|
--- |
|
license: other |
|
tags: |
|
- vision |
|
- image-segmentation |
|
- generated_from_trainer |
|
model-index: |
|
- name: parking-utcustom-train-SF-RGBD-b0_5 |
|
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_5 |
|
|
|
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the sam1120/parking-utcustom-train dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0175 |
|
- 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: 0.00035 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:| |
|
| 0.4985 | 20.0 | 20 | 0.4840 | 0.4998 | 0.9996 | 0.9996 | nan | nan | 0.9996 | nan | 0.0 | 0.9996 | |
|
| 0.1979 | 40.0 | 40 | 0.1365 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | |
|
| 0.1257 | 60.0 | 60 | 0.0414 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | |
|
| 0.0952 | 80.0 | 80 | 0.0249 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | |
|
| 0.0768 | 100.0 | 100 | 0.0225 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | |
|
| 0.054 | 120.0 | 120 | 0.0189 | 1.0 | 1.0 | 1.0 | nan | nan | 1.0 | nan | nan | 1.0 | |
|
| 0.0537 | 140.0 | 140 | 0.0175 | 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 |
|
|
