使用Python API的快速文本无监督模型丢失 [英] Fast Text unsupervised model loss with Python API

问题描述

在使用Python API和Fast Text进行模型的无监督训练时，有什么方法可以使模型丢失吗?目前，我正在使用C ++模型进行培训，并使用Python API进行加载.

Is there any way to get the model loss for the unsupervised training of models using Fast Text with the python API? At the moment I am doing the training using the C++ model and loading it using the Python API.

例如，我首先运行以下代码来调整超级参数

For e.g., I first run the following code to tweak hyper parameters

./fasttext skipgram \
-input /data/cleaned.txt \
-output /models/cleaned-model \
-epoch 12000 \
-minCount 2 \
-ws 3

命令行界面可以估算出损失，如下所示:

The command-line interface gives an estimate of the loss like so:

Progress: 100.0% words/sec/thread:  103006 lr:  0.000000 loss:  1.803622 ETA:   0h 0m

但是，使用Python API进行相同操作:

However, doing the same using the Python API:

import fastText
model = fastText.train_unsupervised('/data/cleaned.txt', 
                                    epoch=12000, 
                                    minCount=2, 
                                    ws=3)

这是训练但不输出损失吗?我检查了训练功能选项中的详细级别verbosity=3，但没有任何反应.这是缺少的功能还是我缺少的东西?

This trains but does not output the loss? I checked increasing the verbosity level verbosity=3 in the training function options but nothing happens. Is this a missing feature or something I am missing?

推荐答案

如果您从外壳程序运行python脚本，它将打印所需的输出.

If you run the python script from the shell, it prints the desired output.

也许您正在使用Jupyter Notebook.在这种情况下，目前没有一种简单的方法可以在笔记本中查看输出.

Maybe you're using Jupyter Notebook. In this case, currently there's not a simple way to see the output in the notebook.

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