Improve language tag
#2
by
lbourdois
- opened
README.md
CHANGED
|
@@ -1,212 +1,224 @@
|
|
| 1 |
-
---
|
| 2 |
-
library_name: transformers
|
| 3 |
-
license: mit
|
| 4 |
-
datasets:
|
| 5 |
-
- ethicalabs/Kurtis-E1-SFT
|
| 6 |
-
language:
|
| 7 |
-
-
|
| 8 |
-
|
| 9 |
-
-
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
|
| 20 |
-
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
|
| 24 |
-
|
| 25 |
-
|
| 26 |
-
|
| 27 |
-
|
| 28 |
-
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
|
| 32 |
-
|
| 33 |
-
|
| 34 |
-
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
###
|
| 46 |
-
|
| 47 |
-
```
|
| 48 |
-
lm_eval --model hf --model_args pretrained=ethicalabs/Kurtis-E1.1-Qwen2.5-3B-Instruct --tasks
|
| 49 |
-
```
|
| 50 |
-
|
| 51 |
-
|
|
| 52 |
-
|
| 53 |
-
|
|
| 54 |
-
|
|
| 55 |
-
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
|
| 66 |
-
|
|
| 67 |
-
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
|
| 73 |
-
|
| 74 |
-
|
|
| 75 |
-
|
| 76 |
-
|
|
| 77 |
-
|
|
| 78 |
-
| -
|
| 79 |
-
|
|
| 80 |
-
| -
|
| 81 |
-
| -
|
| 82 |
-
| -
|
| 83 |
-
| -
|
| 84 |
-
| -
|
| 85 |
-
| -
|
| 86 |
-
| -
|
| 87 |
-
| -
|
| 88 |
-
| -
|
| 89 |
-
| -
|
| 90 |
-
| -
|
| 91 |
-
|
|
| 92 |
-
| -
|
| 93 |
-
|
|
| 94 |
-
| -
|
| 95 |
-
| -
|
| 96 |
-
| -
|
| 97 |
-
| -
|
| 98 |
-
| -
|
| 99 |
-
| -
|
| 100 |
-
| -
|
| 101 |
-
| -
|
| 102 |
-
| -
|
| 103 |
-
| -
|
| 104 |
-
| -
|
| 105 |
-
|
|
| 106 |
-
|
|
| 107 |
-
| -
|
| 108 |
-
| -
|
| 109 |
-
| -
|
| 110 |
-
| -
|
| 111 |
-
| -
|
| 112 |
-
| -
|
| 113 |
-
| -
|
| 114 |
-
| -
|
| 115 |
-
| -
|
| 116 |
-
| -
|
| 117 |
-
| -
|
| 118 |
-
|
|
| 119 |
-
| -
|
| 120 |
-
| -
|
| 121 |
-
| -
|
| 122 |
-
| -
|
| 123 |
-
| -
|
| 124 |
-
| -
|
| 125 |
-
| -
|
| 126 |
-
|
| 127 |
-
|
|
| 128 |
-
|
| 129 |
-
|
|
| 130 |
-
|
|
| 131 |
-
|
|
| 132 |
-
|
|
| 133 |
-
|
|
| 134 |
-
|
| 135 |
-
|
| 136 |
-
|
| 137 |
-
|
| 138 |
-
|
| 139 |
-
|
| 140 |
-
|
| 141 |
-
|
|
| 142 |
-
|
| 143 |
-
|
|
| 144 |
-
| -
|
| 145 |
-
|
|
| 146 |
-
|
| 147 |
-
|
| 148 |
-
|
| 149 |
-
|
| 150 |
-
|
| 151 |
-
|
| 152 |
-
|
| 153 |
-
|
|
| 154 |
-
|
| 155 |
-
|
|
| 156 |
-
|
|
| 157 |
-
| -
|
| 158 |
-
|
|
| 159 |
-
| -
|
| 160 |
-
| -
|
| 161 |
-
| -
|
| 162 |
-
| -
|
| 163 |
-
| -
|
| 164 |
-
| -
|
| 165 |
-
| -
|
| 166 |
-
| -
|
| 167 |
-
| -
|
| 168 |
-
| -
|
| 169 |
-
| -
|
| 170 |
-
|
|
| 171 |
-
| -
|
| 172 |
-
|
|
| 173 |
-
| -
|
| 174 |
-
| -
|
| 175 |
-
| -
|
| 176 |
-
| -
|
| 177 |
-
| -
|
| 178 |
-
| -
|
| 179 |
-
| -
|
| 180 |
-
| -
|
| 181 |
-
| -
|
| 182 |
-
| -
|
| 183 |
-
| -
|
| 184 |
-
|
|
| 185 |
-
|
|
| 186 |
-
| -
|
| 187 |
-
| -
|
| 188 |
-
| -
|
| 189 |
-
| -
|
| 190 |
-
| -
