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mobilenet_v2_1-10k-steps
Efferbach/mobilenet_v2_1-10k-steps
mobilenet_v2_1-10k-steps is a image segmentation model from Efferbach. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Segmentation
- Library
- transformers
- License
- other
- Model type
- mobilenet_v2
- Access
- Public
- Created
- Apr 8, 2023
- Updated
- Apr 8, 2023
- SHA
- a0e0617c
Model card
From the Hugging Face model README
<!-- 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. -->
mobilenet_v2_1-10k-steps
This model is a fine-tuned version of google/mobilenet_v2_1.0_224 on the Efferbach/lane_master2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0827
- 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
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: 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.3253 | 1.0 | 385 | 0.0989 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.128 | 2.0 | 770 | 0.1518 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1212 | 3.0 | 1155 | 0.1852 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.117 | 4.0 | 1540 | 0.1446 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1148 | 5.0 | 1925 | 0.1087 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1167 | 6.0 | 2310 | 0.1502 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1128 | 7.0 | 2695 | 0.0882 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1156 | 8.0 | 3080 | 0.1005 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1164 | 9.0 | 3465 | 0.0844 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1128 | 10.0 | 3850 | 0.1497 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1151 | 11.0 | 4235 | 0.1024 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1112 | 12.0 | 4620 | 0.0869 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1093 | 13.0 | 5005 | 0.0940 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1102 | 14.0 | 5390 | 0.0914 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1111 | 15.0 | 5775 | 0.1047 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1087 | 16.0 | 6160 | 0.1104 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1105 | 17.0 | 6545 | 0.0970 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1083 | 18.0 | 6930 | 0.0868 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1077 | 19.0 | 7315 | 0.1121 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1115 | 20.0 | 7700 | 0.2092 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1102 | 21.0 | 8085 | 0.0850 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1077 | 22.0 | 8470 | 0.1011 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1111 | 23.0 | 8855 | 0.1136 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1099 | 24.0 | 9240 | 0.1001 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1086 | 25.0 | 9625 | 0.0997 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1066 | 25.97 | 10000 | 0.0827 | 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
- Task
- Image Segmentation
- Library
- transformers
- Type
- mobilenet_v2
- License
- other
- Created
- Apr 8, 2023
- Updated
- Apr 8, 2023