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How to train our own models in sentimental analysis
python -m stanza.utils.datasets.prepare_${module}_treebank ${corpus} ${other_args} what we have to pass in module,corpus,other_args
C:\Users\Kalpataru\Desktop\stanza-main\stanza\utils\datasets\ner>python -m stanza.utils.datasets.ner.prepare_ner_dataset fi_turku
FileNotFoundError: Cannot find train component of fi_turku in extern_data/ner\fi_turku\train.tsv
I want to train models as per our every time updated data
Have you downloaded the data? If so, where did you put it?
In general, please include the entire stack trace when making an issue.
On Tue, Jun 7, 2022 at 11:11 AM kalpa277 @.***> wrote:
python -m stanza.utils.datasets.prepare_${module}_treebank ${corpus} ${other_args} what we have to pass in module,corpus,other_args
C:\Users\Kalpataru\Desktop\stanza-main\stanza\utils\datasets\ner>python -m stanza.utils.datasets.ner.prepare_ner_dataset fi_turku
FileNotFoundError: Cannot find train component of fi_turku in extern_data/ner\fi_turku\train.tsv
I want to train models as per our every time updated data
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Yes I have downloaded the data.I am not aware about how to put it can you share some blog or tutorial that will help me to figure it out how to train our own model.
I have downloaded https://github.com/stanfordnlp/stanza.
You're already looking through the page on how to retrain models, it seems. However, the error message is pretty much telling you where it's looking for the data.
You can change the root directory for where to put the fi_turku data by setting NERBASE as an environment variable. There is a bit of description on the environment variables here:
https://stanfordnlp.github.io/stanza/training.html#setting-environment-variables
I will add a bit more to it about Windows in a moment.
I added some more doc - lmk if it helps
also here
https://stanfordnlp.github.io/stanza/training.html#ner-data
and the title of the thread is "sentiment", but you're asking about NER. which are you more interested in?
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For the record:
https://stanfordnlp.github.io/stanza/new_language_sentiment.html
https://stanfordnlp.github.io/stanza/new_language_ner.html