manishiitg/open-aditi-hi-v4

Model trained on Hindi and English data.

This model also includes dataset https://huggingface.co/datasets/sarvamai/samvaad-hi-v1

Check latest evals at https://github.com/manishiitg/IndicEval

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	xlsum-hi	truthfulqa-hi	indic-arc-easy	mmlu_hi	indicqa	flores	indicheadline	indicxparaphrase	hellaswag-indic	indicwikibio	boolq-hi	implicit_hate	indic-arc-challenge	indicsentiment
open-aditi-hi-v2	0.4213	0.6934	0.4979	0.3253	0.0795	43.6822	0.4565	0.6838	0.2404	0.4846	0.8541	11.5021	0.4462	0.9729
open-aditi-hi-v3	0.4490	0.5369	0.5480	0.1351	0.0058	48.2859	0.4682	0.8846	0.4891	0.5034	0.5401	8.8315	0.4633	0.9519
open-aditi-hi-v4	0.4046	0.7671	0.4529	0.2124	0.0026	47.8500	0.1980	0.7737	0.3595	0.4894	0.7015	5.9709	0.3857	0.9699
OpenHermes-2.5-Mistral-7B	0.1774	0.3234	0.3523	0.2769	0.2721	30.3465	0.1996	0.8766	0.2485	0.3332	0.5979	0.2068	0.3396	0.9048
OpenHermes-2.5-Mistral-7B-AWQ	0.1894	0.3428	0.3291	0.2750	0.3116	29.3681	0.2062	0.8536	0.2479	0.3067	0.5272	6.0594	0.3157	0.9218
open-aditi-hi-v1	0.4212	0.4230	0.3889	0.1398	0.1306	40.2376	0.4248	0.5939	0.0848	0.4104	0.3758	8.6105	0.3558	0.8798
Airavata	0.4650	0.0466	0.1128	0.1336	0.0155	58.5260	0.4346	0.6419	0.0550	0.0637	0.0128	6.3612	0.0836	0.0992

Language En

Model	boolq	truthfulqa	arc-easy-exact	mmlu	hellaswag	xlsum	arc-challenge
open-aditi-hi-v4	0.3905	0.3378	0.8460	0.5725	0.7603	0.4384	0.7491
OpenHermes-2.5-Mistral-7B	0.4061	0.2081	0.8687	0.5991	0.7999	0.4328	0.7790
OpenHermes-2.5-Mistral-7B-AWQ	0.4199	0.1897	0.8569	0.5816	0.7826	0.4317	0.7611
open-aditi-hi-v3	0.3749	0.3097	0.8384	0.5478	0.7645	0.4352	0.7415
open-aditi-hi-v2	0.3982	0.2999	0.8388	0.5544	0.4738	0.4349	0.7235
open-aditi-hi-v1	0.0434	0.3317	0.7588	0.2597	0.3509	0.4288	0.6271
Airavata	0.5086	0.3574	0.6772	0.1165	0.1799	0.4393	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: hellaswag-indic Metric: accuracy

Task: indicheadline Metric: bleurt

Task: xlsum-hi Metric: bleurt

Task: indic-arc-challenge Metric: accuracy

Task: mmlu_hi Metric: average_acc

Task: indicqa Metric: accuracy

Task: arc-easy-exact Metric: accuracy

Task: hellaswag Metric: accuracy

Task: arc-challenge Metric: accuracy

Task: mmlu Metric: average_acc

Task: boolq Metric: accuracy

Task: xlsum Metric: bleurt

Task: truthfulqa Metric: accuracy

Model evaluation on OpenLLM LeaderBoard

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	64.23
AI2 Reasoning Challenge (25-Shot)	60.15
HellaSwag (10-Shot)	81.84
MMLU (5-Shot)	61.32
TruthfulQA (0-shot)	44.89
Winogrande (5-shot)	79.95
GSM8k (5-shot)	57.24

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	64.23
AI2 Reasoning Challenge (25-Shot)	60.15
HellaSwag (10-Shot)	81.84
MMLU (5-Shot)	61.32
TruthfulQA (0-shot)	44.89
Winogrande (5-shot)	79.95
GSM8k (5-shot)	57.24