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- `landscape`: https://huggingface.co/datasets/3ee/regularization-landscape
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## π Training Stats
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π GPU: `Nvidia 3080 16GB`
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π¬ Learning Rate: `1e-6` & Training steps per image: `96` (`13400` total)
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π¬ Text Encoder Training: `0.2`
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π¨ Total input images per concept: `14` (total = `14 * 4 = 56`)
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β cups of coffee consumed: `21`
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- I spent a lot of time experimenting and fine tuning. I started with `25` steps per image at first and went on from there.
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- I went as high as `176` steps per image and attempted many different `batch sizes` with `Gradient Accumulation`. The results were different (but really good!) than what I had planned for this model which is: capture the style of SPOP. I plan to use the knowledge I gained from those "failed" models to great use on future ones!
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- In conclusion, the `13400` version came out to be the version that captured the Dreamworks style.
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- `landscape`: https://huggingface.co/datasets/3ee/regularization-landscape
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