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·
b2a80b7
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Parent(s):
aa53828
update results / drop old misplaced results
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- lm-eval-output/RedPajama-INCITE-7B-Base/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -252
- lm-eval-output/RedPajama-INCITE-7B-Base/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -283
- lm-eval-output/RedPajama-INCITE-7B-Base/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -390
- lm-eval-output/RedPajama-INCITE-7B-Base/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -548
- lm-eval-output/RedPajama-INCITE-7B-Base/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -423
- lm-eval-output/RedPajama-INCITE-7B-Base/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/RedPajama-INCITE-7B-Base/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -248
- lm-eval-output/RedPajama-INCITE-7B-Base/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +0 -3
- lm-eval-output/allenai/OLMo-7B/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +21 -19
- lm-eval-output/allenai/OLMo-7B/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +15 -13
- lm-eval-output/allenai/OLMo-7B/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/arithmetic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/arithmetic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +13 -11
- lm-eval-output/allenai/OLMo-7B/arithmetic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/arithmetic__/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/arithmetic__/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +9 -7
- lm-eval-output/allenai/OLMo-7B/arithmetic__/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/asdiv/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/asdiv/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +7 -5
- lm-eval-output/allenai/OLMo-7B/asdiv/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +126 -124
- lm-eval-output/allenai/OLMo-7B/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/boolq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/boolq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -60
- lm-eval-output/allenai/OLMo-7B/boolq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/cb/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/cb/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +5 -3
- lm-eval-output/allenai/OLMo-7B/cb/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/ceval-valid/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/ceval-valid/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +0 -2588
- lm-eval-output/allenai/OLMo-7B/ceval-valid/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +247 -245
- lm-eval-output/allenai/OLMo-7B/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log +2 -2
- lm-eval-output/allenai/OLMo-7B/cola/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz +0 -3
- lm-eval-output/allenai/OLMo-7B/cola/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json +7 -5
lm-eval-output/RedPajama-INCITE-7B-Base/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
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| 121 |
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| 124 |
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| 125 |
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| 130 |
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| 132 |
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| 137 |
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| 138 |
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| 143 |
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| 146 |
