--- license: other base_model: nvidia/mit-b0 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: 3.0184 - Mean Iou: 0.0640 - Mean Accuracy: 0.1277 - Overall Accuracy: 0.4046 - Per Category Iou: [0.34201525710959674, 0.025996616878625384, 0.7898521891625035, 0.4880628111048391, 0.6304014883644438, 0.2600362857635349, 0.0, 0.0, 0.20877671078813045, 0.0, 0.0, 0.0, 0.5262114201454212, 0.0, 0.0, 0.058912017109042966, 0.03817073170731707, 0.0, 0.0, 0.02204585537918871, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] - Per Category Accuracy: [0.7327903499042605, 0.8452460476508573, 0.9948029771516602, 0.9114927547343402, 0.7048267540079297, 0.27804903954590465, nan, nan, 0.282045288531775, 0.0, nan, 0.0, 0.6049924003273706, 0.0, 0.0, 0.33099129372231556, 0.03817073170731707, 0.0, 0.0, 0.022592176078399872, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] ## 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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| 4.9072 | 1.0 | 20 | 4.9606 | 0.0050 | 0.0344 | 0.0694 | [0.1906469231131409, 0.00029699510831586305, 0.2444145404639474, 0.029686890090893883, 0.0, 0.08313867556924476, 0.0, 0.0, 0.05966918425448813, 0.0, 0.0, 7.385673136963951e-05, 0.014832859204631723, 0.00032013218361129754, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0005753556017260668, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.013377071782163508, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 7.705703761924576e-05, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0] | [0.223437129251025, 0.0037853484747272324, 0.2545241939974386, 0.03265353062945641, 0.0, 0.1005126378827212, nan, nan, 0.07409788166544923, 0.0, nan, 9.237487403426268e-05, 0.01732335632721462, 0.00032807010117258606, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0007229496345087958, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, 0.8424401197604791, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 7.803233660028715e-05, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] | | 4.7934 | 2.0 | 40 | 4.7759 | 0.0165 | 0.0565 | 0.1851 | [0.311921114599686, 0.0, 0.7675367243410455, 0.1272097800078871, 0.18671618940235565, 0.05900296147856205, 0.0, 0.0, 0.03291417217850514, 0.0, 0.0, 0.0005156578819004084, 0.08754368486803611, 0.0, 0.0, 0.0, 0.01352250297167908, 0.0, 0.0, 0.00017418264792461375, 0.0, 0.0, 0.0, 0.0020930927937805243, 0.12920699118879098, nan, 0.0, 0.0, 0.0, nan, 0.014315345642490394, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0] | [0.5262800668796662, 0.0, 0.8888208326373035, 0.20156405734876945, 0.1941159570189048, 0.08296548988000962, nan, nan, 0.03678597516435354, 0.0, nan, 0.000621430970775949, 0.10787637865856035, 0.0, 0.0, 0.0, 0.013747228381374724, 0.0, 0.0, 0.00020081934291910997, nan, 0.0, 0.0, 0.015173410404624277, 0.16057804505879186, nan, nan, nan, nan, nan, 0.31511976047904194, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] | | 4.1223 | 3.0 | 60 | 4.5469 | 0.0218 | 0.0677 | 0.2787 | [0.3408503958804526, 0.002009036875303251, 0.6807422606605685, 0.18752806062627195, 0.3057785044715604, 0.1379944821120929, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1869221504831071, 0.0, 4.973639709539441e-05, 0.0, 0.0010866554449960582, 0.0, 0.0, 0.000533843859875191, 0.0, 0.0, 0.0, 0.0, 0.0031025243266111975, nan, nan, 0.0, 0.0, nan, 0.007676746719228176, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0] | [0.5979218743964552, 0.05900690269427744, 0.9883252593871226, 0.6100513685501802, 0.31808308912256505, 0.20968795004201693, nan, nan, 0.0, 0.0, nan, 0.0, 0.20111851592033983, 0.0, 0.00025097251850922326, 0.0, 0.001130820399113082, 0.0, 0.0, 0.0005823760944654189, nan, 0.0, 0.0, 0.0, 0.003949376178080962, nan, nan, nan, nan, nan, 0.05538922155688623, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] | | 4.2254 | 4.0 | 80 | 4.4098 | 0.0305 | 0.0732 | 0.2883 | [0.32455661784828344, 0.0033069343870300335, 0.660569093180853, 0.18995896693217476, 0.6200845689061766, 0.12972526282995656, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.23372471147627594, 0.0, 0.0, 0.0, 0.00011024993660628645, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0028989929813854134, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] | [0.5071818387493723, 0.08684034736138944, 0.9959908680884236, 0.6426090623322855, 0.6522093891857725, 0.153494590904973, nan, nan, 0.0, 0.0, nan, 0.0, 0.25, 0.0, 0.0, 0.0, 0.00011086474501108647, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.003410824881069922, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] | | 3.8409 | 5.0 | 100 | 4.2706 | 0.0389 | 0.0802 | 0.2838 | [0.25873246598207084, 0.0034625138510871426, 0.6751214484574631, 0.2442992068461699, 0.631843704839546, 0.15087493040055966, 0.0, 0.0, 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nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0] | ### Framework versions - Transformers 4.33.3 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.13.3