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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: 4.9393 |
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- Mean Iou: 0.0036 |
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- Mean Accuracy: 0.0214 |
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- Overall Accuracy: 0.0867 |
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- Per Category Iou: [0.16545709180085544, 0.0, 0.0, 0.0, 0.0, 0.058472783227543755, nan, 0.0, 0.0, 0.0, 0.007622227522060578, nan, 3.137911197113122e-05, 0.0, 0.058198708972300964, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.041340794105739556, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0024778587375187066, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.016656203154428628, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0007263579350175389, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0697279103015839, 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, 0.012292855202390655, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, 0.0, 0.0] |
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- Per Category Accuracy: [0.18326833008776816, nan, 0.0, 0.0, 0.0, 0.09695526450076544, nan, nan, 0.0, nan, 0.009522447471605468, nan, 0.0035169988276670576, 0.0, 0.06740772973614463, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.07055362102652567, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0025769907891715358, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.018805149717922753, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0010196214966054064, nan, nan, nan, nan, nan, nan, 0.23142163272931066, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.019714628036161638, 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, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 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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| 4.8574 | 1.0 | 20 | 4.9393 | 0.0036 | 0.0214 | 0.0867 | [0.16545709180085544, 0.0, 0.0, 0.0, 0.0, 0.058472783227543755, nan, 0.0, 0.0, 0.0, 0.007622227522060578, nan, 3.137911197113122e-05, 0.0, 0.058198708972300964, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.041340794105739556, nan, 0.0, 0.0, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0024778587375187066, 0.0, nan, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.016656203154428628, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, 0.0, 0.0, 0.0, 0.0007263579350175389, 0.0, nan, nan, 0.0, 0.0, 0.0, 0.0697279103015839, 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, 0.012292855202390655, 0.0, 0.0, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, nan, 0.0, nan, nan, 0.0, nan, 0.0, 0.0, 0.0, 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, 0.0, 0.0, nan, nan, nan, 0.0, 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, 0.0, 0.0, nan, 0.0, 0.0] | [0.18326833008776816, nan, 0.0, 0.0, 0.0, 0.09695526450076544, nan, nan, 0.0, nan, 0.009522447471605468, nan, 0.0035169988276670576, 0.0, 0.06740772973614463, 0.0, nan, 0.0, 0.0, 0.0, nan, 0.0, 0.0, nan, nan, nan, nan, 0.07055362102652567, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, 0.0025769907891715358, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.018805149717922753, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0010196214966054064, nan, nan, nan, nan, nan, nan, 0.23142163272931066, 0.0, nan, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.019714628036161638, 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, nan, nan, nan, nan, nan, nan, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, 0.0, nan, nan, nan, nan, nan, nan, nan, 0.0, 0.0, nan, nan, nan] | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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