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| 149 |
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| 150 |
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| 151 |
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| 152 |
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| 155 |
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| 157 |
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| 161 |
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| 162 |
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| 163 |
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| 164 |
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| 166 |
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| 168 |
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}
|
| 171 |
-
},
|
| 172 |
-
"xcopa_qu": {
|
| 173 |
-
"task": "xcopa_qu",
|
| 174 |
-
"group": "xcopa",
|
| 175 |
-
"dataset_path": "xcopa",
|
| 176 |
-
"dataset_name": "qu",
|
| 177 |
-
"validation_split": "validation",
|
| 178 |
-
"test_split": "test",
|
| 179 |
-
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f1a7c3579c0>, connector={'cause': 'imataq', 'effect': 'chaymi'})",
|
| 180 |
-
"doc_to_target": "label",
|
| 181 |
-
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
| 182 |
-
"description": "",
|
| 183 |
-
"target_delimiter": " ",
|
| 184 |
-
"fewshot_delimiter": "\n\n",
|
| 185 |
-
"metric_list": [
|
| 186 |
-
{
|
| 187 |
-
"metric": "acc"
|
| 188 |
-
}
|
| 189 |
-
],
|
| 190 |
-
"output_type": "multiple_choice",
|
| 191 |
-
"repeats": 1,
|
| 192 |
-
"should_decontaminate": false,
|
| 193 |
-
"metadata": {
|
| 194 |
-
"version": 1.0
|
| 195 |
-
}
|
| 196 |
-
},
|
| 197 |
-
"xcopa_sw": {
|
| 198 |
-
"task": "xcopa_sw",
|
| 199 |
-
"group": "xcopa",
|
| 200 |
-
"dataset_path": "xcopa",
|
| 201 |
-
"dataset_name": "sw",
|
| 202 |
-
"validation_split": "validation",
|
| 203 |
-
"test_split": "test",
|
| 204 |
-
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f1a7c3d2e80>, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
|
| 205 |
-
"doc_to_target": "label",
|
| 206 |
-
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
| 207 |
-
"description": "",
|
| 208 |
-
"target_delimiter": " ",
|
| 209 |
-
"fewshot_delimiter": "\n\n",
|
| 210 |
-
"metric_list": [
|
| 211 |
-
{
|
| 212 |
-
"metric": "acc"
|
| 213 |
-
}
|
| 214 |
-
],
|
| 215 |
-
"output_type": "multiple_choice",
|
| 216 |
-
"repeats": 1,
|
| 217 |
-
"should_decontaminate": false,
|
| 218 |
-
"metadata": {
|
| 219 |
-
"version": 1.0
|
| 220 |
-
}
|
| 221 |
-
},
|
| 222 |
-
"xcopa_ta": {
|
| 223 |
-
"task": "xcopa_ta",
|
| 224 |
-
"group": "xcopa",
|
| 225 |
-
"dataset_path": "xcopa",
|
| 226 |
-
"dataset_name": "ta",
|
| 227 |
-
"validation_split": "validation",
|
| 228 |
-
"test_split": "test",
|
| 229 |
-
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f1a7c3d2d40>, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
|
| 230 |
-
"doc_to_target": "label",
|
| 231 |
-
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
| 232 |
-
"description": "",
|
| 233 |
-
"target_delimiter": " ",
|
| 234 |
-
"fewshot_delimiter": "\n\n",
|
| 235 |
-
"metric_list": [
|
| 236 |
-
{
|
| 237 |
-
"metric": "acc"
|
| 238 |
-
}
|
| 239 |
-
],
|
| 240 |
-
"output_type": "multiple_choice",
|
| 241 |
-
"repeats": 1,
|
| 242 |
-
"should_decontaminate": false,
|
| 243 |
-
"metadata": {
|
| 244 |
-
"version": 1.0
|
| 245 |
-
}
|
| 246 |
-
},
|
| 247 |
-
"xcopa_th": {
|
| 248 |
-
"task": "xcopa_th",
|
| 249 |
-
"group": "xcopa",
|
| 250 |
-
"dataset_path": "xcopa",
|
| 251 |
-
"dataset_name": "th",
|
| 252 |
-
"validation_split": "validation",
|
