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# segformer-b0-finetuned-human-parsing

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9476
- Mean Iou: 0.0726
- Mean Accuracy: 0.1221
- Overall Accuracy: 0.3575
- Accuracy Background: nan
- Accuracy Hat: 0.0048
- Accuracy Hair: 0.4813
- Accuracy Sunglasses: 0.0
- Accuracy Upper-clothes: 0.9405
- Accuracy Skirt: 0.0000
- Accuracy Pants: 0.0631
- Accuracy Dress: 0.1031
- Accuracy Belt: 0.0
- Accuracy Left-shoe: 0.0011
- Accuracy Right-shoe: 0.0010
- Accuracy Face: 0.4406
- Accuracy Left-leg: 0.0291
- Accuracy Right-leg: 0.0
- Accuracy Left-arm: 0.0
- Accuracy Right-arm: 0.0001
- Accuracy Bag: 0.0114
- Accuracy Scarf: 0.0
- Iou Background: 0.0
- Iou Hat: 0.0043
- Iou Hair: 0.4221
- Iou Sunglasses: 0.0
- Iou Upper-clothes: 0.3239
- Iou Skirt: 0.0000
- Iou Pants: 0.0559
- Iou Dress: 0.0728
- Iou Belt: 0.0
- Iou Left-shoe: 0.0011
- Iou Right-shoe: 0.0009
- Iou Face: 0.3872
- Iou Left-leg: 0.0271
- Iou Right-leg: 0.0
- Iou Left-arm: 0.0
- Iou Right-arm: 0.0001
- Iou Bag: 0.0106
- Iou Scarf: 0.0

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Hat | Accuracy Hair | Accuracy Sunglasses | Accuracy Upper-clothes | Accuracy Skirt | Accuracy Pants | Accuracy Dress | Accuracy Belt | Accuracy Left-shoe | Accuracy Right-shoe | Accuracy Face | Accuracy Left-leg | Accuracy Right-leg | Accuracy Left-arm | Accuracy Right-arm | Accuracy Bag | Accuracy Scarf | Iou Background | Iou Hat | Iou Hair | Iou Sunglasses | Iou Upper-clothes | Iou Skirt | Iou Pants | Iou Dress | Iou Belt | Iou Left-shoe | Iou Right-shoe | Iou Face | Iou Left-leg | Iou Right-leg | Iou Left-arm | Iou Right-arm | Iou Bag | Iou Scarf |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------:|:-------------:|:-------------------:|:----------------------:|:--------------:|:--------------:|:--------------:|:-------------:|:------------------:|:-------------------:|:-------------:|:-----------------:|:------------------:|:-----------------:|:------------------:|:------------:|:--------------:|:--------------:|:-------:|:--------:|:--------------:|:-----------------:|:---------:|:---------:|:---------:|:--------:|:-------------:|:--------------:|:--------:|:------------:|:-------------:|:------------:|:-------------:|:-------:|:---------:|
| 2.5768        | 0.4   | 20   | 2.7812          | 0.0726   | 0.1332        | 0.2876           | nan                 | 0.0178       | 0.3204        | 0.0004              | 0.5548                 | 0.0004         | 0.2555         | 0.2373         | 0.0           | 0.0103             | 0.0003              | 0.5637        | 0.0287            | 0.0302             | 0.0001            | 0.0008             | 0.2435       | 0.0            | 0.0            | 0.0166  | 0.2759   | 0.0001         | 0.2781            | 0.0004    | 0.1710    | 0.1295    | 0.0      | 0.0098        | 0.0003         | 0.3251   | 0.0260       | 0.0248        | 0.0001       | 0.0007        | 0.0491  | 0.0       |
| 2.2093        | 0.8   | 40   | 2.5166          | 0.0563   | 0.1052        | 0.3288           | nan                 | 0.0          | 0.1994        | 0.0                 | 0.9447                 | 0.0015         | 0.0435         | 0.1164         | 0.0           | 0.0008             | 0.0000              | 0.4655        | 0.0007            | 0.0003             | 0.0               | 0.0                | 0.0153       | 0.0            | 0.0            | 0.0     | 0.1946   | 0.0            | 0.3037            | 0.0015    | 0.0417    | 0.0842    | 0.0      | 0.0008        | 0.0000         | 0.3726   | 0.0007       | 0.0003        | 0.0          | 0.0           | 0.0124  | 0.0       |
| 1.8804        | 1.2   | 60   | 2.0209          | 0.0632   | 0.1110        | 0.3374           | nan                 | 0.0087       | 0.3724        | 0.0                 | 0.9475                 | 0.0014         | 0.0162         | 0.0528         | 0.0           | 0.0001             | 0.0008              | 0.4257        | 0.0561            | 0.0001             | 0.0               | 0.0                | 0.0055       | 0.0            | 0.0            | 0.0077  | 0.3472   | 0.0            | 0.3086            | 0.0014    | 0.0156    | 0.0403    | 0.0      | 0.0001        | 0.0008         | 0.3597   | 0.0515       | 0.0001        | 0.0          | 0.0           | 0.0052  | 0.0       |
| 1.8776        | 1.6   | 80   | 2.0016          | 0.0665   | 0.1154        | 0.3454           | nan                 | 0.0056       | 0.4172        | 0.0                 | 0.9412                 | 0.0000         | 0.0490         | 0.0697         | 0.0           | 0.0002             | 0.0006              | 0.4349        | 0.0329            | 0.0000             | 0.0               | 0.0000             | 0.0100       | 0.0            | 0.0            | 0.0048  | 0.3791   | 0.0            | 0.3138            | 0.0000    | 0.0438    | 0.0542    | 0.0      | 0.0002        | 0.0006         | 0.3608   | 0.0304       | 0.0000        | 0.0          | 0.0000        | 0.0093  | 0.0       |
| 1.8471        | 2.0   | 100  | 1.9476          | 0.0726   | 0.1221        | 0.3575           | nan                 | 0.0048       | 0.4813        | 0.0                 | 0.9405                 | 0.0000         | 0.0631         | 0.1031         | 0.0           | 0.0011             | 0.0010              | 0.4406        | 0.0291            | 0.0                | 0.0               | 0.0001             | 0.0114       | 0.0            | 0.0            | 0.0043  | 0.4221   | 0.0            | 0.3239            | 0.0000    | 0.0559    | 0.0728    | 0.0      | 0.0011        | 0.0009         | 0.3872   | 0.0271       | 0.0           | 0.0          | 0.0001        | 0.0106  | 0.0       |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "other", "tags": ["vision", "image-segmentation", "generated_from_trainer"], "model-index": [{"name": "segformer-b0-finetuned-human-parsing", "results": []}]}
transformers pytorch tensorboard safetensors segformer vision image-segmentation generated_from_trainer license:other endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #segformer #vision #image-segmentation #generated_from_trainer #license-other #endpoints_compatible #has_space #region-us 

