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mobilenet_v2_1-10k-steps

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+ ---
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+ license: other
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+ tags:
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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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+
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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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+
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+ # mobilenet_v2_1-10k-steps
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+
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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 None 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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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