update model card README.md

README.md

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+---
+license: other
+tags:
+- generated_from_trainer
+model-index:
+- name: parking-utcustom-train-SF-RGBD-b0_1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# parking-utcustom-train-SF-RGBD-b0_1
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1880
+- Mean Iou: 1.0
+- Mean Accuracy: 1.0
+- Overall Accuracy: 1.0
+- Accuracy Unlabeled: nan
+- Accuracy Parking: nan
+- Accuracy Unparking: 1.0
+- Iou Unlabeled: nan
+- Iou Parking: nan
+- Iou Unparking: 1.0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 150
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Parking | Accuracy Unparking | Iou Unlabeled | Iou Parking | Iou Unparking |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:|
+| 0.7272        | 20.0  | 20   | 0.8038          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
+| 0.4838        | 40.0  | 40   | 0.3752          | 0.5000   | 0.9999        | 0.9999           | nan                | nan              | 0.9999             | 0.0           | nan         | 0.9999        |
+| 0.4131        | 60.0  | 60   | 0.3152          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
+| 0.3286        | 80.0  | 80   | 0.2614          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
+| 0.2869        | 100.0 | 100  | 0.2312          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
+| 0.2711        | 120.0 | 120  | 0.2012          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
+| 0.2536        | 140.0 | 140  | 0.1880          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.13.1
+- Tokenizers 0.13.3