--- license: other base_model: nvidia/mit-b0 tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b0-finetuned-HikingHD results: [] --- # segformer-b0-finetuned-HikingHD This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the twdent/HikingHD dataset. It achieves the following results on the evaluation set: - Loss: 0.1189 - Mean Iou: 0.9224 - Mean Accuracy: 0.9627 - Overall Accuracy: 0.9622 - Accuracy Traversable: 0.9645 - Accuracy Non-traversable: 0.9608 - Iou Traversable: 0.9032 - Iou Non-traversable: 0.9415 ## 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: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Traversable | Accuracy Non-traversable | Iou Traversable | Iou Non-traversable | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------------:|:------------------------:|:---------------:|:-------------------:| | 0.1555 | 1.33 | 20 | 0.3462 | 0.8817 | 0.9484 | 0.9401 | 0.9792 | 0.9176 | 0.8568 | 0.9067 | | 0.1168 | 2.67 | 40 | 0.1551 | 0.8998 | 0.9529 | 0.9503 | 0.9628 | 0.9431 | 0.8764 | 0.9233 | | 0.1054 | 4.0 | 60 | 0.1566 | 0.8910 | 0.9527 | 0.9452 | 0.9807 | 0.9247 | 0.8675 | 0.9146 | | 0.0775 | 5.33 | 80 | 0.1892 | 0.8645 | 0.9415 | 0.9304 | 0.9830 | 0.9000 | 0.8378 | 0.8912 | | 0.1111 | 6.67 | 100 | 0.1369 | 0.9015 | 0.9515 | 0.9514 | 0.9520 | 0.9511 | 0.8776 | 0.9255 | | 0.0737 | 8.0 | 120 | 0.1358 | 0.9005 | 0.9503 | 0.9510 | 0.9476 | 0.9529 | 0.8761 | 0.9249 | | 0.0908 | 9.33 | 140 | 0.1186 | 0.9097 | 0.9565 | 0.9556 | 0.9599 | 0.9532 | 0.8878 | 0.9316 | | 0.0654 | 10.67 | 160 | 0.1177 | 0.9182 | 0.9624 | 0.9599 | 0.9719 | 0.9529 | 0.8986 | 0.9377 | | 0.0871 | 12.0 | 180 | 0.1220 | 0.9105 | 0.9546 | 0.9563 | 0.9482 | 0.9609 | 0.8880 | 0.9330 | | 0.0493 | 13.33 | 200 | 0.1237 | 0.9126 | 0.9559 | 0.9573 | 0.9504 | 0.9613 | 0.8907 | 0.9346 | | 0.0643 | 14.67 | 220 | 0.1232 | 0.9107 | 0.9503 | 0.9567 | 0.9265 | 0.9741 | 0.8868 | 0.9345 | | 0.0491 | 16.0 | 240 | 0.1199 | 0.9140 | 0.9573 | 0.9580 | 0.9545 | 0.9600 | 0.8926 | 0.9355 | | 0.0556 | 17.33 | 260 | 0.1114 | 0.9199 | 0.9613 | 0.9609 | 0.9628 | 0.9598 | 0.9001 | 0.9396 | | 0.0484 | 18.67 | 280 | 0.1137 | 0.9189 | 0.9628 | 0.9603 | 0.9720 | 0.9535 | 0.8995 | 0.9383 | | 0.0607 | 20.0 | 300 | 0.1230 | 0.9163 | 0.9625 | 0.9588 | 0.9762 | 0.9488 | 0.8966 | 0.9359 | | 0.044 | 21.33 | 320 | 0.1349 | 0.9077 | 0.9567 | 0.9545 | 0.9648 | 0.9485 | 0.8858 | 0.9297 | | 0.0426 | 22.67 | 340 | 0.1313 | 0.9070 | 0.9563 | 0.9541 | 0.9646 | 0.9481 | 0.8850 | 0.9291 | | 0.0269 | 24.0 | 360 | 0.1143 | 0.9226 | 0.9668 | 0.9620 | 0.9850 | 0.9487 | 0.9046 | 0.9406 | | 0.0593 | 25.33 | 380 | 0.1038 | 0.9235 | 0.9616 | 0.9629 | 0.9570 | 0.9662 | 0.9041 | 0.9428 | | 0.0321 | 26.67 | 400 | 0.1136 | 0.9179 | 0.9598 | 0.9599 | 0.9595 | 0.9602 | 0.8976 | 0.9383 | | 0.0752 | 28.0 | 420 | 0.1196 | 0.9194 | 0.9627 | 0.9606 | 0.9705 | 0.9548 | 0.9000 | 0.9388 | | 0.0812 | 29.33 | 440 | 0.1253 | 0.9216 | 0.9665 | 0.9615 | 0.9854 | 0.9477 | 0.9035 | 0.9398 | | 0.0329 | 30.67 | 460 | 0.1023 | 0.9294 | 0.9671 | 0.9657 | 0.9725 | 0.9618 | 0.9120 | 0.9467 | | 0.035 | 32.0 | 480 | 0.0969 | 0.9282 | 0.9658 | 0.9651 | 0.9686 | 0.9631 | 0.9104 | 0.9460 | | 0.0332 | 33.33 | 500 | 0.1086 | 0.9231 | 0.9620 | 0.9626 | 0.9598 | 0.9643 | 0.9038 | 0.9424 | | 0.0343 | 34.67 | 520 | 0.0962 | 0.9312 | 0.9689 | 0.9666 | 0.9774 | 0.9603 | 0.9145 | 0.9480 | | 0.0337 | 36.0 | 540 | 0.1072 | 0.9251 | 0.9649 | 0.9635 | 0.9703 | 0.9595 | 0.9067 | 0.9434 | | 0.0367 | 37.33 | 560 | 0.1033 | 0.9302 | 0.9692 | 0.9660 | 0.9809 | 0.9574 | 0.9135 | 0.9470 | | 0.0327 | 38.67 | 580 | 0.1014 | 0.9312 | 0.9681 | 0.9666 | 0.9734 | 0.9627 | 0.9143 | 0.9482 | | 0.0293 | 40.0 | 600 | 0.1202 | 0.9207 | 0.9622 | 0.9613 | 0.9656 | 0.9588 | 0.9012 | 0.9401 | | 0.0272 | 41.33 | 620 | 0.1113 | 0.9246 | 0.9634 | 0.9633 | 0.9637 | 0.9631 | 0.9058 | 0.9433 | | 0.0304 | 42.67 | 640 | 0.1070 | 0.9253 | 0.9643 | 0.9637 | 0.9668 | 0.9619 | 0.9069 | 0.9438 | | 0.037 | 44.0 | 660 | 0.1120 | 0.9228 | 0.9629 | 0.9624 | 0.9648 | 0.9610 | 0.9037 | 0.9419 | | 0.0323 | 45.33 | 680 | 0.1132 | 0.9213 | 0.9615 | 0.9617 | 0.9609 | 0.9621 | 0.9016 | 0.9409 | | 0.0281 | 46.67 | 700 | 0.1203 | 0.9199 | 0.9616 | 0.9609 | 0.9643 | 0.9589 | 0.9002 | 0.9396 | | 0.0339 | 48.0 | 720 | 0.1124 | 0.9253 | 0.9646 | 0.9637 | 0.9683 | 0.9610 | 0.9070 | 0.9437 | | 0.0289 | 49.33 | 740 | 0.1189 | 0.9224 | 0.9627 | 0.9622 | 0.9645 | 0.9608 | 0.9032 | 0.9415 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.1+cu121 - Datasets 2.14.6 - Tokenizers 0.14.1