--- 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 --- # 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