segformer-b0-finetuned-human-parsing
====================================


This model is a fine-tuned version of nvidia/mit-b0 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9476
* Mean Iou: 0.0726
* Mean Accuracy: 0.1221
* Overall Accuracy: 0.3575
* Accuracy Background: nan
* Accuracy Hat: 0.0048
* Accuracy Hair: 0.4813
* Accuracy Sunglasses: 0.0
* Accuracy Upper-clothes: 0.9405
* Accuracy Skirt: 0.0000
* Accuracy Pants: 0.0631
* Accuracy Dress: 0.1031
* Accuracy Belt: 0.0
* Accuracy Left-shoe: 0.0011
* Accuracy Right-shoe: 0.0010
* Accuracy Face: 0.4406
* Accuracy Left-leg: 0.0291
* Accuracy Right-leg: 0.0
* Accuracy Left-arm: 0.0
* Accuracy Right-arm: 0.0001
* Accuracy Bag: 0.0114
* Accuracy Scarf: 0.0
* Iou Background: 0.0
* Iou Hat: 0.0043
* Iou Hair: 0.4221
* Iou Sunglasses: 0.0
* Iou Upper-clothes: 0.3239
* Iou Skirt: 0.0000
* Iou Pants: 0.0559
* Iou Dress: 0.0728
* Iou Belt: 0.0
* Iou Left-shoe: 0.0011
* Iou Right-shoe: 0.0009
* Iou Face: 0.3872
* Iou Left-leg: 0.0271
* Iou Right-leg: 0.0
* Iou Left-arm: 0.0
* Iou Right-arm: 0.0001
* Iou Bag: 0.0106
* Iou Scarf: 0.0


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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #safetensors #segformer #vision #image-segmentation #generated_from_trainer #license-other #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3