Andrew Ding posted an update — Dec 06, 2021 11:42 PM EST

Devpost 2: Team Salad Party

Introduction:

Cooking is hard work. Creating new recipes is even harder. A good dish combines the contrast of different tastes, textures, and colors. We hope to learn some interesting relationships between ingredients and the subtlety and structure of recipes using a deep learning model. By parsing and training on thousands upon thousands of recipes, we hope to eventually be able to generate a novel recipe of our own.

Challenges:

We wanted the model to be versatile so we chose a character based tokenizer instead of word based. However, it gave out very random characters for the title like “ujd$’2_%T5’8DAøs|Q‭unded strawberries” and “Ajy%3î••qpppllypook”. It has been really hard to overcome this, even after a lot of hyper parameter tuning. Another challenge was (and still is) to have the model come up with ‘high serendipity’ recipes. It’s nice and all that the model churns out recipes that make sense, but we want it to produce something that has never been seen before and also tastes good. We tried various things to achieve this: fusion recipes, character based tokenizer, using different recipe sources but our main focus has obviously been to have it churn out legible english. Insights: Are there any concrete results you can show at this point? As I mentioned earlier, we do have the character based model working but it’s outputting random characters in the title. Here is a sample output

Title: ujd$'2_%T5'8DAøs|Q‭unded strawberries
    Ingredients:
    1/4 cup blad puree, vinegar
      Salt and pepper to taste
Instructions: 
      Preheat oven to 400 degrees F0 to 10 minutes or until inoprediated and cooked through, are a little about 1 atchotuth. 
      Let stand ubte-remove excest foil. Then slice the should mixer until frag and hust as neel yenuper. Add the onions, garlic, and cool.
      Add the pecoass and vanilla ex cool off thyme begins to simmering craacher.
      Put the paumation in a packs in a bowl, combine the pastry for 1 minute. Scatting freeze rush of the sausage on top of the filling up simonid. Between the spoon mixture in the eggplant spreading it half with a lit (roaster Salt.) Turn ail inut sandwich and surranach with the same meal.;

Plan:

We definitely did not expect to have it work the first time, but we did expect it to output legible english. We now need to rethink the project a little bit and switch to a word based model. The downside to this is that if the user inputs an ingredient (word) that the model has not seen before, it wouldn’t work, so it is limiting in a sense. But at the same time, a good, large dataset should cover a solid amount of ingredients and not leave much behind.

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