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📢 I've tested google/Gemma-2-9b-it in Target Sentiment Analysis (TSA), in zero-shot learning mode on RuSentNE-2023 dataset with texts translated into English (🇺🇸).
🔎 Findings: The key contribution with the most recent Gemma-2 release is reasoning alignment between different langauges. This is basically the first model under 10B category which shows equal results in English and non-english texts. In the case of texts in English it performs similar to LLaMa-3-8B / Mistal-7B
Model: google/gemma-2-9b-it
Benchmark: https://github.com/nicolay-r/RuSentNE-LLM-Benchmark
🔎 Findings: The key contribution with the most recent Gemma-2 release is reasoning alignment between different langauges. This is basically the first model under 10B category which shows equal results in English and non-english texts. In the case of texts in English it performs similar to LLaMa-3-8B / Mistal-7B
Model: google/gemma-2-9b-it
Benchmark: https://github.com/nicolay-r/RuSentNE-LLM-Benchmark
