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README.md
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---
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license:
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base_model:
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- name: Accuracy
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type: accuracy
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value:
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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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# day-night
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size:
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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### Framework versions
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license: other
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base_model: google/mobilenet_v2_0.75_160
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tags:
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- image-classification
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9988452655889145
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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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# day-night
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This model is a fine-tuned version of [google/mobilenet_v2_0.75_160](https://huggingface.co/google/mobilenet_v2_0.75_160) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0030
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- Accuracy: 0.9988
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 10
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.1021 | 0.6 | 200 | 0.0679 | 0.9734 |
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| 0.0199 | 1.19 | 400 | 0.0184 | 0.9919 |
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| 0.0723 | 1.79 | 600 | 0.6625 | 0.7852 |
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| 0.0247 | 2.38 | 800 | 0.0030 | 0.9988 |
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| 0.0273 | 2.98 | 1000 | 0.0254 | 0.9885 |
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| 0.012 | 3.57 | 1200 | 0.0177 | 0.9965 |
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| 0.0142 | 4.17 | 1400 | 0.0282 | 0.9908 |
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| 0.009 | 4.76 | 1600 | 0.0189 | 0.9977 |
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### Framework versions
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