Summary of Bielik 7b V0.1: a Polish Language Model — Development, Insights, and Evaluation, by Krzysztof Ociepa et al.
Bielik 7B v0.1: A Polish Language Model – Development, Insights, and Evaluation
by Krzysztof Ociepa, Łukasz Flis, Krzysztof Wróbel, Adrian Gwoździej, Remigiusz Kinas
First submitted to arxiv on: 24 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The Bielik 7B v0.1 generative text model is introduced as a significant advancement in Polish language processing. This 7-billion-parameter model is trained on curated Polish corpora using innovative techniques such as Weighted Instruction Cross-Entropy Loss and Adaptive Learning Rate. To evaluate its performance, the Open PL LLM Leaderboard and Polish MT-Bench frameworks are created, assessing various NLP tasks and conversational abilities. The Bielik 7B v0.1 model demonstrates a 9 percentage point increase in average score compared to Mistral-7B-v0.1 on the RAG Reader task, as well as excellence in the Reasoning (6.15/10) and Role-playing (7.83/10) categories of Polish MT-Bench. This breakthrough represents a powerful tool for diverse linguistic applications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The Bielik 7B v0.1 is a new text model that can understand and generate text in the Polish language. It’s like a super smart AI that can learn from lots of information, and then use that knowledge to do things like translate text or have conversations. The model uses special techniques to make it better at learning, and it does very well on tests of its abilities. |
Keywords
» Artificial intelligence » Cross entropy » Nlp » Rag
