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# 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

```
"id2label": {
    "0": "background",
    "1": "hat",
    "2": "hair",
    "3": "glove",
    "4": "glasses",
    "5": "upper_only_torso_region",
    "6": "dresses_only_torso_region",
    "7": "coat_only_torso_region",
    "8": "socks",
    "9": "left_pants",
    "10": "right_patns",
    "11": "skin_around_neck_region",
    "12": "scarf",
    "13": "skirts",
    "14": "face",
    "15": "left_arm",
    "16": "right_arm",
    "17": "left_leg",
    "18": "right_leg",
    "19": "left_shoe",
    "20": "right_shoe",
    "21": "left_sleeve_for_upper",
    "22": "right_sleeve_for_upper",
    "23": "bag"
}
```

## 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
{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["human_parsing_29_mix"], "base_model": "mattmdjaga/segformer_b2_clothes", "pipeline_tag": "image-segmentation", "model-index": [{"name": "segformer-b2-human-parse-24", "results": []}]}
transformers tensorboard safetensors segformer generated_from_trainer image-segmentation dataset:human_parsing_29_mix base_model:mattmdjaga/segformer_b2_clothes license:mit endpoints_compatible has_space region:us