diff --git "a/README.md" "b/README.md" new file mode 100644--- /dev/null +++ "b/README.md" @@ -0,0 +1,114 @@ +--- +library_name: transformers +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: 2.8674 +- Mean Iou: 0.0770 +- Mean Accuracy: 0.1411 +- Overall Accuracy: 0.4357 +- Per Category Iou: [0.21593546299292682, 0.3935327175705143, 0.5716092270384063, 0.8738152062734401, 0.3293232591560336, 0.1997124731715091, 0.5503564157580214, 0.001307010372865094, 0.3286320849612994, 0.3105208549491596, 0.0, 0.0, 0.0, 0.01079484120220442, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.22041095890410958, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] +- Per Category Accuracy: [0.5528510134635302, 0.5464225932940638, 0.8573149914650066, 0.977952287192637, 0.8082565130260521, 0.8612516449773359, 0.6441899452105828, 0.10202521971723347, 0.36493295002263415, 0.4968127490039841, nan, 0.0, 0.0, 0.01079484120220442, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.4088425867107102, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 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 | +|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| 4.8639 | 1.0 | 20 | 4.9118 | 0.0067 | 0.0230 | 0.0932 | [0.029470638149735644, 0.10141407359730113, 0.0153454621141165, 0.36657136834339016, 0.06342547887988143, 0.0, 0.11581367776240861, 0.0, 0.008840348256143424, 0.01457480586052561, 0.0, 0.0017087772225888565, 0.0, 0.013251831459101302, 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, 0.00352948435796705, 0.0, 0.0, 0.0, 0.027341116833391754, 0.0, 0.0, 0.0007125890736342043, 0.010417905477725186, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 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, nan, 0.0, nan, 0.0, 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, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, nan, 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, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, 0.0, 0.0] | [0.03206391478029294, 0.10586117820136343, 0.01809641753411208, 0.42467603828014105, 0.2515608995769316, 0.0, 0.12423002562834405, 0.0, 0.010088361346760966, 0.016865869853917664, nan, 0.0060333707818416345, 0.0, 0.016135446849610817, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.005646371318013109, nan, nan, nan, 0.03163510435840639, nan, nan, 0.0013433337064815852, 0.0388814913448735, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan] | +| 4.4818 | 2.0 | 40 | 4.6282 | 0.0210 | 0.0682 | 0.2757 | [0.09925538458461061, 0.341860423666129, 0.19045900258677737, 0.6027165565418298, 0.09591331437295124, 0.22486592796098986, 0.2501996052252212, 0.0, 0.012321692324467927, 0.047397153109640995, 0.0, 0.011405940594059406, 0.0, 0.11724213286713286, 0.0, 0.0, 0.0006594262197398841, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.011575736756087151, 0.0, nan, nan, 0.0038084553613604156, 0.0, 0.0, 0.0004089645018812367, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0017076402178713382, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, 0.0, nan, 0.0, 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0.0, nan] | +| 3.8263 | 5.0 | 100 | 3.8665 | 0.0446 | 0.1011 | 0.3715 | [0.22990107392494116, 0.37551026107215413, 0.3122641803610964, 0.6828177043214068, 0.24328723411866554, 0.210398479902026, 0.282726189941121, 4.093110067822834e-06, 0.00514923387538541, 0.0, 0.0, 0.0, 0.0, 0.0034713612695264073, 0.0, 0.0, 0.0004774428484725875, 0.0, 0.0, nan, 0.0, 0.06448263928942208, nan, 0.0, nan, 0.0, nan, nan, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0, nan, nan, nan, nan, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 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