A Seq-to-Seq Transformer Premised Temporal Convolutional Network for Chinese Word Segmentation
Table 3: Performance comparison of the models. Size means the number of parameters of the models. Speed is the training speed of models and its unit of measurement is sentences/s meaning that how many sentences are processed per second.
['[BOLD] Model', '[BOLD] F', '[BOLD] Size', '[BOLD] Speed']
We select the Bi-LSTM-with-CRF and the Tcn-no-CRF as the baseline models, and experiment these models on NLPCC2016 dataset, and show the performance comparison between our model with the models on the test set. The training speed is an important performance to evaluate the power of parallel computing in identical hardware and software environment. Meanwhile, if a product based on the algorithm of deep-learning is trained more quickly, the product is released more early before the other similar product.