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--- |
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license: other |
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tags: |
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- image-segmentation |
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- vision |
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- generated_from_trainer |
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model-index: |
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- name: mobilenet_v2_1-10k-steps |
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results: [] |
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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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# mobilenet_v2_1-10k-steps |
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This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the Efferbach/lane_master2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0827 |
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- Mean Iou: 0.0 |
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- Mean Accuracy: 0.0 |
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- Overall Accuracy: 0.0 |
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- Accuracy Background: nan |
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- Accuracy Left: 0.0 |
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- Accuracy Right: 0.0 |
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- Iou Background: 0.0 |
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- Iou Left: 0.0 |
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- Iou Right: 0.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 1337 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- training_steps: 10000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Left | Accuracy Right | Iou Background | Iou Left | Iou Right | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:--------------:|:--------------:|:--------:|:---------:| |
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| 0.3253 | 1.0 | 385 | 0.0989 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.128 | 2.0 | 770 | 0.1518 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1212 | 3.0 | 1155 | 0.1852 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.117 | 4.0 | 1540 | 0.1446 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1148 | 5.0 | 1925 | 0.1087 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1167 | 6.0 | 2310 | 0.1502 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1128 | 7.0 | 2695 | 0.0882 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1156 | 8.0 | 3080 | 0.1005 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1164 | 9.0 | 3465 | 0.0844 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1128 | 10.0 | 3850 | 0.1497 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1151 | 11.0 | 4235 | 0.1024 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1112 | 12.0 | 4620 | 0.0869 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1093 | 13.0 | 5005 | 0.0940 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1102 | 14.0 | 5390 | 0.0914 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1111 | 15.0 | 5775 | 0.1047 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1087 | 16.0 | 6160 | 0.1104 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1105 | 17.0 | 6545 | 0.0970 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1083 | 18.0 | 6930 | 0.0868 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1077 | 19.0 | 7315 | 0.1121 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1115 | 20.0 | 7700 | 0.2092 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1102 | 21.0 | 8085 | 0.0850 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1077 | 22.0 | 8470 | 0.1011 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1111 | 23.0 | 8855 | 0.1136 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1099 | 24.0 | 9240 | 0.1001 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1086 | 25.0 | 9625 | 0.0997 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1066 | 25.97 | 10000 | 0.0827 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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