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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: dropoff-utcustom-train-SF-RGBD-b0_7 |
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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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# dropoff-utcustom-train-SF-RGBD-b0_7 |
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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: 0.2075 |
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- Mean Iou: 0.6372 |
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- Mean Accuracy: 0.6861 |
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- Overall Accuracy: 0.9647 |
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- Accuracy Unlabeled: nan |
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- Accuracy Dropoff: 0.3822 |
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- Accuracy Undropoff: 0.9900 |
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- Iou Unlabeled: nan |
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- Iou Dropoff: 0.3104 |
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- Iou Undropoff: 0.9641 |
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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: 8e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 120 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Dropoff | Accuracy Undropoff | Iou Unlabeled | Iou Dropoff | Iou Undropoff | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:| |
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| 0.9508 | 5.0 | 10 | 1.0263 | 0.3104 | 0.5474 | 0.8717 | nan | 0.1937 | 0.9011 | 0.0 | 0.0605 | 0.8706 | |
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| 0.7814 | 10.0 | 20 | 0.7568 | 0.4971 | 0.5339 | 0.9361 | nan | 0.0952 | 0.9726 | nan | 0.0584 | 0.9359 | |
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| 0.642 | 15.0 | 30 | 0.5907 | 0.5134 | 0.5443 | 0.9494 | nan | 0.1026 | 0.9861 | nan | 0.0777 | 0.9492 | |
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| 0.5118 | 20.0 | 40 | 0.4804 | 0.3658 | 0.5923 | 0.9513 | nan | 0.2006 | 0.9839 | 0.0 | 0.1464 | 0.9509 | |
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| 0.4581 | 25.0 | 50 | 0.4405 | 0.3715 | 0.5915 | 0.9569 | nan | 0.1930 | 0.9900 | 0.0 | 0.1578 | 0.9565 | |
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| 0.4213 | 30.0 | 60 | 0.4146 | 0.3828 | 0.6136 | 0.9580 | nan | 0.2379 | 0.9892 | 0.0 | 0.1910 | 0.9575 | |
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| 0.3571 | 35.0 | 70 | 0.3750 | 0.3846 | 0.6180 | 0.9578 | nan | 0.2474 | 0.9887 | 0.0 | 0.1963 | 0.9574 | |
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| 0.3205 | 40.0 | 80 | 0.3478 | 0.5777 | 0.6202 | 0.9576 | nan | 0.2522 | 0.9882 | nan | 0.1982 | 0.9571 | |
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| 0.3114 | 45.0 | 90 | 0.3461 | 0.3895 | 0.6423 | 0.9541 | nan | 0.3022 | 0.9824 | 0.0 | 0.2150 | 0.9535 | |
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| 0.2747 | 50.0 | 100 | 0.3253 | 0.5875 | 0.6357 | 0.9575 | nan | 0.2847 | 0.9867 | nan | 0.2180 | 0.9570 | |
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| 0.2593 | 55.0 | 110 | 0.3083 | 0.5967 | 0.6599 | 0.9552 | nan | 0.3377 | 0.9820 | nan | 0.2387 | 0.9546 | |
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| 0.2293 | 60.0 | 120 | 0.2762 | 0.5966 | 0.6389 | 0.9606 | nan | 0.2880 | 0.9898 | nan | 0.2331 | 0.9601 | |
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| 0.2306 | 65.0 | 130 | 0.2655 | 0.6016 | 0.6587 | 0.9577 | nan | 0.3326 | 0.9848 | nan | 0.2462 | 0.9571 | |
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| 0.2118 | 70.0 | 140 | 0.2446 | 0.6039 | 0.6509 | 0.9605 | nan | 0.3133 | 0.9886 | nan | 0.2479 | 0.9600 | |
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| 0.2038 | 75.0 | 150 | 0.2395 | 0.6164 | 0.6708 | 0.9607 | nan | 0.3547 | 0.9870 | nan | 0.2727 | 0.9601 | |
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| 0.1895 | 80.0 | 160 | 0.2196 | 0.6254 | 0.6721 | 0.9636 | nan | 0.3542 | 0.9900 | nan | 0.2878 | 0.9630 | |
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| 0.1681 | 85.0 | 170 | 0.2176 | 0.6302 | 0.6829 | 0.9630 | nan | 0.3773 | 0.9884 | nan | 0.2979 | 0.9624 | |
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| 0.1612 | 90.0 | 180 | 0.2175 | 0.6334 | 0.6870 | 0.9633 | nan | 0.3857 | 0.9884 | nan | 0.3042 | 0.9627 | |
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| 0.1545 | 95.0 | 190 | 0.2140 | 0.6337 | 0.6816 | 0.9644 | nan | 0.3732 | 0.9900 | nan | 0.3035 | 0.9638 | |
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| 0.1551 | 100.0 | 200 | 0.2134 | 0.6357 | 0.6891 | 0.9637 | nan | 0.3896 | 0.9886 | nan | 0.3083 | 0.9631 | |
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| 0.1508 | 105.0 | 210 | 0.2090 | 0.6359 | 0.6865 | 0.9642 | nan | 0.3837 | 0.9894 | nan | 0.3083 | 0.9636 | |
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| 0.1536 | 110.0 | 220 | 0.2057 | 0.6346 | 0.6801 | 0.9650 | nan | 0.3694 | 0.9908 | nan | 0.3048 | 0.9644 | |
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| 0.1392 | 115.0 | 230 | 0.2083 | 0.6387 | 0.6890 | 0.9646 | nan | 0.3883 | 0.9896 | nan | 0.3133 | 0.9640 | |
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| 0.1446 | 120.0 | 240 | 0.2075 | 0.6372 | 0.6861 | 0.9647 | nan | 0.3822 | 0.9900 | nan | 0.3104 | 0.9641 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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