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📊 Lovely to share the unique reasoning capabilities 🧠 findings of Qwen2-7B 🇨🇳 in Target Sentiment Analysis (TSA) for original texts (🇷🇺) and their translated version in English (🇺🇸), in zero-shot-learning mode.
📊 Lovely to share the unique reasoning capabilities 🧠 findings of Qwen2-7B 🇨🇳 in Target Sentiment Analysis (TSA) for original texts (🇷🇺) and their translated version in English (🇺🇸), in zero-shot-learning mode.
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Since the last update on 1.5, I have to say:
Since the last update on 1.5, I have to say:
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☑️ 1.  Qwen2-7B is the first model in my list that reasons 🔥 better 🔥 in Russian rather than in English; it strongly surpasses other 7B LLMs and LLaMA3-70B by correctly distributing sentiment cases (F1(PN) metric).
☑️ 1.  Qwen2-7B is the first model in my list that reasons 🔥 better 🔥 in Russian rather than in English; it strongly surpasses other 7B LLMs and LLaMA3-70B by correctly distributing sentiment cases (F1(PN) metric).
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☑️ 2. Surprisingly, but Qwen2-7B significantly underperformed to the "earlier bro" Qwen1.5-7B on texts in English. The key problem is that ~17% of answers has mixed entries of labels, so for such cases the automatic and accurate assessment is difficult. Therefore, I believe it is more about particular evaluation, rather something wrong with the model in TSA domain.
☑️ 2. Surprisingly, but Qwen2-7B significantly underperformed to the "earlier bro" Qwen1.5-7B on texts in English. The key problem is that ~17% of answers has mixed entries of labels, so for such cases the automatic and accurate assessment is difficult. Therefore, I believe it is more about particular evaluation, rather something wrong with the model in TSA domain.
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What's next? I have to checkout 
What's next? I have to checkout 
resource
https://huggingface.co/Qwen/Qwen2-72B-Instruct
model
Qwen/Qwen2-72B-Instruct
https://huggingface.co/Qwen/Qwen2-72B-Instruct
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 then 🧪 If you know the best hosting for infering, please let me know 🙏
 then 🧪 If you know the best hosting for infering, please let me know 🙏
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Model: 
Model: 
resource
https://huggingface.co/Qwen/Qwen1.5-7B-Chat
model
Qwen/Qwen1.5-7B-Chat
https://huggingface.co/Qwen/Qwen1.5-7B-Chat
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📊 Lovely to share the unique reasoning capabilities 🧠 findings of Qwen2-7B 🇨🇳 in Target Sentiment Analysis (TSA) for original texts (🇷🇺) and their translated version in English (🇺🇸), in zero-shot-learning mode.
Since the last update on 1.5, I have to say:
☑️ 1.  Qwen2-7B is the first model in my list that reasons 🔥 better 🔥 in Russian rather than in English; it strongly surpasses other 7B LLMs and LLaMA3-70B by correctly distributing sentiment cases (F1(PN) metric).
☑️ 2. Surprisingly, but Qwen2-7B significantly underperformed to the "earlier bro" Qwen1.5-7B on texts in English. The key problem is that ~17% of answers has mixed entries of labels, so for such cases the automatic and accurate assessment is difficult. Therefore, I believe it is more about particular evaluation, rather something wrong with the model in TSA domain.

What's next? I have to checkout https://huggingface.co/Qwen/Qwen2-72B-Instruct then 🧪 If you know the best hosting for infering, please let me know 🙏

Model: https://huggingface.co/Qwen/Qwen1.5-7B-Chat
