0.9651 | 0.9198 | 0.9273 | 0.0 | 0.0 | 0.9422 | 0.9415 | 0.0037 | 0.9939 | nan | 0.9247 | 0.0 | 0.0 | 0.9341 | 0.4136 | 0.0042 | 0.0 | 0.9202 | 0.9193 | 0.9193 | nan | 0.7899 | 0.9563 | 0.9403 | 0.9388 | 0.8745 | 0.8741 | 0.0 | 0.0 | 0.8963 | 0.8970 | 0.0037 |
| 0.0402 | 6.46 | 4000 | 0.0818 | 0.6023 | 0.6321 | 0.9780 | 0.9969 | nan | 0.9646 | 0.0 | 0.0 | 0.9747 | 0.4939 | 0.0039 | 0.0 | 0.9604 | 0.9646 | 0.9585 | nan | 0.8904 | 0.9796 | 0.9703 | 0.9700 | 0.9267 | 0.9297 | 0.0 | 0.0 | 0.9462 | 0.9517 | 0.0234 | 0.9941 | nan | 0.9268 | 0.0 | 0.0 | 0.9351 | 0.4059 | 0.0035 | 0.0 | 0.9232 | 0.9217 | 0.9227 | nan | 0.7887 | 0.9582 | 0.9436 | 0.9426 | 0.8836 | 0.8767 | 0.0 | 0.0 | 0.9005 | 0.9012 | 0.0232 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0 |