--- license: other tags: - generated_from_trainer datasets: - scene_parse_150 model-index: - name: segformer-b0-scene-parse-150 results: [] --- # segformer-b0-scene-parse-150 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the scene_parse_150 dataset. It achieves the following results on the evaluation set: - Loss: 3.2289 - Mean Iou: 0.0624 - Mean Accuracy: 0.1917 - Overall Accuracy: 0.3217 - Per Category Iou: [0.2478175629093416, 0.25383335249325295, 0.8595279462283469, 0.3585768829967094, 0.0, 0.09958428678812746, 0.01625582944703531, 0.0, 0.08457054462449773, nan, 0.05180472234492783, 0.03730669006246153, 0.13281580262096, 0.003548456316827952, nan, 0.0, 0.00566525353600937, 0.06168678810630946, nan, 0.2245182436378021, 0.14621728948172283, 0.20058242899202094, 0.0, nan, 0.0, 0.0, 0.02158498001776199, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] - Per Category Accuracy: [0.5219981938563889, 0.5001658464235151, 0.9977606431263399, 0.9121276782964495, 0.0, 0.6783117875024752, 0.016302376634532788, nan, 0.0941490255376344, nan, 0.8225113122171945, 0.3077670951712218, 0.5481798715203426, 0.00355890566275432, nan, 0.0, 0.00566525353600937, 0.10318989509740954, nan, 0.33737156443714794, 0.479978608195735, 0.9331381403735133, 0.0, nan, 0.0, nan, 0.02162684481643946, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] ## 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 | Per Category Iou | Per Category Accuracy | 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| 4.2285 | 1.0 | 20 | 4.2035 | 0.0431 | 0.1369 | 0.2843 | [0.22050628234305308, 0.2563038672781469, 0.8125239885835986, 0.2703117244673665, 7.155196205701669e-05, 0.05622590511416175, 0.0, 0.0, 0.01720283194634207, nan, 0.07446164326533701, 0.0, 0.0, 0.0, 0.0, 0.0, 0.005959625108214245, 0.0, nan, 0.18143939878069043, 0.0, 0.3020646758068193, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0] | [0.4929002219106095, 0.42711251938245803, 0.9944828463144213, 0.7967024506137533, 0.0025017869907076485, 0.5590223756046505, 0.0, nan, 0.01745211693548387, nan, 0.8902714932126696, 0.0, 0.0, 0.0, nan, 0.0, 0.006047180740684159, 0.0, nan, 0.40182286506835746, 0.0, 0.6137329826476767, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] | | 4.1493 | 2.0 | 40 | 3.9645 | 0.0397 | 0.1236 | 0.3160 | [0.2494581568011776, 0.3504709042216185, 0.6945768786978617, 0.24269182770487463, 0.0, 0.08821616654296116, 0.0, 0.0, 0.01828378905848758, nan, 0.0407216459831951, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0002672095686474106, 0.0, nan, 0.038871612616614835, 0.0, 0.10474296079482211, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] | [0.4737405778751946, 0.7294492011056428, 0.999311238816461, 0.8470456245325355, 0.0, 0.7060337755650476, 0.0, nan, 0.01869119623655914, nan, 0.6781674208144797, 0.0, 0.0, 0.0, nan, 0.0, 0.0002673490432723523, 0.0, nan, 0.0743015652863087, 0.0, 0.16811407208906093, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] | | 3.7043 | 3.0 | 60 | 3.8422 | 0.0369 | 0.1197 | 0.3047 | [0.2021212658805299, 0.37212244496824687, 0.6943778657134937, 0.178581155596037, 0.0, 0.08608014243237187, 0.0, 0.0, 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0.0028022304622264994, 0.004077812688013905, 0.0664317734438324, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] | | 3.5075 | 4.0 | 80 | 3.9024 | 0.0425 | 0.1258 | 0.3038 | [0.24532855441440674, 0.29787745967326146, 0.8339459035112761, 0.18163523652986108, 0.0, 0.08493965781957022, 0.0, 0.0, 0.0, nan, 0.04218993253762325, 0.0, 0.05424256398432096, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0036449340897256708, 0.0, 0.08577250021908685, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] | [0.4963672915560517, 0.6309957527135441, 0.990565737839833, 0.8885234722161116, 0.0, 0.8294249101864162, 0.0, nan, 0.0, nan, 0.7357466063348417, 0.0, 0.0746292330874772, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.003764612641172974, 0.0, 0.12952210808396605, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] | | 3.4706 | 5.0 | 100 | 3.7212 | 0.0470 | 0.1324 | 0.3401 | [0.29729258586902946, 0.33147047893754256, 0.6567743612234621, 0.17931655544616598, 0.0, 0.15023420427789919, 0.0, 0.0, 0.0, nan, 0.03693687018375815, 0.0, 0.0005457664119756744, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.008637438756546713, 0.0, 0.36042466127982953, 0.0, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 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nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] | | 2.9252 | 6.0 | 120 | 3.6661 | 0.0458 | 0.1381 | 0.3267 | [0.26655654652977095, 0.3628751321035356, 0.668043495193295, 0.19590840707440443, 0.0, 0.08144395016597901, 0.0, 0.0, 0.0, nan, 0.047927470036745766, 0.00012295333920777065, 0.017286963595688428, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.007809601543370186, 0.003069956636862504, 0.27059077498740736, 0.0, nan, 0.0, 0.0, 0.001726672584045268, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 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0.016302376634532788, nan, 0.0941490255376344, nan, 0.8225113122171945, 0.3077670951712218, 0.5481798715203426, 0.00355890566275432, nan, 0.0, 0.00566525353600937, 0.10318989509740954, nan, 0.33737156443714794, 0.479978608195735, 0.9331381403735133, 0.0, nan, 0.0, nan, 0.02162684481643946, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan] | ### Framework versions - Transformers 4.26.1 - Pytorch 1.13.1+cu116 - Datasets 2.10.1 - Tokenizers 0.13.2