Datasets:
QCRI
/

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Text
Formats:
json
Languages:
Hindi
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pandas
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add results

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@@ -180,6 +180,25 @@ This repo includes scripts needed to run our full pipeline, including data prepr
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  ## File Format
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  Each JSONL file in the dataset follows a structured format with the following fields:
 
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  ---
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+ ## Results
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+ Below, we present the performance of **LlamaLens** in **Hindi** compared to existing SOTA (if available) and the Llama-Instruct baseline, The “Delta” column here is
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+ calculated as **(LLamalens – SOTA)**.
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+ | **Task** | **Dataset** | **Metric** | **SOTA** | **Llama-instruct** | **LLamalens** | **Delta** (LLamalens - SOTA) |
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+ |------------------------|------------------------|-----------:|--------:|--------------------:|--------------:|------------------------------:|
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+ | NLI | NLI_dataset | W-F1 | 0.646 | 0.633 | 0.655 | 0.009 |
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+ | News Summarization | xlsum | R-2 | 0.136 | 0.078 | 0.117 | -0.019 |
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+ | Sentiment | Sentiment Analysis | Acc | 0.697 | 0.552 | 0.669 | -0.028 |
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+ | Factuality | fake-news | Mi-F1 | – | 0.759 | 0.713 | – |
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+ | Hate Speech | hate-speech-detection | Mi-F1 | 0.639 | 0.750 | 0.994 | 0.355 |
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+ | Hate Speech | Hindi-Hostility | W-F1 | 0.841 | 0.469 | 0.720 | -0.121 |
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+ | Offensive | Offensive Speech | Mi-F1 | 0.723 | 0.621 | 0.847 | 0.124 |
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+ | Cyberbullying | MC_Hinglish1 | Acc | 0.609 | 0.233 | 0.587 | -0.022 |
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  ## File Format
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  Each JSONL file in the dataset follows a structured format with the following fields: