mit-b0-finetuned-human-parsing-dataset
This model is a fine-tuned version of nvidia/mit-b0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1612
- Mean Iou: 0.5450
- Mean Accuracy: 0.6607
- Overall Accuracy: 0.8160
- Accuracy Background: nan
- Accuracy Hat: 0.5935
- Accuracy Hair: 0.8675
- Accuracy Sunglasses: 0.1278
- Accuracy Upper-clothes: 0.8806
- Accuracy Skirt: 0.7150
- Accuracy Pants: 0.8529
- Accuracy Dress: 0.8186
- Accuracy Belt: 0.0817
- Accuracy Left-shoe: 0.6562
- Accuracy Right-shoe: 0.6193
- Accuracy Face: 0.8987
- Accuracy Left-leg: 0.8838
- Accuracy Right-leg: 0.8541
- Accuracy Left-arm: 0.8193
- Accuracy Right-arm: 0.8202
- Accuracy Bag: 0.7409
- Accuracy Scarf: 0.0012
- Iou Background: 0.0
- Iou Hat: 0.5417
- Iou Hair: 0.7745
- Iou Sunglasses: 0.1273
- Iou Upper-clothes: 0.7733
- Iou Skirt: 0.6469
- Iou Pants: 0.7596
- Iou Dress: 0.6192
- Iou Belt: 0.0773
- Iou Left-shoe: 0.5307
- Iou Right-shoe: 0.5156
- Iou Face: 0.8002
- Iou Left-leg: 0.7577
- Iou Right-leg: 0.7632
- Iou Left-arm: 0.7325
- Iou Right-arm: 0.7315
- Iou Bag: 0.6578
- Iou Scarf: 0.0012
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: 7e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.1738 | 1.0 | 200 | 0.2036 | 0.4669 | 0.5844 | 0.7641 | nan | 0.2353 | 0.8366 | 0.0 | 0.8116 | 0.6698 | 0.7972 | 0.8264 | 0.0 | 0.5317 | 0.4734 | 0.8657 | 0.8419 | 0.7916 | 0.7738 | 0.7692 | 0.7112 | 0.0 | 0.0 | 0.2283 | 0.7279 | 0.0 | 0.7127 | 0.5858 | 0.7043 | 0.5625 | 0.0 | 0.4160 | 0.3786 | 0.7652 | 0.6935 | 0.6938 | 0.6787 | 0.6674 | 0.5891 | 0.0 |
0.184 | 2.0 | 400 | 0.1841 | 0.4970 | 0.6199 | 0.7940 | nan | 0.4453 | 0.8607 | 0.0 | 0.8745 | 0.7569 | 0.8160 | 0.7201 | 0.0 | 0.5756 | 0.5385 | 0.9054 | 0.8440 | 0.8553 | 0.8249 | 0.8242 | 0.6971 | 0.0 | 0.0 | 0.4153 | 0.7599 | 0.0 | 0.7467 | 0.6348 | 0.7162 | 0.5777 | 0.0 | 0.4517 | 0.4229 | 0.7710 | 0.7025 | 0.7143 | 0.7096 | 0.7060 | 0.6183 | 0.0 |
0.1793 | 3.0 | 600 | 0.1717 | 0.5121 | 0.6276 | 0.8018 | nan | 0.5648 | 0.8591 | 0.0 | 0.8920 | 0.7414 | 0.8757 | 0.7207 | 0.0 | 0.6178 | 0.5797 | 0.8696 | 0.8117 | 0.8442 | 0.7867 | 0.7884 | 0.7170 | 0.0 | 0.0 | 0.4805 | 0.7622 | 0.0 | 0.7497 | 0.6576 | 0.7450 | 0.5970 | 0.0 | 0.4793 | 0.4538 | 0.7821 | 0.7290 | 0.7402 | 0.7075 | 0.7070 | 0.6269 | 0.0 |
0.3023 | 4.0 | 800 | 0.1753 | 0.5129 | 0.6313 | 0.7953 | nan | 0.5461 | 0.8778 | 0.0 | 0.8113 | 0.7911 | 0.8080 | 0.8468 | 0.0 | 0.6061 | 0.5468 | 0.8959 | 0.8538 | 0.8359 | 0.8053 | 0.8009 | 0.7055 | 0.0 | 0.0 | 0.4921 | 0.7589 | 0.0 | 0.7408 | 0.6533 | 0.7325 | 0.5989 | 0.0 | 0.4843 | 0.4550 | 0.7872 | 0.7399 | 0.7417 | 0.7114 | 0.7089 | 0.6265 | 0.0 |
