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Kaggle新赛(baseline)-基于BERT的fine-tuning方案+基于tensor2tensor的Transformer Encoder方案

Shell 3.96% Python 96.04%

kaggle-quora-insincere-questions-classification's Introduction

Kaggle-Quora-Insincere-Questions-Classification

Kaggle新赛-基于BERT的fine-tuning方案baseline

submit.csv是测试集的预测结果

代码和项目基于BERT的中文tagging一样,仅提供关键fine-tuning代码和运行脚本

基于bert的验证集的结果:

class precision recall f1-score
0 0.98 0.98 0.98
1 0.65 0.62 0.63
micro avg 0.96 0.96 0.96
macro avg 0.81 0.80 0.81
weighted avg 0.96 0.96 0.96

基于tensor2tensor的验证集结果:

class precision recall f1-score
0 0.98 0.96 0.96
1 0.23 0.19 0.21
micro avg 0.92 0.92 0.92
macro avg 0.59 0.57 0.58
weighted avg 0.91 0.92 0.91

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