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license: mit
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This model is finetuned from HuggingFaceH4/zephyr-7b-gemma-v0.1 and is finetuned on 8 Indian languages.
To improve the resoning and maths skills, we first SFT tune the gemma on Microsoft's Orca datasets.

We utilize Orca maths Hindi dataset: GenVRadmin/Aryabhatta-Orca-Maths-Hindi
And original Orca maths dataset: microsoft/orca-math-word-problems-200k

This pushes the MATHS score from 24.3 in Gemma-7B to 25.5 in Zephyr-Gemma and 31.6 in GemmaOrca.

The model is then finetuned on GenVR's Samvaad datasets (GenVRadmin/Samvaad-Indic-Positive and GenVRadmin/Samvaad-Tamil-Mixtral and a subset of GenVRadmin/Samvaad-Mixed-Language-3).

This is then finetuned on various open sourced datasets like:

Telugu-LLM-Labs/yahma_alpaca_cleaned_telugu_filtered_and_romanized, Telugu-LLM-Labs/teknium_GPTeacher_general_instruct_telugu_filtered_and_romanized
abhinand/tamil-alpaca
Tensoic/airoboros-3.2_kn, Tensoic/gpt-teacher_kn
Tensoic/Alpaca-Gujarati
Open-Orca/OpenOrca
pankajmathur/alpaca_orca

The model achieves following scores on benchmarks:

Model	AGIEval	GPT4All	TruthfulQA	BigBench	Average ⬇️
AryaBhatta-GemmaOrca  39.9   74.26   58.85   43.35   54.09
zephyr-7b-beta	37.52	71.77	55.26	39.77	51.08
zephyr-7b-gemma-v0.1	34.22	66.37	52.19	37.10	47.47
mlabonne/Gemmalpaca-7B	21.6	40.87	44.85	30.49	34.45
google/gemma-7b-it	21.33	40.84	41.70	30.25	33.53