--- license: other base_model: nvidia/mit-b0 tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b0-finetuned-segments-stamp-verification results: [] --- # segformer-b0-finetuned-segments-stamp-verification This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the AliShah07/stamp-verification dataset. It achieves the following results on the evaluation set: - Loss: 0.0535 - Mean Iou: 0.1317 - Mean Accuracy: 0.2635 - Overall Accuracy: 0.2635 - Accuracy Unlabeled: nan - Accuracy Stamp: 0.2635 - Iou Unlabeled: 0.0 - Iou Stamp: 0.2635 ## 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: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Stamp | Iou Unlabeled | Iou Stamp | |:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:| | 0.6502 | 0.8333 | 20 | 0.6958 | 0.4685 | 0.9370 | 0.9370 | nan | 0.9370 | 0.0 | 0.9370 | | 0.4529 | 1.6667 | 40 | 0.5458 | 0.0754 | 0.1508 | 0.1508 | nan | 0.1508 | 0.0 | 0.1508 | | 0.3716 | 2.5 | 60 | 0.3818 | 0.0021 | 0.0041 | 0.0041 | nan | 0.0041 | 0.0 | 0.0041 | | 0.3238 | 3.3333 | 80 | 0.2932 | 0.0126 | 0.0252 | 0.0252 | nan | 0.0252 | 0.0 | 0.0252 | | 0.2167 | 4.1667 | 100 | 0.2326 | 0.0008 | 0.0015 | 0.0015 | nan | 0.0015 | 0.0 | 0.0015 | | 0.1948 | 5.0 | 120 | 0.2029 | 0.0033 | 0.0065 | 0.0065 | nan | 0.0065 | 0.0 | 0.0065 | | 0.1643 | 5.8333 | 140 | 0.1609 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | | 0.1642 | 6.6667 | 160 | 0.1428 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | | 0.1326 | 7.5 | 180 | 0.1222 | 0.0001 | 0.0002 | 0.0002 | nan | 0.0002 | 0.0 | 0.0002 | | 0.1012 | 8.3333 | 200 | 0.0981 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | | 0.0981 | 9.1667 | 220 | 0.0972 | 0.0058 | 0.0117 | 0.0117 | nan | 0.0117 | 0.0 | 0.0117 | | 0.0838 | 10.0 | 240 | 0.0781 | 0.0015 | 0.0031 | 0.0031 | nan | 0.0031 | 0.0 | 0.0031 | | 0.0771 | 10.8333 | 260 | 0.0708 | 0.0060 | 0.0120 | 0.0120 | nan | 0.0120 | 0.0 | 0.0120 | | 0.0743 | 11.6667 | 280 | 0.0696 | 0.0298 | 0.0596 | 0.0596 | nan | 0.0596 | 0.0 | 0.0596 | | 0.0655 | 12.5 | 300 | 0.0630 | 0.0398 | 0.0795 | 0.0795 | nan | 0.0795 | 0.0 | 0.0795 | | 0.0673 | 13.3333 | 320 | 0.0613 | 0.0856 | 0.1712 | 0.1712 | nan | 0.1712 | 0.0 | 0.1712 | | 0.0573 | 14.1667 | 340 | 0.0538 | 0.0725 | 0.1450 | 0.1450 | nan | 0.1450 | 0.0 | 0.1450 | | 0.0623 | 15.0 | 360 | 0.0543 | 0.1008 | 0.2016 | 0.2016 | nan | 0.2016 | 0.0 | 0.2016 | | 0.0557 | 15.8333 | 380 | 0.0559 | 0.1474 | 0.2947 | 0.2947 | nan | 0.2947 | 0.0 | 0.2947 | | 0.0594 | 16.6667 | 400 | 0.0492 | 0.1019 | 0.2039 | 0.2039 | nan | 0.2039 | 0.0 | 0.2039 | | 0.056 | 17.5 | 420 | 0.0479 | 0.1235 | 0.2470 | 0.2470 | nan | 0.2470 | 0.0 | 0.2470 | | 0.0499 | 18.3333 | 440 | 0.0481 | 0.1124 | 0.2248 | 0.2248 | nan | 0.2248 | 0.0 | 0.2248 | | 0.0516 | 19.1667 | 460 | 0.0477 | 0.1465 | 0.2930 | 0.2930 | nan | 0.2930 | 0.0 | 0.2930 | | 0.0517 | 20.0 | 480 | 0.0535 | 0.1317 | 0.2635 | 0.2635 | nan | 0.2635 | 0.0 | 0.2635 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1