|
| 191 |
-
| -
|
| 192 |
-
| -
|
| 193 |
-
| -
|
| 194 |
-
| -
|
| 195 |
-
| -
|
| 196 |
-
| -
|
| 197 |
-
|
|
| 198 |
-
| -
|
| 199 |
-
| -
|
| 200 |
-
| -
|
| 201 |
-
| -
|
| 202 |
-
| -
|
| 203 |
-
| -
|
| 204 |
-
| -
|
| 205 |
-
|
| 206 |
-
|
|
| 207 |
-
|
| 208 |
-
|
|
| 209 |
-
|
|
| 210 |
-
|
|
| 211 |
-
|
|
| 212 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
license: mit
|
| 4 |
+
datasets:
|
| 5 |
+
- ethicalabs/Kurtis-E1-SFT
|
| 6 |
+
language:
|
| 7 |
+
- zho
|
| 8 |
+
- eng
|
| 9 |
+
- fra
|
| 10 |
+
- spa
|
| 11 |
+
- por
|
| 12 |
+
- deu
|
| 13 |
+
- ita
|
| 14 |
+
- rus
|
| 15 |
+
- jpn
|
| 16 |
+
- kor
|
| 17 |
+
- vie
|
| 18 |
+
- tha
|
| 19 |
+
- ara
|
| 20 |
+
base_model:
|
| 21 |
+
- Qwen/Qwen2.5-3B-Instruct
|
| 22 |
+
pipeline_tag: text-generation
|
| 23 |
+
---
|
| 24 |
+
|
| 25 |
+
# Model Card for Kurtis-E1.1-Qwen2.5-3B-Instruct
|
| 26 |
+
|
| 27 |
+
Kurtis E1.1 fine-tuned with [flower](https://flower.ai/)
|
| 28 |
+
|
| 29 |
+
## Eval Results
|
| 30 |
+
|
| 31 |
+
Evaluation tasks were performed with the [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) on an NVIDIA A40.
|
| 32 |
+
|
| 33 |
+
|
| 34 |
+
### hellaswag
|
| 35 |
+
|
| 36 |
+
```
|
| 37 |
+
lm_eval --model hf --model_args pretrained=ethicalabs/Kurtis-E1.1-Qwen2.5-3B-Instruct --tasks hellaswag --device cuda:0 --batch_size 8
|
| 38 |
+
```
|
| 39 |
+
|
| 40 |
+
| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr|
|
| 41 |
+
|---------|------:|------|-----:|--------|---|-----:|---|-----:|
|
| 42 |
+
|hellaswag| 1|none | 0|acc |↑ |0.5555|± |0.0050|
|
| 43 |
+
| | |none | 0|acc_norm|↑ |0.7412|± |0.0044|
|
| 44 |
+
|
| 45 |
+
### arc_easy
|
| 46 |
+
|
| 47 |
+
```
|
| 48 |
+
lm_eval --model hf --model_args pretrained=ethicalabs/Kurtis-E1.1-Qwen2.5-3B-Instruct --tasks arc_easy --device cuda:0 --batch_size 8
|
| 49 |
+
```
|
| 50 |
+
|
| 51 |
+
| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr|
|
| 52 |
+
|--------|------:|------|-----:|--------|---|-----:|---|-----:|
|
| 53 |
+
|arc_easy| 1|none | 0|acc |↑ |0.7710|± |0.0086|
|
| 54 |
+
| | |none | 0|acc_norm|↑ |0.6789|± |0.0096|
|
| 55 |
+
|
| 56 |
+
|
| 57 |
+
### arc_challenge
|
| 58 |
+
|
| 59 |
+
```
|
| 60 |
+
lm_eval --model hf --model_args pretrained=ethicalabs/Kurtis-E1.1-Qwen2.5-3B-Instruct --tasks arc_challenge --device cuda:0 --batch_size 8
|
| 61 |
+
```
|
| 62 |
+
|
| 63 |
+
| Tasks |Version|Filter|n-shot| Metric | |Value| |Stderr|
|
| 64 |
+
|-------------|------:|------|-----:|--------|---|----:|---|-----:|
|
| 65 |
+
|arc_challenge| 1|none | 0|acc |↑ |0.436|± |0.0145|
|
| 66 |
+
| | |none | 0|acc_norm|↑ |0.448|± |0.0145|
|
| 67 |
+
|
| 68 |
+
### mmlu
|
