Data Skeptic

The Limits of NLP

Dec 24, 2019

29:47

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Episode notes

The Perimeter Flop Trade-Off Between DeCoter and Incoecoter Language Models

02:21

Using Attention Masks in a Language Model

01:34

A Regression Task or Predict a Probability?

01:52

Introduction

2min

A Regression Task or Predict a Probability?

2min

The Limits of Text to Text Transformations

2min

Scaling Is Not the Most Satisfying Solution

2min

The in Coder Only Architecture in Transfer Learning for Natural Language Processing

3min

Give Well - Give Well Data Sceptic

4min

Transfer Learning for Text - Can You Get Natural Text Out of Common Crawl?

2min

Using Loss Functions in Machine Learning Models

3min

Using Attention Masks in a Language Model

2min

10.

The Perimeter Flop Trade-Off Between DeCoter and Incoecoter Language Models

2min

11.

Transfer Learning

2min

12.

Using a Colap Note Book to Find Tune a Text Model

2min

13.

Can We Just Keep Putting in Bigger Data Sets and See Better Performance?

3min

We are joined by Colin Raffel to discuss the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer".

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Data Skeptic

The Limits of NLP

The Perimeter Flop Trade-Off Between DeCoter and Incoecoter Language Models

Using Attention Masks in a Language Model

A Regression Task or Predict a Probability?

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Save anymoment

Share& Export

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