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segformer-b0-finetuned-segments-sidewalk-2

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PyTorch
segformer
vision
semantic-segmentation
Generated from Trainer
Inference Endpoints
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  ---
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  license: other
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  tags:
 
 
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  - generated_from_trainer
 
 
 
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  model-index:
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  - name: segformer-b0-finetuned-segments-sidewalk-2
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  results: []
@@ -12,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # segformer-b0-finetuned-segments-sidewalk-2
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- This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5568
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- - Mean Iou: 0.1429
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- - Mean Accuracy: 0.1909
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- - Overall Accuracy: 0.7302
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- - Per Category Iou: [nan, 0.4939249651377763, 0.7719350693388762, 0.0, 0.03491527266588522, 0.0007851043658245269, nan, 0.0, 0.0, 0.0, 0.5957492947164502, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5578896542272563, 0.0, 8.731498772678703e-06, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.763823679694206, 0.5627622811191442, 0.7914659567091414, 0.0, 0.0, 3.4412391213828277e-06, 0.0]
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- - Per Category Accuracy: [nan, 0.8311952182095418, 0.9317484161484766, 0.0, 0.03491984657702897, 0.0007870032398194515, nan, 0.0, 0.0, 0.0, 0.8874888349993965, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8733272803927883, 0.0, 8.732022947756307e-06, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.9141159811565875, 0.788047139121296, 0.8472913943123015, 0.0, 0.0, 3.4413693897075525e-06, 0.0]
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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- | 2.1501 | 0.5 | 100 | 1.7902 | 0.1355 | 0.1841 | 0.7104 | [nan, 0.45744119291698754, 0.7571272493181429, 0.0, 0.00033640367932780314, 0.0003751385454855486, nan, 1.1301520807983395e-05, 0.0, 0.0, 0.603134432234208, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5277902723725074, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.7525759481063863, 0.5102277252814887, 0.7259971515863731, 0.0, 0.0, 0.0, 0.0] | [nan, 0.8342415185752861, 0.8927152239695044, 0.0, 0.00033640367932780314, 0.00037609004380752546, nan, 1.1301659177747787e-05, 0.0, 0.0, 0.8649657094576059, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9071099090067092, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.9070157155961565, 0.719362898131699, 0.7640401968695343, 0.0, 0.0, 0.0, 0.0] |
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- | 1.5623 | 1.0 | 200 | 1.5568 | 0.1429 | 0.1909 | 0.7302 | [nan, 0.4939249651377763, 0.7719350693388762, 0.0, 0.03491527266588522, 0.0007851043658245269, nan, 0.0, 0.0, 0.0, 0.5957492947164502, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5578896542272563, 0.0, 8.731498772678703e-06, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.763823679694206, 0.5627622811191442, 0.7914659567091414, 0.0, 0.0, 3.4412391213828277e-06, 0.0] | [nan, 0.8311952182095418, 0.9317484161484766, 0.0, 0.03491984657702897, 0.0007870032398194515, nan, 0.0, 0.0, 0.0, 0.8874888349993965, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.8733272803927883, 0.0, 8.732022947756307e-06, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.9141159811565875, 0.788047139121296, 0.8472913943123015, 0.0, 0.0, 3.4413693897075525e-06, 0.0] |
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  ### Framework versions
 
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  ---
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  license: other
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  tags:
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+ - vision
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+ - semantic-segmentation
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  - generated_from_trainer
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+ datasets:
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+ - ds_tag1
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+ - ds_tag2
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  model-index:
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  - name: segformer-b0-finetuned-segments-sidewalk-2
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  results: []
 
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  # segformer-b0-finetuned-segments-sidewalk-2
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6449
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+ - Mean Iou: 0.1548
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+ - Mean Accuracy: 0.2076
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+ - Overall Accuracy: 0.7095
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+ - Per Category Iou: [nan, 0.5140599138533896, 0.7174504614949924, 0.0, 0.2891488100731331, 0.0017519579090739337, nan, 2.896471421964715e-05, 0.0, 0.0, 0.572608873148249, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.5022343403146414, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.7363557838688449, 0.5136205023614682, 0.7964013451546083, 0.0, 0.0, 0.0, 0.0]
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+ - Per Category Accuracy: [nan, 0.8064241561480351, 0.9062036975406429, 0.0, 0.30153947289328054, 0.0017733699866858271, nan, 2.8972126882463944e-05, 0.0, 0.0, 0.8850507869466231, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.8639780836322506, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.9144389240012535, 0.668388685537115, 0.8810818896148822, 0.0, 0.0, 0.0, 0.0]
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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+ | 1.9382 | 0.5 | 100 | 1.8048 | 0.1339 | 0.1853 | 0.6789 | [nan, 0.4752344017185758, 0.694067134540047, 0.0, 0.12409993164299513, 0.0008311245506368295, nan, 0.0013254481219605065, 0.0, 0.0, 0.5409277406718473, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.4841581403327513, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.690024139245331, 0.2320795469313362, 0.7749690806204844, 0.0, 0.0, 0.0, 0.0] | [nan, 0.7639758158865736, 0.8976245985998512, 0.0, 0.12474373026419283, 0.0008415168706412761, nan, 0.0013278891487795974, 0.0, 0.0, 0.880573362170307, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.8526119656818829, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.9393214014210579, 0.26355731572405905, 0.8357039981550286, 0.0, 0.0, 0.0, 0.0] |
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+ | 1.5173 | 1.0 | 200 | 1.6449 | 0.1548 | 0.2076 | 0.7095 | [nan, 0.5140599138533896, 0.7174504614949924, 0.0, 0.2891488100731331, 0.0017519579090739337, nan, 2.896471421964715e-05, 0.0, 0.0, 0.572608873148249, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.5022343403146414, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.7363557838688449, 0.5136205023614682, 0.7964013451546083, 0.0, 0.0, 0.0, 0.0] | [nan, 0.8064241561480351, 0.9062036975406429, 0.0, 0.30153947289328054, 0.0017733699866858271, nan, 2.8972126882463944e-05, 0.0, 0.0, 0.8850507869466231, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.8639780836322506, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.9144389240012535, 0.668388685537115, 0.8810818896148822, 0.0, 0.0, 0.0, 0.0] |
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  ### Framework versions