Table 8: An overview of the performance of all models finetuned for this work, along with proprietary models, on selected benchmarks. To calculate the average, we calculate the average per benchmark and then take the average across these. See App. F for more details.
MMLU	GSM	BBH	TydiQA	Codex-Eval	AlpacaEval	Average
0-shot	5-shot	Direct	CoT	Direct	CoT	GP	CB	P@1	P@10	v Davinci-003	-
Proprietary models ↓
GPT-4	82.4	83.9	35.0	92.5	50.9	88.0	70.8	27.6	85.7	94.1	93.5	74.8
ChatGPT	67.9	69.9	32.5	76.0	49.0	66.1	51.9	20.0	72.2	88.4	83.6	63.4
LLaMa 65B finetuning experiments ↓
Vanilla LLaMa	58.7	63.3	14.0	50.0	46.2	58.1	56.8	18.1	23.5	46.9	-	-
ShareGPT	61.3	62.8	23.0	59.0	40.0	55.8	31.6	9.8	30.8	56.2	73.6	48.1
Human mix.	60.4	61.4	8.5	60.0	53.1	54.8	58.3	15.9	23.9	44.6	43.4	44.0
H+GPT mix (♂)	59.2	60.8	10.0	59.0	48.4	54.4	56.6	13.3	29.2	49.4	61.8	47.0
LLaMa 30B finetuning experiments ↓
Vanilla LLaMa	54.6	57.9	12.0	36.0	41.4	49.5	55.3	15.8	22.0	42.8	-	-
ShareGPT	54.6	57.5	20.5	47.5	42.2	51.1	34.6	10.7	28.1	49.8	69.1	44.6
Human mix.	56.5	58.8	5.5	52.0	46.8	50.6	57.5	14.5	24.8	41.3	38.3	40.4
H+GPT mix (♀)	57.7	58.4	6.0	53.0	47.1	51.9	51.9	13.0	27.2	48.9	62.3	44.9
LLaMa 13B finetuning experiments ↓
Vanilla LLaMa	42.3	46.4	7.0	14.5	37.1	39.3	43.2	11.5	16.2	28.6	-	-
SuperNI	49.7	50.3	2.5	4.0	9.4	4.5	50.2	9.6	8.2	12.9	4.2	20.0
CoT	44.2	45.2	12.5	40.0	38.7	41.9	47.8	9.1	12.8	23.7	6.0	27.3
Flan V2	50.6	51.2	3.0	20.0	41.7	40.8	47.2	11.4	9.0	16.8	3.2	24.8
Dolly	45.6	45.1	7.0	18.0	32.3	28.4	46.5	11.6	12.9	31.0	13.7	25.5
Open Assistant 1	43.3	36.7	5.0	15.0	35.9	39.6	33.4	10.3	16.1	31.9	58.1	32.0
Self-instruct	30.4	32.1	4.5	11.0	33.2	30.7	41.3	8.5	8.7	12.5	5.0	18.6
Unnat. Instruct.	46.4	45.7	5.5	8.0	37.9	33.7	41.0	8.5	14.4	23.9	8.4	23.5
Alpaca	45.0	46.9	7.0	9.5	36.0	36.6	31.1	7.9	14.6	29.9	21.9	25.7
Code-Alpaca	42.5	44.3	4.5	13.5	35.9	35.6	38.9	10.2	21.3	34.2	15.8	26.0
GPT4-Alpaca	46.9	47.1	9.0	16.5	38.2	38.8	23.5	6.2	15.1	36.6	63.1	33.7
Baize	43.7	41.6	5.0	10.0	37.2	38.7	33.6	7.2	15.1	28.7	21.9	25.4
ShareGPT	49.3	47.7	6.0	27.0	23.1	40.4	30.5	7.1	16.1	34.1	70.5	35.2
Human mix.	50.2	51.2	6.0	38.5	43.9	39.6	47.0	8.8	11.9	25.0	35.0	32.7
H+GPT mix (♂)	49.3	51.9	4.5	40.5	40.7	43.3	45.6	9.2	21.2	35.9	56.5	37.9
LLaMa-2 13B finetuning experiments ↓
Vanilla LLaMa-2	52.0	55.5	10.0	25.0	41.8	48.9	56.5	17.2	18.1	32.5	-	-
H+GPT mix (♀)	52.3	54.6	5.0	53.0	44.1	50.6	58.8	15.7	23.5	38.9	64.0	43.7
LLaMa 7B finetuning experiments ↓
Vanilla LLaMa	31.5	33.8	5.0	10.0	32.2	33.0	38.4	9.0	11.0	20.5	-	-
SuperNI	44.1	43.5	3.0	4.5	37.4	3.3	43.4	7.5	7.0	12.1	2.9	17.6
CoT	41.8	42.2	6.5	27.5	36.2	33.9	36.3	5.6	8.8	15.7	5.0	22.0
Flan V2	45.4	46.9	3.5	13.0	34.4	36.0	38.5	9.0	9.8	12.9	3.1	21.3
Dolly	38.1	35.0	4.5	5.5	28.3	23.8	39.8	9.7	11.4	22.5	10.9	20.1
Open Assistant 1	33.0	30.2	6.0	10.0	21.5	31.8	26.8	6.8	10.4	21.7	51.4	25.1
Self-instruct.	35.6	32.7	3.5	7.0	31.5	29.4	34.5	7.1	6.2	11.8	4.0	17.3
Unnat. Instruct.	43.1	37.8	3.5	7.0	32.9	32.7	37.3	6.9	9.2	16.8	7.5	20.2
Alpaca	41.6	40.0	7.0	7.5	34.1	31.2	29.4	7.3	10.4	21.7	21.4	22.7
Code-Alpaca	34.3	33.7	6.5	7.0	31.1	30.6	35.8	9.5	16.6	28.2	15.3	22.0
GPT4-Alpaca	42.2	37.4	6.5	10.5	30.9	32.3	20.6	4.9	13.2	26.2	57.3	28.3
Baize	40.5	38.1	4.0	6.5	31.3	34.0	29.1	6.8	11.5	26.5	20.0	22.4
ShareGPT	44.5	39.5	6.0	9.5	9.7	34.1	22.8	7.2	12.3	21.2	62.4	27.6
Human mix	46.2	48.2	4.5	25.5	38.8	35.6	43.2	8.0	9.5	20.2	28.7	28.1
H+GPT mix (♂)	44.8	47.1	7.0	25.0	38.5	38.5	43.5	8.0	18.6	29.1	48.6	33.1
LLaMa-2 7B finetuning experiments ↓
Vanilla LLaMa-2	41.8	46.1	8.0	12.0	32.2	39.3	51.2	15.1	13.3	26.8	-	-
H+GPT mix (♀)	49.2	50.5	6.5	37.0	38.6	44.2	52.8	11.9	20.4	33.9	57.3	38.3
Non-LLaMa 7B finetuning experiments ↓
OPT 6.7B	25.0	24.6	7.0	3.0	0.0	28.5	18.8	4.2	0.6	0.9	-	-
+H+GPT mix	32.6	33.7	3.0	13.5	30.6	27.9	24.1	3.6	5.2	8.9	25.9	19.6
Pythia 6.9B	25.8	26.2	4.5	3.5	0.0	28.1	25.6	3.6	7.5	13.7	-	-
+H+GPT mix	34.8	35.0	4.0	16.0	31.7	29.2	32.8	2.8	14.9	20.9	23.5	22.4