| 69 |
+
|
| 70 |
+
```
|
| 71 |
+
lm_eval --model hf --model_args pretrained=ethicalabs/Kurtis-E1.1-Qwen2.5-3B-Instruct --tasks mmlu --device cuda:0 --batch_size 8
|
| 72 |
+
```
|
| 73 |
+
|
| 74 |
+
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|
| 75 |
+
|---------------------------------------|------:|------|-----:|------|---|-----:|---|-----:|
|
| 76 |
+
|mmlu | 2|none | |acc |↑ |0.6522|± |0.0038|
|
| 77 |
+
| - humanities | 2|none | |acc |↑ |0.5734|± |0.0066|
|
| 78 |
+
| - formal_logic | 1|none | 0|acc |↑ |0.4603|± |0.0446|
|
| 79 |
+
| - high_school_european_history | 1|none | 0|acc |↑ |0.7939|± |0.0316|
|
| 80 |
+
| - high_school_us_history | 1|none | 0|acc |↑ |0.8333|± |0.0262|
|
| 81 |
+
| - high_school_world_history | 1|none | 0|acc |↑ |0.8397|± |0.0239|
|
| 82 |
+
| - international_law | 1|none | 0|acc |↑ |0.7769|± |0.0380|
|
| 83 |
+
| - jurisprudence | 1|none | 0|acc |↑ |0.7963|± |0.0389|
|
| 84 |
+
| - logical_fallacies | 1|none | 0|acc |↑ |0.7975|± |0.0316|
|
| 85 |
+
| - moral_disputes | 1|none | 0|acc |↑ |0.6850|± |0.0250|
|
| 86 |
+
| - moral_scenarios | 1|none | 0|acc |↑ |0.2905|± |0.0152|
|
| 87 |
+
| - philosophy | 1|none | 0|acc |↑ |0.7106|± |0.0258|
|
| 88 |
+
| - prehistory | 1|none | 0|acc |↑ |0.7438|± |0.0243|
|
| 89 |
+
| - professional_law | 1|none | 0|acc |↑ |0.4759|± |0.0128|
|
| 90 |
+
| - world_religions | 1|none | 0|acc |↑ |0.8246|± |0.0292|
|
| 91 |
+
| - other | 2|none | |acc |↑ |0.7087|± |0.0079|
|
| 92 |
+
| - business_ethics | 1|none | 0|acc |↑ |0.7300|± |0.0446|
|
| 93 |
+
| - clinical_knowledge | 1|none | 0|acc |↑ |0.7321|± |0.0273|
|
| 94 |
+
| - college_medicine | 1|none | 0|acc |↑ |0.6705|± |0.0358|
|
| 95 |
+
| - global_facts | 1|none | 0|acc |↑ |0.3900|± |0.0490|
|
| 96 |
+
| - human_aging | 1|none | 0|acc |↑ |0.7130|± |0.0304|
|
| 97 |
+
| - management | 1|none | 0|acc |↑ |0.7961|± |0.0399|
|
| 98 |
+
| - marketing | 1|none | 0|acc |↑ |0.8803|± |0.0213|
|
| 99 |
+
| - medical_genetics | 1|none | 0|acc |↑ |0.7600|± |0.0429|
|
| 100 |
+
| - miscellaneous | 1|none | 0|acc |↑ |0.7957|± |0.0144|
|
| 101 |
+
| - nutrition | 1|none | 0|acc |↑ |0.7353|± |0.0253|
|
| 102 |
+
| - professional_accounting | 1|none | 0|acc |↑ |0.5426|± |0.0297|
|
| 103 |
+
| - professional_medicine | 1|none | 0|acc |↑ |0.6434|± |0.0291|
|
| 104 |
+
| - virology | 1|none | 0|acc |↑ |0.4880|± |0.0389|
|
| 105 |
+
| - social sciences | 2|none | |acc |↑ |0.7618|± |0.0076|
|
| 106 |
+
| - econometrics | 1|none | 0|acc |↑ |0.5439|± |0.0469|
|
| 107 |
+
| - high_school_geography | 1|none | 0|acc |↑ |0.7677|± |0.0301|
|
| 108 |
+
| - high_school_government_and_politics| 1|none | 0|acc |↑ |0.8860|± |0.0229|