0.1041 | 5.0 | 1000 | 0.1655 | 0.5235 | 0.6388 | 0.8078 | nan | 0.6147 | 0.8667 | 0.0025 | 0.8768 | 0.7477 | 0.8536 | 0.7777 | 0.0022 | 0.5801 | 0.5814 | 0.8896 | 0.8580 | 0.8658 | 0.8238 | 0.8236 | 0.6964 | 0.0 | 0.0 | 0.5389 | 0.7662 | 0.0025 | 0.7582 | 0.6485 | 0.7581 | 0.6070 | 0.0022 | 0.4840 | 0.4767 | 0.7900 | 0.7534 | 0.7572 | 0.7267 | 0.7204 | 0.6336 | 0.0 |
0.1179 | 6.0 | 1200 | 0.1628 | 0.5312 | 0.6475 | 0.8111 | nan | 0.5886 | 0.8725 | 0.0326 | 0.8560 | 0.7353 | 0.8538 | 0.8384 | 0.0221 | 0.6322 | 0.5871 | 0.9038 | 0.8580 | 0.8579 | 0.8263 | 0.8279 | 0.7142 | 0.0 | 0.0 | 0.5293 | 0.7663 | 0.0326 | 0.7629 | 0.6531 | 0.7624 | 0.6189 | 0.0217 | 0.5135 | 0.4931 | 0.7930 | 0.7599 | 0.7641 | 0.7293 | 0.7224 | 0.6386 | 0.0 |
0.1323 | 7.0 | 1400 | 0.1619 | 0.5390 | 0.6531 | 0.8129 | nan | 0.6147 | 0.8846 | 0.0754 | 0.8677 | 0.7143 | 0.8672 | 0.8331 | 0.0484 | 0.6528 | 0.6319 | 0.8896 | 0.8392 | 0.8467 | 0.8096 | 0.8072 | 0.7201 | 0.0 | 0.0 | 0.5489 | 0.7726 | 0.0753 | 0.7693 | 0.6392 | 0.7660 | 0.6163 | 0.0468 | 0.5264 | 0.5172 | 0.7976 | 0.7612 | 0.7666 | 0.7314 | 0.7245 | 0.6434 | 0.0 |
0.1235 | 8.0 | 1600 | 0.1612 | 0.5450 | 0.6607 | 0.8160 | nan | 0.5935 | 0.8675 | 0.1278 | 0.8806 | 0.7150 | 0.8529 | 0.8186 | 0.0817 | 0.6562 | 0.6193 | 0.8987 | 0.8838 | 0.8541 | 0.8193 | 0.8202 | 0.7409 | 0.0012 | 0.0 | 0.5417 | 0.7745 | 0.1273 | 0.7733 | 0.6469 | 0.7596 | 0.6192 | 0.0773 | 0.5307 | 0.5156 | 0.8002 | 0.7577 | 0.7632 | 0.7325 | 0.7315 | 0.6578 | 0.0012 |
0.093 | 9.0 | 1800 | 0.1621 | 0.5489 | 0.6621 | 0.8165 | nan | 0.6190 | 0.8752 | 0.1554 | 0.8799 | 0.7153 | 0.8561 | 0.8333 | 0.0834 | 0.6491 | 0.6138 | 0.8950 | 0.8622 | 0.8528 | 0.8119 | 0.8053 | 0.7411 | 0.0068 | 0.0 | 0.5590 | 0.7745 | 0.1544 | 0.7730 | 0.6432 | 0.7665 | 0.6144 | 0.0788 | 0.5308 | 0.5146 | 0.8012 | 0.7651 | 0.7687 | 0.7353 | 0.7305 | 0.6629 | 0.0068 |
0.1171 | 10.0 | 2000 | 0.1631 | 0.5504 | 0.6659 | 0.8147 | nan | 0.6300 | 0.8701 | 0.1681 | 0.8613 | 0.7188 | 0.8489 | 0.8576 | 0.0908 | 0.6585 | 0.6139 | 0.8979 | 0.8608 | 0.8580 | 0.8264 | 0.8141 | 0.7360 | 0.0096 | 0.0 | 0.5640 | 0.7730 | 0.1669 | 0.7699 | 0.6460 | 0.7657 | 0.6125 | 0.0854 | 0.5349 | 0.5162 | 0.8019 | 0.7652 | 0.7697 | 0.7366 | 0.7317 | 0.6573 | 0.0096 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for raks87/mit-b0-finetuned-human-parsing-dataset
Base model
nvidia/mit-b0