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--- |
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license: mit |
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base_model: mattmdjaga/segformer_b2_clothes |
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tags: |
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- generated_from_trainer |
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datasets: |
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- human_parsing_29_mix |
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model-index: |
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- name: segformer-b2-human-parse-24 |
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results: [] |
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pipeline_tag: image-segmentation |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# segformer-b2-human-parse-24 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0818 |
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- Mean Iou: 0.6023 |
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- Mean Accuracy: 0.6321 |
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- Overall Accuracy: 0.9780 |
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- Accuracy Background: 0.9969 |
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- Accuracy Hat: nan |
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- Accuracy Hair: 0.9646 |
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- Accuracy Glove: 0.0 |
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- Accuracy Glasses: 0.0 |
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- Accuracy Upper Only Torso Region: 0.9747 |
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- Accuracy Dresses Only Torso Region: 0.4939 |
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- Accuracy Coat Only Torso Region: 0.0039 |
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- Accuracy Socks: 0.0 |
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- Accuracy Left Pants: 0.9604 |
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- Accuracy Right Patns: 0.9646 |
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- Accuracy Skin Around Neck Region: 0.9585 |
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- Accuracy Scarf: nan |
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- Accuracy Skirts: 0.8904 |
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- Accuracy Face: 0.9796 |
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- Accuracy Left Arm: 0.9703 |
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- Accuracy Right Arm: 0.9700 |
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- Accuracy Left Leg: 0.9267 |
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- Accuracy Right Leg: 0.9297 |
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- Accuracy Left Shoe: 0.0 |
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- Accuracy Right Shoe: 0.0 |
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- Accuracy Left Sleeve For Upper: 0.9462 |
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- Accuracy Right Sleeve For Upper: 0.9517 |
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- Accuracy Bag: 0.0234 |
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- Iou Background: 0.9941 |
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- Iou Hat: nan |
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- Iou Hair: 0.9268 |
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- Iou Glove: 0.0 |
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- Iou Glasses: 0.0 |
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- Iou Upper Only Torso Region: 0.9351 |
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- Iou Dresses Only Torso Region: 0.4059 |
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- Iou Coat Only Torso Region: 0.0035 |
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- Iou Socks: 0.0 |
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- Iou Left Pants: 0.9232 |
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- Iou Right Patns: 0.9217 |
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- Iou Skin Around Neck Region: 0.9227 |
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- Iou Scarf: nan |
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- Iou Skirts: 0.7887 |
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- Iou Face: 0.9582 |
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- Iou Left Arm: 0.9436 |
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- Iou Right Arm: 0.9426 |
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- Iou Left Leg: 0.8836 |
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- Iou Right Leg: 0.8767 |
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- Iou Left Shoe: 0.0 |
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- Iou Right Shoe: 0.0 |
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- Iou Left Sleeve For Upper: 0.9005 |
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- Iou Right Sleeve For Upper: 0.9012 |
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- Iou Bag: 0.0232 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------:|:-------------:|:--------------:|:----------------:|:--------------------------------:|:----------------------------------:|:-------------------------------:|:--------------:|:-------------------:|:--------------------:|:--------------------------------:|:--------------:|:---------------:|:-------------:|:-----------------:|:------------------:|:-----------------:|:------------------:|:------------------:|:-------------------:|:------------------------------:|:-------------------------------:|:------------:|:--------------:|:-------:|:--------:|:---------:|:-----------:|:---------------------------:|:-----------------------------:|:--------------------------:|:---------:|:--------------:|:---------------:|:---------------------------:|:---------:|:----------:|:--------:|:------------:|:-------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------------------------:|:--------------------------:|:-------:| |
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| 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 | |
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| 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 | |
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| 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 | |
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| 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 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
