Hey, Recently the folks at PolyAI have open-sourced a new sentence encoding model called ConveRT which is pretrained on a large conversational dataset and hence claims better conversational representations over traditional large language models like BERT, etc. The idea resonates very well with what we also believe and have been working on internally at Rasa. Since they open sourced their model as a TFHub model , we decided to build a quick featurizer based on this to extract representations and use them with downstream intent classification models already existing inside Rasa. In our internal tests, the model does give a significant boost to intent classification accuracy on multiple datasets. We would love the community to try it out and share evaluation numbers on their test sets. We have released the featurizer as part of Rasa 1.5.0. You can try by doing a pip install of Rasa- pip install rasa==1.5.0 The featurizer uses an optional dependency tensorflow_text. Install it with - pip install --no-deps tensorflow_text==1.15.1 Now you are ready to use the ConveRTFeaturizer . In the project directory, we recommend using a config along these lines - language: en pipeline: - name: WhitespaceTokenizer - name: ConveRTFeaturizer - name: EmbeddingIntentClassifier This uses the ConveRT model as a feature extractor alone and we do not fine tune it along with our intent classifier. Please note that this model can only be used for a dataset in english language. Feel free to change the config params of EmbeddingIntentClassifier according to your dataset. It would be great if you can share the numbers for evaluation metrics on your test dataset here.

If that does not work, I can offer you connecting to your system to investigate the issue. We would do that via ngrok - if you want to.

Hi, okay. Open a terminal and enter: ngrok tcp 22 You will see something like: ngrok by @inconshreveable (Ctrl+C to quit) Tunnel Status online Version 2.0.19/2.0.17 Web Interface [http://127.0.0.1:4040](http://127.0.0.1:4040/) Forwarding tcp://0.tcp.ngrok.io:36428 -> localhost:22 Connections ttl opn rt1 rt5 p50 p90 0 0 0.00 0.00 0.00 0.00 I need the address after “Forwarding …” such that I can connect. Regards

Oh I forgot something. Please make sure that sshd runs: How to enable SSH on Ubuntu Regards

@arbazkhan971 Upgrade your pip version by using pip install --upgrade pip

i tried this too but still facing same issue

@arbazkhan971 Share your VM detail and cloud provider name. Before upgrading pip, please run sudo apt-get update if you are using ubuntu

Account (Plan: Free) Version 2.3.35 Region United States (us) Web Interface http://127.0.0.1:4040 Forwarding http://86ce8c8d.ngrok.io -> http://localhost:80 Forwarding https://86ce8c8d.ngrok.io -> http://localhost:80 Connections ttl opn rt1 rt5 p50 p90 0 0 0.00 0.00 0.00 0.00

Feedback on ConveRT Model + Rasa NLU

Rasa Open Source

shubham3582 (Shubham Srivastava) December 1, 2019, 5:54pm 39

@arbazkhan971 Please share which cloud VM you are using, also python version, pip version. I believe your pip version is older, please upgrade it to v19+.

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Feedback on ConveRT Model + Rasa NLU

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