| 253 |
-
"test_split": "test",
|
| 254 |
-
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f1a7c4816c0>, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
|
| 255 |
-
"doc_to_target": "label",
|
| 256 |
-
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
| 257 |
-
"description": "",
|
| 258 |
-
"target_delimiter": " ",
|
| 259 |
-
"fewshot_delimiter": "\n\n",
|
| 260 |
-
"metric_list": [
|
| 261 |
-
{
|
| 262 |
-
"metric": "acc"
|
| 263 |
-
}
|
| 264 |
-
],
|
| 265 |
-
"output_type": "multiple_choice",
|
| 266 |
-
"repeats": 1,
|
| 267 |
-
"should_decontaminate": false,
|
| 268 |
-
"metadata": {
|
| 269 |
-
"version": 1.0
|
| 270 |
-
}
|
| 271 |
-
},
|
| 272 |
-
"xcopa_tr": {
|
| 273 |
-
"task": "xcopa_tr",
|
| 274 |
-
"group": "xcopa",
|
| 275 |
-
"dataset_path": "xcopa",
|
| 276 |
-
"dataset_name": "tr",
|
| 277 |
-
"validation_split": "validation",
|
| 278 |
-
"test_split": "test",
|
| 279 |
-
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f1a7c357b00>, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
|
| 280 |
-
"doc_to_target": "label",
|
| 281 |
-
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
| 282 |
-
"description": "",
|
| 283 |
-
"target_delimiter": " ",
|
| 284 |
-
"fewshot_delimiter": "\n\n",
|
| 285 |
-
"metric_list": [
|
| 286 |
-
{
|
| 287 |
-
"metric": "acc"
|
| 288 |
-
}
|
| 289 |
-
],
|
| 290 |
-
"output_type": "multiple_choice",
|
| 291 |
-
"repeats": 1,
|
| 292 |
-
"should_decontaminate": false,
|
| 293 |
-
"metadata": {
|
| 294 |
-
"version": 1.0
|
| 295 |
-
}
|
| 296 |
-
},
|
| 297 |
-
"xcopa_vi": {
|
| 298 |
-
"task": "xcopa_vi",
|
| 299 |
-
"group": "xcopa",
|
| 300 |
-
"dataset_path": "xcopa",
|
| 301 |
-
"dataset_name": "vi",
|
| 302 |
-
"validation_split": "validation",
|
| 303 |
-
"test_split": "test",
|
| 304 |
-
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f1a90202f20>, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
|
| 305 |
-
"doc_to_target": "label",
|
| 306 |
-
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
| 307 |
-
"description": "",
|
| 308 |
-
"target_delimiter": " ",
|
| 309 |
-
"fewshot_delimiter": "\n\n",
|
| 310 |
-
"metric_list": [
|
| 311 |
-
{
|
| 312 |
-
"metric": "acc"
|
| 313 |
-
}
|
| 314 |
-
],
|
| 315 |
-
"output_type": "multiple_choice",
|
| 316 |
-
"repeats": 1,
|
| 317 |
-
"should_decontaminate": false,
|
| 318 |
-
"metadata": {
|
| 319 |
-
"version": 1.0
|
| 320 |
-
}
|
| 321 |
-
},
|
| 322 |
-
"xcopa_zh": {
|
| 323 |
-
"task": "xcopa_zh",
|
| 324 |
-
"group": "xcopa",
|
| 325 |
-
"dataset_path": "xcopa",
|
| 326 |
-
"dataset_name": "zh",
|
| 327 |
-
"validation_split": "validation",
|
| 328 |
-
"test_split": "test",
|
| 329 |
-
"doc_to_text": "functools.partial(<function doc_to_text at 0x7f1a9edd3380>, connector={'cause': '因为', 'effect': '所以'})",
|
| 330 |
-
"doc_to_target": "label",
|
| 331 |
-
"doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
|
| 332 |
-
"description": "",
|
| 333 |
-
"target_delimiter": " ",
|
| 334 |
-
"fewshot_delimiter": "\n\n",
|
| 335 |
-
"metric_list": [
|
| 336 |
-
{
|
| 337 |
-
"metric": "acc"
|
| 338 |
-
}
|
| 339 |
-
],
|
| 340 |
-
"output_type": "multiple_choice",
|
| 341 |
-
"repeats": 1,
|
| 342 |
-
"should_decontaminate": false,
|
| 343 |
-
"metadata": {
|
| 344 |
-
"version": 1.0
|
| 345 |
-
}
|
| 346 |
-
}
|
| 347 |
-
},
|
| 348 |
-
"versions": {
|
| 349 |
-
"xcopa": "N/A",
|
| 350 |
-
"xcopa_et": 1.0,
|
| 351 |
-
"xcopa_ht": 1.0,
|
| 352 |
-
"xcopa_id": 1.0,
|
| 353 |
-
"xcopa_it": 1.0,
|
| 354 |
-
"xcopa_qu": 1.0,
|
| 355 |
-
"xcopa_sw": 1.0,
|
| 356 |
-
"xcopa_ta": 1.0,
|
| 357 |
-
"xcopa_th": 1.0,
|
| 358 |
-
"xcopa_tr": 1.0,
|
| 359 |
-
"xcopa_vi": 1.0,
