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---
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license: other
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base_model: nvidia/mit-b0
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tags:
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- generated_from_trainer
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datasets:
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- scene_parse_150
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model-index:
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- name: segformer-b0-scene-parse-150
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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-scene-parse-150
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the scene_parse_150 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.9476
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- Mean Iou: 0.0059
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- Mean Accuracy: 0.0467
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- Overall Accuracy: 0.0792
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- Per Category Iou: [0.015290646787191019, 0.0, 0.0, 0.29707155265364804, 0.0, 0.08276914236227738, 0.0, 0.0, 0.0, 0.0, 0.012636310927907107, 0.0, 0.0, 0.0, 0.08227787105184403, 0.0, 0.0, 0.0, 0.02964898714815463, 0.0, 0.0, nan, 0.001510992695378508, nan, 0.0, 0.0, 0.0, 0.0008937418640346616, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0006580782683957911, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.15182749560810285, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 4.8507583352197394e-05, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.09386101051905502, 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, 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, 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, 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, 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, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
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- Per Category Accuracy: [0.015300257646825658, nan, nan, 0.3063194873378629, nan, 0.4663087217719412, nan, nan, 0.0, nan, 0.015581846316572973, nan, nan, nan, 0.09177343204121063, 0.0, nan, nan, 0.040619224731872905, 0.0, nan, nan, 0.00745248489659126, nan, 0.0, nan, nan, 0.0011775849269129355, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0006601654719106768, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.1750304681339164, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 5.521201413427562e-05, nan, nan, nan, nan, nan, nan, 0.18748493024857915, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan]
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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: 2
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- eval_batch_size: 2
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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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| 4.8424 | 1.0 | 20 | 4.9476 | 0.0059 | 0.0467 | 0.0792 | [0.015290646787191019, 0.0, 0.0, 0.29707155265364804, 0.0, 0.08276914236227738, 0.0, 0.0, 0.0, 0.0, 0.012636310927907107, 0.0, 0.0, 0.0, 0.08227787105184403, 0.0, 0.0, 0.0, 0.02964898714815463, 0.0, 0.0, nan, 0.001510992695378508, nan, 0.0, 0.0, 0.0, 0.0008937418640346616, 0.0, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0006580782683957911, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.15182749560810285, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, nan, nan, 0.0, 4.8507583352197394e-05, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.09386101051905502, 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, 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, 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, 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, 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, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] | [0.015300257646825658, nan, nan, 0.3063194873378629, nan, 0.4663087217719412, nan, nan, 0.0, nan, 0.015581846316572973, nan, nan, nan, 0.09177343204121063, 0.0, nan, nan, 0.040619224731872905, 0.0, nan, nan, 0.00745248489659126, nan, 0.0, nan, nan, 0.0011775849269129355, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0006601654719106768, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, 0.1750304681339164, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 5.521201413427562e-05, nan, nan, nan, nan, nan, nan, 0.18748493024857915, 0.0, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 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, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, 0.0, nan, nan] |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.2.0
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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