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81 lines
2.6 KiB
Markdown
81 lines
2.6 KiB
Markdown
---
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title: Sevval Bulburu
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published: true
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taxonomy:
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category: [iaeste2023]
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tag: [hatespeech,nlp]
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author: Daniel Hladek
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---
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Sevval Bulburu
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IAESTE Intern Summer 2023, two months
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Goal: Help with the [Hate Speech Project](/topics/hatespeech)
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Final Meeting 12.10.2023
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State:
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- Proposed extra layer above BERT model to make a classifier.
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Tasks:
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- Please send me your work report.
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- Please upload your scripts and notebooks on git and send me a link. git is git.kemt.fei.tuke.sk or github.
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- Prepare some short comment about scripts.
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- You can also upload the slovak dataset - there is some work done on it.
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Meeting 5.9.2023
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State:
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- Proposed own Flask application
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- Created Django application with data model https://github.com/hladek/hate-annot
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Tasks:
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Meeting 22.8.2023
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State:
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- Familiar with Python, Anaconda, Tensorflow, AI projects
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- created account at idoc.fei.tuke.sk and installed anaconda.
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- Continue with previous open tasks.
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- Read a website and pick a dataset from https://hatespeechdata.com/
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- Evaluate (calculate p r f1) existing multilingual model. E.G. https://huggingface.co/Andrazp/multilingual-hate-speech-robacofi with any data
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- Get familiar with Django.
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Notes:
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- ssh bulbur@idoc.fei.tuke.sk
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- nvidia-smi command to check status of GPU.
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- 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.
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- Use WSL2 to have local linux just to play.
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Tasks:
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- [ ] 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.
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- [ ] 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.
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- [x] get familiar with Prodi.gy annotation tool.
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- [-] Set up web-based annotation environment for students (open, cooperation with [Vladimir Ferko](/students/2021/vladimir_ferko) ).
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Ideas for annotation tools:
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- https://github.com/UniversalDataTool/universal-data-tool
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- https://www.johnsnowlabs.com/top-6-text-annotation-tools/
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- https://app.labelbox.com/
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- https://github.com/recogito/recogito-js
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- https://github.com/topics/text-annotation?l=javascript
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Future tasks (to be decided):
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- Translate existing English dataset into Slovak. Use OPUS English Slovak Marian NMT model. Train Slovak munolingual model.
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- Prepare existing Slovak Twitter dataaset, train evaluate a model.
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