There are many reasons behind this.
Kaggle just announced that the 1st Place Team, Bestpetting[1], has been disqualified from the Petfinder.my competition for cheating. One of its important features is being able to encode a continuous sequence like [A, B, C, …, Z] into one vector.Note that in NLP, the whole [A, B, C, …, Z] sequence can be considered to correspond to one sentence, and each alphabet corresponds to each word of a sentence.The Transformer (TR) can be stacked in multiple layers to encode more abstract information. Facebook launched the competition last year to encourage the development of new technologies to detect deepfakes and manipulated media, and there were more than 2,000 entries were submitted. By using Kaggle, you agree to our use of cookies.
Kaggle Winning Solutions Sortable and searchable compilation of solutions to past Kaggle competitions. To prevent cheating, machine learning competitions include data that isn’t labeled and is used in two phases:The result of this competition format is that if a team obtains the ground-truth answers to the private test dataset — it is effectively guaranteed to win. If you would like to dive deep into the different types or formats and datasets offered by Kaggle, take a look at Kaggle's Help and Documentation S: Yeah, I guess so! Most of the scoring errors and peculiarities that made other participants mad in the first 2–3 weeks of the Google QUEST Q&A Labeling competition was easy for us.So, Dmitry, Oleg, and I merged with Dmitriy A., who came up with a powerful technique for language model pretraining with StackExchange data.Oleg started with a simple PyTorch baseline based on one of the public Notebooks (We think competing as a team was the best part of the whole experience and let us win in this competition with quite a good margin.But actually we have three major “secret” ingredients of our solution to share:We used an additional dump of ~7 mln StackExchange questions to fine-tune the BERT language model through a Masked Language Model task (MLM, see the Apart from that, we also built additional auxiliary targets — while fine-tuning LM we also predicted 5 targets (question_score, question_view_count, question_favorite_count, answer_score, answers_count) which we engineered based on StackExchange data.We used a customized extended cased vocabulary for a simple reason: StackExchange questions often contain not just pure spoken language but also math and code. One such method would be to optimize hyperparameters using the full dataset, creating a model that seems as though it’s coincidentally more effective.
On the Kaggle-front, I participated in my first competition in February 2019 and here I am!First, my experience with feature engineering to use tabular data as input to Deep Neural Networks (DNNs) was really helpful.Second, my experience of dealing with Transformer models in the Predicting Molecular Properties competition.Recently, we were inspired by this and were trying to apply the Transformer in other fields.
Kaggle Competitions are designed to provide challenges for competitors at all different stages of their machine learning careers. We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Many teams were applying various thresholding heuristics as post-processing, often for each of 30 target columns separately. The two online platforms — Facebook and Kaggle have recently started facing an online backlash after they disqualified the apparent winners of Facebook’s Deepfake Detection Challenge..
We clearly recognized that as overfitting. So, you became a Grandmaster in about a year’s time? Then an average of 30 Spearman correlation coefficients produces the final metric.The toy example above shows that a vector of predictions b can be “thresholded” to produce b2 and thus increase its Spearman correlation with a (ground truth) from 0.89 to 1.Actually, that was one of drawbacks of the whole competition — the target metric was a bit too sensitive to hacks like thresholding predictions. There is normally a metric associated with the competition and the goal of the competition is to optimize that metric. While Kaggle does have an extremely low barrier of entry (for most of its competitions), winning is an altogether different ordeal.
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