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dropoff-utcustom-train-SF-RGBD-b0_5

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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_5
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+ results: []
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+ ---
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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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+
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+ # dropoff-utcustom-train-SF-RGBD-b0_5
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+
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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: 0.2608
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+ - Mean Iou: 0.6161
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+ - Mean Accuracy: 0.6630
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+ - Overall Accuracy: 0.9623
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Dropoff: 0.3365
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+ - Accuracy Undropoff: 0.9894
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+ - Iou Unlabeled: nan
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+ - Iou Dropoff: 0.2705
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+ - Iou Undropoff: 0.9617
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 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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+
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+ ### Training results
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+
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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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+ | 0.9263 | 5.0 | 10 | 1.0370 | 0.2869 | 0.7147 | 0.7632 | nan | 0.6618 | 0.7675 | 0.0 | 0.1042 | 0.7565 |
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+ | 0.8069 | 10.0 | 20 | 0.8622 | 0.4857 | 0.5062 | 0.9589 | nan | 0.0125 | 0.9999 | nan | 0.0124 | 0.9589 |
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+ | 0.6851 | 15.0 | 30 | 0.6490 | 0.4876 | 0.5081 | 0.9586 | nan | 0.0167 | 0.9995 | nan | 0.0165 | 0.9586 |
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+ | 0.5882 | 20.0 | 40 | 0.4739 | 0.3253 | 0.5085 | 0.9586 | nan | 0.0177 | 0.9994 | 0.0 | 0.0174 | 0.9585 |
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+ | 0.53 | 25.0 | 50 | 0.4153 | 0.3375 | 0.5274 | 0.9584 | nan | 0.0573 | 0.9975 | 0.0 | 0.0542 | 0.9583 |
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+ | 0.5009 | 30.0 | 60 | 0.4275 | 0.3835 | 0.6488 | 0.9475 | nan | 0.3230 | 0.9746 | 0.0 | 0.2037 | 0.9468 |
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+ | 0.4699 | 35.0 | 70 | 0.3819 | 0.4158 | 0.6985 | 0.9578 | nan | 0.4157 | 0.9813 | 0.0 | 0.2904 | 0.9570 |
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+ | 0.3946 | 40.0 | 80 | 0.3563 | 0.6183 | 0.6844 | 0.9585 | nan | 0.3854 | 0.9834 | nan | 0.2787 | 0.9579 |
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+ | 0.3788 | 45.0 | 90 | 0.3259 | 0.6292 | 0.7011 | 0.9593 | nan | 0.4196 | 0.9827 | nan | 0.2998 | 0.9585 |
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+ | 0.3412 | 50.0 | 100 | 0.3392 | 0.6170 | 0.6933 | 0.9562 | nan | 0.4066 | 0.9801 | nan | 0.2785 | 0.9555 |
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+ | 0.3326 | 55.0 | 110 | 0.3214 | 0.6279 | 0.6914 | 0.9606 | nan | 0.3977 | 0.9851 | nan | 0.2958 | 0.9600 |
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+ | 0.2954 | 60.0 | 120 | 0.3119 | 0.6261 | 0.6847 | 0.9613 | nan | 0.3831 | 0.9864 | nan | 0.2915 | 0.9607 |
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+ | 0.3006 | 65.0 | 130 | 0.2853 | 0.5900 | 0.6223 | 0.9625 | nan | 0.2513 | 0.9934 | nan | 0.2180 | 0.9621 |
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+ | 0.2715 | 70.0 | 140 | 0.3021 | 0.6314 | 0.6903 | 0.9620 | nan | 0.3938 | 0.9867 | nan | 0.3014 | 0.9614 |
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+ | 0.276 | 75.0 | 150 | 0.2950 | 0.6243 | 0.6783 | 0.9619 | nan | 0.3690 | 0.9877 | nan | 0.2873 | 0.9613 |
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+ | 0.2622 | 80.0 | 160 | 0.2843 | 0.6134 | 0.6651 | 0.9608 | nan | 0.3426 | 0.9876 | nan | 0.2665 | 0.9602 |
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+ | 0.2395 | 85.0 | 170 | 0.2752 | 0.6050 | 0.6495 | 0.9613 | nan | 0.3094 | 0.9895 | nan | 0.2493 | 0.9608 |
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+ | 0.2597 | 90.0 | 180 | 0.2813 | 0.6296 | 0.6874 | 0.9620 | nan | 0.3879 | 0.9869 | nan | 0.2979 | 0.9614 |
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+ | 0.2294 | 95.0 | 190 | 0.2747 | 0.6106 | 0.6575 | 0.9615 | nan | 0.3259 | 0.9890 | nan | 0.2602 | 0.9609 |
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+ | 0.2303 | 100.0 | 200 | 0.2606 | 0.6040 | 0.6462 | 0.9616 | nan | 0.3023 | 0.9902 | nan | 0.2468 | 0.9611 |
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+ | 0.2335 | 105.0 | 210 | 0.2606 | 0.6080 | 0.6515 | 0.9619 | nan | 0.3130 | 0.9901 | nan | 0.2547 | 0.9614 |
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+ | 0.2322 | 110.0 | 220 | 0.2619 | 0.6167 | 0.6631 | 0.9624 | nan | 0.3366 | 0.9896 | nan | 0.2715 | 0.9619 |
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+ | 0.2116 | 115.0 | 230 | 0.2618 | 0.6183 | 0.6660 | 0.9624 | nan | 0.3427 | 0.9893 | nan | 0.2747 | 0.9618 |
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+ | 0.2099 | 120.0 | 240 | 0.2608 | 0.6161 | 0.6630 | 0.9623 | nan | 0.3365 | 0.9894 | nan | 0.2705 | 0.9617 |
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+
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+
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+ ### Framework versions
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+
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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