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dropoff-utcustom-train-SF-RGBD-b0_3

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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_3
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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_3
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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: 0.3666
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+ - Mean Iou: 0.6400
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+ - Mean Accuracy: 0.7120
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+ - Overall Accuracy: 0.9610
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Dropoff: 0.4404
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+ - Accuracy Undropoff: 0.9836
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+ - Iou Unlabeled: nan
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+ - Iou Dropoff: 0.3196
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+ - Iou Undropoff: 0.9603
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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: 4e-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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+ | 1.0352 | 5.0 | 10 | 1.0676 | 0.2560 | 0.5776 | 0.7142 | nan | 0.4286 | 0.7266 | 0.0 | 0.0589 | 0.7090 |
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+ | 0.9564 | 10.0 | 20 | 0.9743 | 0.3355 | 0.5576 | 0.9248 | nan | 0.1571 | 0.9581 | 0.0 | 0.0822 | 0.9243 |
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+ | 0.8577 | 15.0 | 30 | 0.8504 | 0.3318 | 0.5283 | 0.9409 | nan | 0.0782 | 0.9784 | 0.0 | 0.0545 | 0.9407 |
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+ | 0.7512 | 20.0 | 40 | 0.6972 | 0.3270 | 0.5122 | 0.9527 | nan | 0.0318 | 0.9926 | 0.0 | 0.0283 | 0.9526 |
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+ | 0.6955 | 25.0 | 50 | 0.5761 | 0.3259 | 0.5099 | 0.9545 | nan | 0.0250 | 0.9948 | 0.0 | 0.0234 | 0.9544 |
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+ | 0.6691 | 30.0 | 60 | 0.5209 | 0.3360 | 0.5271 | 0.9525 | nan | 0.0632 | 0.9911 | 0.0 | 0.0557 | 0.9524 |
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+ | 0.626 | 35.0 | 70 | 0.5297 | 0.3408 | 0.5362 | 0.9505 | nan | 0.0844 | 0.9881 | 0.0 | 0.0719 | 0.9503 |
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+ | 0.5544 | 40.0 | 80 | 0.5263 | 0.3616 | 0.5757 | 0.9521 | nan | 0.1652 | 0.9862 | 0.0 | 0.1330 | 0.9518 |
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+ | 0.5316 | 45.0 | 90 | 0.4825 | 0.3836 | 0.6353 | 0.9506 | nan | 0.2915 | 0.9792 | 0.0 | 0.2009 | 0.9500 |
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+ | 0.4929 | 50.0 | 100 | 0.4763 | 0.3958 | 0.6588 | 0.9530 | nan | 0.3378 | 0.9797 | 0.0 | 0.2352 | 0.9524 |
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+ | 0.468 | 55.0 | 110 | 0.4583 | 0.4077 | 0.6974 | 0.9528 | nan | 0.4188 | 0.9759 | 0.0 | 0.2713 | 0.9519 |
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+ | 0.429 | 60.0 | 120 | 0.4268 | 0.3985 | 0.6526 | 0.9575 | nan | 0.3199 | 0.9852 | 0.0 | 0.2386 | 0.9569 |
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+ | 0.4211 | 65.0 | 130 | 0.3988 | 0.3951 | 0.6406 | 0.9584 | nan | 0.2939 | 0.9872 | 0.0 | 0.2275 | 0.9578 |
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+ | 0.3926 | 70.0 | 140 | 0.4085 | 0.4102 | 0.6780 | 0.9587 | nan | 0.3718 | 0.9842 | 0.0 | 0.2726 | 0.9581 |
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+ | 0.4006 | 75.0 | 150 | 0.3944 | 0.6077 | 0.6574 | 0.9604 | nan | 0.3269 | 0.9879 | nan | 0.2555 | 0.9599 |
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+ | 0.3978 | 80.0 | 160 | 0.3881 | 0.6216 | 0.6875 | 0.9591 | nan | 0.3912 | 0.9838 | nan | 0.2848 | 0.9585 |
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+ | 0.3553 | 85.0 | 170 | 0.3877 | 0.6333 | 0.7077 | 0.9595 | nan | 0.4329 | 0.9824 | nan | 0.3079 | 0.9588 |
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+ | 0.3637 | 90.0 | 180 | 0.4004 | 0.6428 | 0.7273 | 0.9594 | nan | 0.4741 | 0.9805 | nan | 0.3270 | 0.9586 |
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+ | 0.3416 | 95.0 | 190 | 0.3835 | 0.6403 | 0.7166 | 0.9604 | nan | 0.4507 | 0.9825 | nan | 0.3210 | 0.9596 |
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+ | 0.342 | 100.0 | 200 | 0.3634 | 0.6371 | 0.7061 | 0.9611 | nan | 0.4279 | 0.9842 | nan | 0.3137 | 0.9604 |
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+ | 0.3393 | 105.0 | 210 | 0.3740 | 0.6429 | 0.7217 | 0.9604 | nan | 0.4614 | 0.9820 | nan | 0.3262 | 0.9596 |
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+ | 0.3535 | 110.0 | 220 | 0.3771 | 0.6423 | 0.7199 | 0.9605 | nan | 0.4575 | 0.9823 | nan | 0.3249 | 0.9597 |
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+ | 0.3159 | 115.0 | 230 | 0.3710 | 0.6423 | 0.7167 | 0.9610 | nan | 0.4502 | 0.9832 | nan | 0.3243 | 0.9603 |
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+ | 0.3278 | 120.0 | 240 | 0.3666 | 0.6400 | 0.7120 | 0.9610 | nan | 0.4404 | 0.9836 | nan | 0.3196 | 0.9603 |
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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