|
| 109 |
+
| - high_school_macroeconomics | 1|none | 0|acc |↑ |0.6949|± |0.0233|
|
| 110 |
+
| - high_school_microeconomics | 1|none | 0|acc |↑ |0.7773|± |0.0270|
|
| 111 |
+
| - high_school_psychology | 1|none | 0|acc |↑ |0.8477|± |0.0154|
|
| 112 |
+
| - human_sexuality | 1|none | 0|acc |↑ |0.7786|± |0.0364|
|
| 113 |
+
| - professional_psychology | 1|none | 0|acc |↑ |0.7075|± |0.0184|
|
| 114 |
+
| - public_relations | 1|none | 0|acc |↑ |0.6818|± |0.0446|
|
| 115 |
+
| - security_studies | 1|none | 0|acc |↑ |0.7224|± |0.0287|
|
| 116 |
+
| - sociology | 1|none | 0|acc |↑ |0.8458|± |0.0255|
|
| 117 |
+
| - us_foreign_policy | 1|none | 0|acc |↑ |0.8400|± |0.0368|
|
| 118 |
+
| - stem | 2|none | |acc |↑ |0.6070|± |0.0085|
|
| 119 |
+
| - abstract_algebra | 1|none | 0|acc |↑ |0.4700|± |0.0502|
|
| 120 |
+
| - anatomy | 1|none | 0|acc |↑ |0.6667|± |0.0407|
|
| 121 |
+
| - astronomy | 1|none | 0|acc |↑ |0.6776|± |0.0380|
|
| 122 |
+
| - college_biology | 1|none | 0|acc |↑ |0.7222|± |0.0375|
|
| 123 |
+
| - college_chemistry | 1|none | 0|acc |↑ |0.5000|± |0.0503|
|
| 124 |
+
| - college_computer_science | 1|none | 0|acc |↑ |0.6000|± |0.0492|
|
| 125 |
+
| - college_mathematics | 1|none | 0|acc |↑ |0.3400|± |0.0476|
|
| 126 |
+
| - college_physics | 1|none | 0|acc |↑ |0.4902|± |0.0497|
|
| 127 |
+
| - computer_security | 1|none | 0|acc |↑ |0.7000|± |0.0461|
|
| 128 |
+
| - conceptual_physics | 1|none | 0|acc |↑ |0.6468|± |0.0312|
|
| 129 |
+
| - electrical_engineering | 1|none | 0|acc |↑ |0.6690|± |0.0392|
|
| 130 |
+
| - elementary_mathematics | 1|none | 0|acc |↑ |0.5979|± |0.0253|
|
| 131 |
+
| - high_school_biology | 1|none | 0|acc |↑ |0.8129|± |0.0222|
|
| 132 |
+
| - high_school_chemistry | 1|none | 0|acc |↑ |0.5813|± |0.0347|
|
| 133 |
+
| - high_school_computer_science | 1|none | 0|acc |↑ |0.7800|± |0.0416|
|
| 134 |
+
| - high_school_mathematics | 1|none | 0|acc |↑ |0.5037|± |0.0305|
|
| 135 |
+
| - high_school_physics | 1|none | 0|acc |↑ |0.4437|± |0.0406|
|
| 136 |
+
| - high_school_statistics | 1|none | 0|acc |↑ |0.5972|± |0.0334|
|
| 137 |
+
| - machine_learning | 1|none | 0|acc |↑ |0.4554|± |0.0473|
|
| 138 |
+
|
| 139 |
+
| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr|
|
| 140 |
+
|------------------|------:|------|------|------|---|-----:|---|-----:|
|
| 141 |
+
|mmlu | 2|none | |acc |↑ |0.6522|± |0.0038|
|
| 142 |
+
| - humanities | 2|none | |acc |↑ |0.5734|± |0.0066|
|
| 143 |
+
| - other | 2|none | |acc |↑ |0.7087|± |0.0079|
|
| 144 |
+
| - social sciences| 2|none | |acc |↑ |0.7618|± |0.0076|
|
| 145 |
+
| - stem | 2|none | |acc |↑ |0.6070|± |0.0085|
|
| 146 |
+
|
| 147 |
+
### mmlu (5-shot)
|
