manishiitg
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Update README.md
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README.md
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results: []
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---
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DHARMA TINY EVAL
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============
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@@ -27,8 +79,6 @@ DHARMA TINY EVAL
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| OpenHathi-7B-Hi-v0.1-Base | 0.2862 | 0.3333 | 0.5130 | 0.6077 | 0.4907 | 0.2301 | 0.3017 | 0.2677 | 0.1933 |
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| Airavata | 0.2751 | 0.1274 | 0.2268 | 0.0615 | 0.3866 | 0.1104 | 0.2845 | 0.1450 | 0.3383 |
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| gemma-7b-it | 0.1227 | 0.0786 | 0.0743 | 0.1808 | 0.1561 | 0.0491 | 0.1078 | 0.0818 | 0.0855 |
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| Qwen1.5-72B-Chat-AWQ | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
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| Qwen1.5-7B-Chat | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
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#### Language En
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| open-aditi-hi-v1 | 0.8104 | 0.3902 | 0.2491 | 0.6962 | 0.5539 | 0.3681 | 0.6379 | 0.5056 | 0.5911 |
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| Airavata | 0.7026 | 0.4282 | 0.3123 | 0.7192 | 0.5651 | 0.3313 | 0.5172 | 0.3792 | 0.5093 |
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| OpenHathi-7B-Hi-v0.1-Base | 0.4684 | 0.3062 | 0.4758 | 0.6346 | 0.5167 | 0.2577 | 0.3017 | 0.2788 | 0.2714 |
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Task: BoolQ Metric: score
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results: []
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---
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Preview of dataset trained on: https://huggingface.co/datasets/manishiitg/aditi-syn-v2
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The synthetic dataset (https://huggingface.co/datasets/manishiitg/aditi-syn-v2) and the full data creation pipeline (https://github.com/manishiitg/aditi_dataset) have been open-sourced, enabling transparency and fostering further research in this domain. The dataset is a rich tapestry of Hinglish (a blend of Hindi and English) data, as well as a diverse array of tasks spanning tools, retrieval-augmented generation (RAG), mathematics, and reasoning – all in the Hindi language.
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LMJudge Eval
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============
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https://github.com/manishiitg/IndicLMJudge
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#### LLM Judge Language: hi
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| Model | Language | Score | No# Questions |
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| --- | --- | --- | --- |
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| mistralai/Mixtral-8x7B-Instruct-v0.1 | hi | 8.7148 | 554 |
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| Qwen/Qwen1.5-72B-Chat-AWQ | hi | 8.3695 | 554 |
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| manishiitg/open-aditi-v6-llama3 | hi | 8.2659 | 551 |
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| Qwen/Qwen1.5-14B-Chat | hi | 8.2404 | 554 |
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| google/gemma-7b-it | hi | 7.9152 | 554 |
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| manishiitg/open-aditi-v6-gemma | hi | 7.8634 | 549 |
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| Qwen/Qwen1.5-7B-Chat | hi | 7.8587 | 554 |
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| manishiitg/open-aditi-hi-v3 | hi | 7.7644 | 554 |
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| manishiitg/open-aditi-hi-v4 | hi | 7.6150 | 554 |
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| manishiitg/open-aditi-hi-v2 | hi | 7.2518 | 554 |
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| teknium/OpenHermes-2.5-Mistral-7B | hi | 7.2489 | 554 |
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| ai4bharat/Airavata | hi | 6.9468 | 554 |
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| 01-ai/Yi-34B-Chat | hi | 6.5801 | 554 |
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| manishiitg/open-aditi-hi-v1 | hi | 4.7022 | 554 |
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| sarvamai/OpenHathi-7B-Hi-v0.1-Base | hi | 4.2834 | 598 |
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| Qwen/Qwen1.5-4B-Chat | hi | 4.1101 | 554 |
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#### LLM Judge Language: en
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| Model | Language | Score | No# Questions |
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| Qwen/Qwen1.5-14B-Chat | en | 9.1947 | 356 |
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| Qwen/Qwen1.5-72B-Chat-AWQ | en | 9.1618 | 356 |
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| Qwen/Qwen1.5-7B-Chat | en | 9.1570 | 356 |
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| 01-ai/Yi-34B-Chat | en | 9.1368 | 356 |
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| mistralai/Mixtral-8x7B-Instruct-v0.1 | en | 9.1306 | 356 |
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| manishiitg/open-aditi-v6-gemma | en | 9.1003 | 356 |
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| teknium/OpenHermes-2.5-Mistral-7B | en | 9.0230 | 356 |
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| manishiitg/open-aditi-v6-llama3 | en | 9.0197 | 356 |
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| manishiitg/open-aditi-hi-v3 | en | 8.9615 | 356 |
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| manishiitg/open-aditi-hi-v4 | en | 8.9188 | 356 |
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| google/gemma-7b-it | en | 8.8191 | 356 |
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| Qwen/Qwen1.5-4B-Chat | en | 8.7500 | 356 |
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| google/gemma-2b-it | en | 8.4671 | 356 |
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| manishiitg/open-aditi-hi-v2 | en | 8.4584 | 356 |
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| ai4bharat/Airavata | en | 7.3834 | 356 |
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| manishiitg/open-aditi-hi-v1 | en | 6.6559 | 356 |
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| sarvamai/OpenHathi-7B-Hi-v0.1-Base | en | 5.9567 | 312 |
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DHARMA TINY EVAL
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============
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| OpenHathi-7B-Hi-v0.1-Base | 0.2862 | 0.3333 | 0.5130 | 0.6077 | 0.4907 | 0.2301 | 0.3017 | 0.2677 | 0.1933 |
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| Airavata | 0.2751 | 0.1274 | 0.2268 | 0.0615 | 0.3866 | 0.1104 | 0.2845 | 0.1450 | 0.3383 |
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| gemma-7b-it | 0.1227 | 0.0786 | 0.0743 | 0.1808 | 0.1561 | 0.0491 | 0.1078 | 0.0818 | 0.0855 |
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#### Language En
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| open-aditi-hi-v1 | 0.8104 | 0.3902 | 0.2491 | 0.6962 | 0.5539 | 0.3681 | 0.6379 | 0.5056 | 0.5911 |
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| Airavata | 0.7026 | 0.4282 | 0.3123 | 0.7192 | 0.5651 | 0.3313 | 0.5172 | 0.3792 | 0.5093 |
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| OpenHathi-7B-Hi-v0.1-Base | 0.4684 | 0.3062 | 0.4758 | 0.6346 | 0.5167 | 0.2577 | 0.3017 | 0.2788 | 0.2714 |
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Task: BoolQ Metric: score
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