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--- |
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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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- accuracy |
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model-index: |
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- name: day-night |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9965357967667436 |
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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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# 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: 0.0117 |
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- Accuracy: 0.9965 |
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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: 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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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.0899 | 0.6 | 200 | 0.0934 | 0.9711 | |
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| 0.026 | 1.19 | 400 | 0.0225 | 0.9942 | |
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| 0.0689 | 1.79 | 600 | 1.5236 | 0.7032 | |
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| 0.0193 | 2.38 | 800 | 0.0117 | 0.9965 | |
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| 0.028 | 2.98 | 1000 | 0.0186 | 0.9919 | |
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| 0.0159 | 3.57 | 1200 | 0.0150 | 0.9954 | |
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| 0.0194 | 4.17 | 1400 | 0.0369 | 0.9919 | |
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| 0.0081 | 4.76 | 1600 | 0.0471 | 0.9850 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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