3.1 KiB
| title | published | taxonomy | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Sevval Bulburu | true |
|
Sevval Bulburu
IAESTE Intern Summer 2023, two months
Goal: Help with the Hate Speech Project
Final Meeting 12.10.2023
State:
- Proposed and tried extra layers above BERT model to make a classifier in seriees of experiments. There is a single sigmoid neuron on the output.
- Manually adjusted the slovak HS dataset. Slovak dataset is not balanced. Tried some methods for "balancing" the dataset. By google translate - augmentation. Other samples are "generated" by translation into random langauge and translating back. This creates "paraphrases" of the original samples. It helps.
- Tried SMOTE upsampling, it did not work.
- Is date and user name an important feature?
Tasks:
- Please send me your work report.
- Please upload your scripts and notebooks on git and send me a link. git is git.kemt.fei.tuke.sk or github.
- Prepare some short comment about scripts.
- You can also upload the slovak dataset - there is some work done on it.
Meeting 5.9.2023
State:
- Proposed own Flask application
- Created Django application with data model https://github.com/hladek/hate-annot
Tasks:
Meeting 22.8.2023
State:
- Familiar with Python, Anaconda, Tensorflow, AI projects
- created account at idoc.fei.tuke.sk and installed anaconda.
- Continue with previous open tasks.
- Read a website and pick a dataset from https://hatespeechdata.com/
- Evaluate (calculate p r f1) existing multilingual model. E.G. https://huggingface.co/Andrazp/multilingual-hate-speech-robacofi with any data
- Get familiar with Django.
Notes:
- ssh bulbur@idoc.fei.tuke.sk
- nvidia-smi command to check status of GPU.
- Use WinSCP to Copy Files. Use anaconda virtual env to create and activate a new python virtual environment. Use Visual Studio Code Remote to delvelop on your computer and run on remote computer (idoc.fei.tuke.sk). Use the same credentials for idoc server.
- Use WSL2 to have local linux just to play.
Tasks:
-
Get familiar with the task of Hate speech detection. Find out how can we use Transformer neural networks to detect and categorize hate speech in internet comments created by random people.
-
Get familiar with the basic tools: Huggingface Transformers, Learn how to use https://huggingface.co/Andrazp/multilingual-hate-speech-robacofi in Python script. Learn something about Transformer neural networks.
-
get familiar with Prodi.gy annotation tool.
-
[-] Set up web-based annotation environment for students (open, cooperation with Vladimir Ferko ).
Ideas for annotation tools:
- https://github.com/UniversalDataTool/universal-data-tool
- https://www.johnsnowlabs.com/top-6-text-annotation-tools/
- https://app.labelbox.com/
- https://github.com/recogito/recogito-js
- https://github.com/topics/text-annotation?l=javascript
Future tasks (to be decided):
- Translate existing English dataset into Slovak. Use OPUS English Slovak Marian NMT model. Train Slovak munolingual model.
- Prepare existing Slovak Twitter dataaset, train evaluate a model.