| 148 |
+
|
| 149 |
+
```
|
| 150 |
+
lm_eval --model hf --model_args pretrained=ethicalabs/Kurtis-E1.1-Qwen2.5-3B-Instruct --tasks mmlu --device cuda:0 --batch_size 8 --num_fewshot 5
|
| 151 |
+
```
|
| 152 |
+
|
| 153 |
+
| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr|
|
| 154 |
+
|---------------------------------------|------:|------|-----:|------|---|-----:|---|-----:|
|
| 155 |
+
|mmlu | 2|none | |acc |↑ |0.6629|± |0.0038|
|
| 156 |
+
| - humanities | 2|none | |acc |↑ |0.5862|± |0.0067|
|
| 157 |
+
| - formal_logic | 1|none | 5|acc |↑ |0.4683|± |0.0446|
|
| 158 |
+
| - high_school_european_history | 1|none | 5|acc |↑ |0.7818|± |0.0323|
|
| 159 |
+
| - high_school_us_history | 1|none | 5|acc |↑ |0.8284|± |0.0265|
|
| 160 |
+
| - high_school_world_history | 1|none | 5|acc |↑ |0.8692|± |0.0219|
|
| 161 |
+
| - international_law | 1|none | 5|acc |↑ |0.7769|± |0.0380|
|
| 162 |
+
| - jurisprudence | 1|none | 5|acc |↑ |0.7963|± |0.0389|
|
| 163 |
+
| - logical_fallacies | 1|none | 5|acc |↑ |0.8098|± |0.0308|
|
| 164 |
+
| - moral_disputes | 1|none | 5|acc |↑ |0.7110|± |0.0244|
|
| 165 |
+
| - moral_scenarios | 1|none | 5|acc |↑ |0.3464|± |0.0159|
|
| 166 |
+
| - philosophy | 1|none | 5|acc |↑ |0.7042|± |0.0259|
|
| 167 |
+
| - prehistory | 1|none | 5|acc |↑ |0.7284|± |0.0247|
|
| 168 |
+
| - professional_law | 1|none | 5|acc |↑ |0.4759|± |0.0128|
|
| 169 |
+
| - world_religions | 1|none | 5|acc |↑ |0.8304|± |0.0288|
|
| 170 |
+
| - other | 2|none | |acc |↑ |0.7171|± |0.0078|
|
| 171 |
+
| - business_ethics | 1|none | 5|acc |↑ |0.7400|± |0.0441|
|
| 172 |
+
| - clinical_knowledge | 1|none | 5|acc |↑ |0.7321|± |0.0273|
|
| 173 |
+
| - college_medicine | 1|none | 5|acc |↑ |0.6647|± |0.0360|
|
| 174 |
+
| - global_facts | 1|none | 5|acc |↑ |0.4100|± |0.0494|
|
| 175 |
+
| - human_aging | 1|none | 5|acc |↑ |0.7220|± |0.0301|
|
| 176 |
+
| - management | 1|none | 5|acc |↑ |0.7864|± |0.0406|
|
| 177 |
+
| - marketing | 1|none | 5|acc |↑ |0.8889|± |0.0206|
|
| 178 |
+
| - medical_genetics | 1|none | 5|acc |↑ |0.7900|± |0.0409|
|
| 179 |
+
| - miscellaneous | 1|none | 5|acc |↑ |0.7957|± |0.0144|
|
| 180 |
+
| - nutrition | 1|none | 5|acc |↑ |0.7680|± |0.0242|
|
| 181 |
+
| - professional_accounting | 1|none | 5|acc |↑ |0.5532|± |0.0297|
|
| 182 |
+
| - professional_medicine | 1|none | 5|acc |↑ |0.6471|± |0.0290|
|
| 183 |
+
| - virology | 1|none | 5|acc |↑ |0.5120|± |0.0389|
|
| 184 |
+
| - social sciences | 2|none | |acc |↑ |0.7735|± |0.0075|
|
| 185 |
+
| - econometrics | 1|none | 5|acc |↑ |0.5877|± |0.0463|
|
| 186 |
+
| - high_school_geography | 1|none | 5|acc |↑ |0.7828|± |0.0294|
|
| 187 |
+
