manishiitg/open-aditi-hi-v2

Model trained on Hindi and English data.

Try it out: https://colab.research.google.com/drive/1A_hbsq1vrCeAh3dEMvtwxxNxcNZ1BUyW?usp=sharing

For sample responose on different prompts checkout: https://github.com/manishiitg/hi-llm-eval

Language Hi

Model	implicit_hate	flores	indicwikibio	hellaswag-indic	truthfulqa-hi	boolq-hi	indicheadline	indic-arc-easy	indicqa	indic-arc-challenge	indicsentiment	xlsum-hi	indicxparaphrase	mmlu_hi
open-aditi-hi-v2	11.5021	43.6822	0.4846	0.2404	0.6934	0.8541	0.4565	0.4979	0.0795	0.4462	0.9729	0.4213	0.6838	0.3253
OpenHermes-2.5-Mistral-7B	0.2068	30.3465	0.3332	0.2485	0.3234	0.5979	0.1996	0.3523	0.2721	0.3396	0.9048	0.1774	0.8766	0.2769
open-aditi-hi-v1	8.6105	40.2376	0.4104	0.0848	0.4230	0.3758	0.4248	0.3889	0.1306	0.3558	0.8798	0.4212	0.5939	0.1398
Airavata	0.0663	58.0555	0.0637	0.0254	0.2122	0.0373	0.4346	0.1128	0.1008	0.0836	0.8437	0.4650	0.3277	0.1336

Language En

Model	boolq	hellaswag	mmlu	truthfulqa	xlsum	arc-easy-exact	arc-challenge
OpenHermes-2.5-Mistral-7B	0.4061	0.7999	0.5991	0.2081	0.4328	0.8687	0.7790
open-aditi-hi-v2	0.3982	0.4738	0.5544	0.2999	0.4349	0.8388	0.7235
open-aditi-hi-v1	0.0434	0.3509	0.2597	0.3317	0.4288	0.7588	0.6271
Airavata	0.0437	0.0277	0.1165	0.3586	0.4393	0.2534	0.1630

Task: flores Metric: chrf

Task: implicit_hate Metric: chrf

Task: indicsentiment Metric: accuracy

Task: indicxparaphrase Metric: accuracy

Task: boolq-hi Metric: accuracy

Task: truthfulqa-hi Metric: accuracy

Task: indic-arc-easy Metric: accuracy

Task: indicwikibio Metric: bleurt

Task: xlsum-hi Metric: bleurt

Task: indicheadline Metric: bleurt

Task: indic-arc-challenge Metric: accuracy

Task: mmlu_hi Metric: average_acc

Task: indicqa Metric: accuracy

Task: hellaswag-indic Metric: accuracy

Task: arc-easy-exact Metric: accuracy

Task: hellaswag Metric: accuracy

Task: arc-challenge Metric: accuracy

Task: mmlu Metric: average_acc

Task: xlsum Metric: bleurt

Task: boolq Metric: accuracy

Task: truthfulqa Metric: accuracy

Model evaluation on OpenLLM LeaderBoard

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	59.31
AI2 Reasoning Challenge (25-Shot)	59.39
HellaSwag (10-Shot)	82.01
MMLU (5-Shot)	61.41
TruthfulQA (0-shot)	45.84
Winogrande (5-shot)	77.19
GSM8k (5-shot)	30.02