🚀 mobilevit-small-10k-steps
This model is a fine - tuned version of apple/deeplabv3-mobilevit-small on the Efferbach/lane_master2 dataset. It offers a solution for image - segmentation tasks in the vision field, with specific performance metrics on the evaluation set.
📚 Documentation
Model Overview
This model is a fine - tuned version of apple/deeplabv3-mobilevit-small on the Efferbach/lane_master2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0821
- Mean Iou: 0.0
- Mean Accuracy: 0.0
- Overall Accuracy: 0.0
- Accuracy Background: nan
- Accuracy Left: 0.0
- Accuracy Right: 0.0
- Iou Background: 0.0
- Iou Left: 0.0
- Iou Right: 0.0
Training and Evaluation
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e - 05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
- lr_scheduler_type: polynomial
- training_steps: 10000
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
Mean Iou |
Mean Accuracy |
Overall Accuracy |
Accuracy Background |
Accuracy Left |
Accuracy Right |
Iou Background |
Iou Left |
Iou Right |
0.5041 |
1.0 |
385 |
0.3382 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.1553 |
2.0 |
770 |
0.1387 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.1019 |
3.0 |
1155 |
0.1037 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0882 |
4.0 |
1540 |
0.0883 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0828 |
5.0 |
1925 |
0.0823 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0807 |
6.0 |
2310 |
0.0820 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0795 |
7.0 |
2695 |
0.0804 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0786 |
8.0 |
3080 |
0.0784 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0777 |
9.0 |
3465 |
0.0786 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0771 |
10.0 |
3850 |
0.0774 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0773 |
11.0 |
4235 |
0.0775 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0765 |
12.0 |
4620 |
0.0782 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0757 |
13.0 |
5005 |
0.0775 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0756 |
14.0 |
5390 |
0.0774 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0754 |
15.0 |
5775 |
0.0775 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0746 |
16.0 |
6160 |
0.0775 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.074 |
17.0 |
6545 |
0.0779 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0736 |
18.0 |
6930 |
0.0792 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0737 |
19.0 |
7315 |
0.0801 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.073 |
20.0 |
7700 |
0.0804 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0729 |
21.0 |
8085 |
0.0805 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0734 |
22.0 |
8470 |
0.0804 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0726 |
23.0 |
8855 |
0.0811 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0726 |
24.0 |
9240 |
0.0816 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0721 |
25.0 |
9625 |
0.0822 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0727 |
25.97 |
10000 |
0.0821 |
0.0 |
0.0 |
0.0 |
nan |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
📄 License
The model is released under the "other" license.
Property |
Details |
Model Type |
Fine - tuned version of apple/deeplabv3 - mobilevit - small |
Training Data |
Efferbach/lane_master2 dataset |