| - high_school_government_and_politics| 1|none | 5|acc |↑ |0.8756|± |0.0238|
|
| 188 |
+
| - high_school_macroeconomics | 1|none | 5|acc |↑ |0.7051|± |0.0231|
|
| 189 |
+
| - high_school_microeconomics | 1|none | 5|acc |↑ |0.7773|± |0.0270|
|
| 190 |
+
| - high_school_psychology | 1|none | 5|acc |↑ |0.8550|± |0.0151|
|
| 191 |
+
| - human_sexuality | 1|none | 5|acc |↑ |0.8092|± |0.0345|
|
| 192 |
+
| - professional_psychology | 1|none | 5|acc |↑ |0.7288|± |0.0180|
|
| 193 |
+
| - public_relations | 1|none | 5|acc |↑ |0.6909|± |0.0443|
|
| 194 |
+
| - security_studies | 1|none | 5|acc |↑ |0.7551|± |0.0275|
|
| 195 |
+
| - sociology | 1|none | 5|acc |↑ |0.8308|± |0.0265|
|
| 196 |
+
| - us_foreign_policy | 1|none | 5|acc |↑ |0.8300|± |0.0378|
|
| 197 |
+
| - stem | 2|none | |acc |↑ |0.6159|± |0.0084|
|
| 198 |
+
| - abstract_algebra | 1|none | 5|acc |↑ |0.5000|± |0.0503|
|
| 199 |
+
| - anatomy | 1|none | 5|acc |↑ |0.6222|± |0.0419|
|
| 200 |
+
| - astronomy | 1|none | 5|acc |↑ |0.7500|± |0.0352|
|
| 201 |
+
| - college_biology | 1|none | 5|acc |↑ |0.7083|± |0.0380|
|
| 202 |
+
| - college_chemistry | 1|none | 5|acc |↑ |0.4700|± |0.0502|
|
| 203 |
+
| - college_computer_science | 1|none | 5|acc |↑ |0.6200|± |0.0488|
|
| 204 |
+
| - college_mathematics | 1|none | 5|acc |↑ |0.4000|± |0.0492|
|
| 205 |
+
| - college_physics | 1|none | 5|acc |↑ |0.4902|± |0.0497|
|
| 206 |
+
| - computer_security | 1|none | 5|acc |↑ |0.8200|± |0.0386|
|
| 207 |
+
| - conceptual_physics | 1|none | 5|acc |↑ |0.6383|± |0.0314|
|
| 208 |
+
| - electrical_engineering | 1|none | 5|acc |↑ |0.6483|± |0.0398|
|
| 209 |
+
| - elementary_mathematics | 1|none | 5|acc |↑ |0.5820|± |0.0254|
|
| 210 |
+
| - high_school_biology | 1|none | 5|acc |↑ |0.8161|± |0.0220|
|
| 211 |
+
| - high_school_chemistry | 1|none | 5|acc |↑ |0.6059|± |0.0344|
|
| 212 |
+
| - high_school_computer_science | 1|none | 5|acc |↑ |0.7500|± |0.0435|
|
| 213 |
+
| - high_school_mathematics | 1|none | 5|acc |↑ |0.4926|± |0.0305|
|
| 214 |
+
| - high_school_physics | 1|none | 5|acc |↑ |0.4702|± |0.0408|
|
| 215 |
+
| - high_school_statistics | 1|none | 5|acc |↑ |0.6343|± |0.0328|
|
| 216 |
+
| - machine_learning | 1|none | 5|acc |↑ |0.4911|± |0.0475|
|
| 217 |
+
|
| 218 |
+
| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr|
|
| 219 |
+
|------------------|------:|------|------|------|---|-----:|---|-----:|
|
| 220 |
+
|mmlu | 2|none | |acc |↑ |0.6629|± |0.0038|
|
| 221 |
+
| - humanities | 2|none | |acc |↑ |0.5862|± |0.0067|
|
| 222 |
+
| - other | 2|none | |acc |↑ |0.7171|± |0.0078|
|
| 223 |
+
| - social sciences| 2|none | |acc |↑ |0.7735|± |0.0075|
|
| 224 |
+
| - stem | 2|none | |acc |↑ |0.6159|± |0.0084|
|