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- Dataset: I'm using the `cats_vs_dogs` dataset from **kaggle** instead of huggingface `datasets` since `cats_vs_dogs` in `datasets` have checksum error. The original dataset is from Microsoft. However, some files are corrupted and it hasn't been divided into `train` and `test` folders.
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- Model: I'm using `ResNet50` with `pretrained=True` from `pytorch`. The choice of optimizer is `Adam` with `lr=1e-4`. I had tried `AdamW` before coming back to `Adam`. I also added the `lr_scheduler` to reconfigure the learning rate.
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- Number of epochs: I'm using 10 epochs in total. I had tried with 20, however, only the `train_acc` increases by ~1%, so it does not worth trying for an increasing amount of training time.
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- Dataset: I'm using the `cats_vs_dogs` dataset from **kaggle** instead of huggingface `datasets` since `cats_vs_dogs` in `datasets` have checksum error. The original dataset is from Microsoft. However, some files are corrupted and it hasn't been divided into `train` and `test` folders.
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- Model: I'm using `ResNet50` with `pretrained=True` from `pytorch`. The choice of optimizer is `Adam` with `lr=1e-4`. I had tried `AdamW` before coming back to `Adam`. I also added the `lr_scheduler` to reconfigure the learning rate.
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- Number of epochs: I'm using 10 epochs in total. I had tried with 20, however, only the `train_acc` increases by ~1%, so it does not worth trying for an increasing amount of training time.
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1FgVFvmjFn-tGk1pzVUTfra6UyafcuPLV?usp=sharing]
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