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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: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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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: 1.6110 |
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- Mean Iou: 0.1367 |
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- Mean Accuracy: 0.1875 |
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- Overall Accuracy: 0.6881 |
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- Per Category Iou: [nan, 0.4358992825292338, 0.7376212533796545, 0.0, 0.02621246785982382, 0.00043211553703970075, nan, 8.015736841193088e-05, 0.0, 0.0, 0.5772424406028427, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.5033973978720222, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6694084376012885, 0.36677387384992766, 0.7828643395512115, 0.0, 0.0, 0.0, 0.0] |
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- Per Category Accuracy: [nan, 0.7389109053459296, 0.9324628469379894, 0.0, 0.02623033308234139, 0.0004332220803205606, nan, 8.024933685852042e-05, 0.0, 0.0, 0.8439578372191763, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.8847599631606713, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9401313327814339, 0.38739120652321696, 0.8720917833707338, 0.0, 0.0, 0.0, 0.0] |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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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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| 1.9298 | 0.5 | 100 | 1.7681 | 0.1199 | 0.1738 | 0.6593 | [nan, 0.40090810552182926, 0.7239864361905679, 0.0, 0.0017647225539722043, 0.00039874720019120934, nan, 0.0001017888855199896, 0.0, 0.0, 0.5266858358368541, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.4982673421879428, 0.0, 0.00013373579730320418, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6162371375150854, 0.06163531325154459, 0.7657580090286384, 0.0, 0.0, 0.00018678310951226077, 0.0] | [nan, 0.7294785690321806, 0.9040101249330418, 0.0, 0.001765437619648865, 0.00039998860566583264, nan, 0.0001019383468202827, 0.0, 0.0, 0.8602156135201492, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.8580331196294607, 0.0, 0.00013373747781887638, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9448016748237693, 0.06210387463397946, 0.852450875265527, 0.0, 0.0, 0.0001871709770030242, 0.0] | |
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| 2.0284 | 1.0 | 200 | 1.6110 | 0.1367 | 0.1875 | 0.6881 | [nan, 0.4358992825292338, 0.7376212533796545, 0.0, 0.02621246785982382, 0.00043211553703970075, nan, 8.015736841193088e-05, 0.0, 0.0, 0.5772424406028427, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.5033973978720222, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6694084376012885, 0.36677387384992766, 0.7828643395512115, 0.0, 0.0, 0.0, 0.0] | [nan, 0.7389109053459296, 0.9324628469379894, 0.0, 0.02623033308234139, 0.0004332220803205606, nan, 8.024933685852042e-05, 0.0, 0.0, 0.8439578372191763, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.8847599631606713, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9401313327814339, 0.38739120652321696, 0.8720917833707338, 0.0, 0.0, 0.0, 0.0] | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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