|
| 360 |
-
"xcopa_zh": 1.0
|
| 361 |
-
},
|
| 362 |
-
"n-shot": {
|
| 363 |
-
"xcopa": 0,
|
| 364 |
-
"xcopa_et": 0,
|
| 365 |
-
"xcopa_ht": 0,
|
| 366 |
-
"xcopa_id": 0,
|
| 367 |
-
"xcopa_it": 0,
|
| 368 |
-
"xcopa_qu": 0,
|
| 369 |
-
"xcopa_sw": 0,
|
| 370 |
-
"xcopa_ta": 0,
|
| 371 |
-
"xcopa_th": 0,
|
| 372 |
-
"xcopa_tr": 0,
|
| 373 |
-
"xcopa_vi": 0,
|
| 374 |
-
"xcopa_zh": 0
|
| 375 |
-
},
|
| 376 |
-
"config": {
|
| 377 |
-
"model": "hf",
|
| 378 |
-
"model_args": "pretrained=togethercomputer/RedPajama-INCITE-7B-Base,dtype=bfloat16,trust_remote_code=True",
|
| 379 |
-
"batch_size": "auto",
|
| 380 |
-
"batch_sizes": [
|
| 381 |
-
16
|
| 382 |
-
],
|
| 383 |
-
"device": null,
|
| 384 |
-
"use_cache": null,
|
| 385 |
-
"limit": null,
|
| 386 |
-
"bootstrap_iters": 100000,
|
| 387 |
-
"gen_kwargs": null
|
| 388 |
-
},
|
| 389 |
-
"git_hash": "2c0a875"
|
| 390 |
-
}
|
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"task": "xnli_sw",
|
| 337 |
-
"group": "xnli",
|
| 338 |
-
"dataset_path": "xnli",
|
| 339 |
-
"dataset_name": "sw",
|
| 340 |
-
"training_split": "train",
|
| 341 |
-
"validation_split": "validation",
|
| 342 |
-
"doc_to_text": "",
|
| 343 |
-
"doc_to_target": "label",
|
| 344 |
-
"doc_to_choice": "{{[premise+\", sahihi? Ndiyo, \"+hypothesis,premise+\", sahihi? Hivyo, \"+hypothesis,premise+\", sahihi? Hapana, \"+hypothesis]}}",
|
| 345 |
-
"description": "",
|
| 346 |
-
"target_delimiter": " ",
|
| 347 |
-
"fewshot_delimiter": "\n\n",
|
| 348 |
-
"metric_list": [
|
| 349 |
-
{
|
| 350 |
-
"metric": "acc",
|
| 351 |
-
"aggregation": "mean",
|
| 352 |
-
"higher_is_better": true
|
| 353 |
-
}
|
| 354 |
-
],
|
| 355 |
-
"output_type": "multiple_choice",
|
| 356 |
-
"repeats": 1,
|
| 357 |
-
"should_decontaminate": false,
|
| 358 |
-
"metadata": {
|
| 359 |
-
"version": 1.0
|
| 360 |
-
}
|
| 361 |
-
},
|
| 362 |
-
"xnli_th": {
|
| 363 |
-
"task": "xnli_th",
|
| 364 |
-
"group": "xnli",
|
| 365 |
-
"dataset_path": "xnli",
|
| 366 |
-
"dataset_name": "th",
|
| 367 |
-
"training_split": "train",
|
| 368 |
-
"validation_split": "validation",
|
| 369 |
-
"doc_to_text": "",
|
| 370 |
-
"doc_to_target": "label",
|
| 371 |
-
"doc_to_choice": "{{[premise+\", ถูกต้อง? ใช่, \"+hypothesis,premise+\", ถูกต้อง? ดังนั้น, \"+hypothesis,premise+\", ถูกต้อง? ไม่, \"+hypothesis]}}",
|
| 372 |
-
"description": "",
|
| 373 |
-
"target_delimiter": " ",
|
| 374 |
-
"fewshot_delimiter": "\n\n",
|
| 375 |
-
"metric_list": [
|
| 376 |
-
{
|
| 377 |
-
"metric": "acc",
|
| 378 |
-
"aggregation": "mean",
|
| 379 |
-
"higher_is_better": true
|
| 380 |
-
}
|
| 381 |
-
],
|
| 382 |
-
"output_type": "multiple_choice",
|
| 383 |
-
"repeats": 1,
|
| 384 |
-
"should_decontaminate": false,
|
| 385 |
-
"metadata": {
|
| 386 |
-
"version": 1.0
|
| 387 |
-
}
|
| 388 |
-
},
|
| 389 |
-
"xnli_tr": {
|
| 390 |
-
"task": "xnli_tr",
|
| 391 |
-
"group": "xnli",
|
| 392 |
-
"dataset_path": "xnli",
|
| 393 |
-
"dataset_name": "tr",
|
| 394 |
-
"training_split": "train",
|
| 395 |
-
"validation_split": "validation",
|
| 396 |
-
"doc_to_text": "",
|
| 397 |
-
"doc_to_target": "label",
|
| 398 |
-
"doc_to_choice": "{{[premise+\", doğru? Evet, \"+hypothesis,premise+\", doğru? Böylece, \"+hypothesis,premise+\", doğru? Hayır, \"+hypothesis]}}",
|
| 399 |
-
"description": "",
|
| 400 |
-
"target_delimiter": " ",
|
| 401 |
-
"fewshot_delimiter": "\n\n",
|
| 402 |
-
"metric_list": [
|
| 403 |
-
{
|
| 404 |
-
"metric": "acc",
|
| 405 |
-
"aggregation": "mean",
|
| 406 |
-
"higher_is_better": true
|
| 407 |
-
}
|
| 408 |
-
],
|
| 409 |
-
"output_type": "multiple_choice",
|
| 410 |
-
"repeats": 1,
|
| 411 |
-
"should_decontaminate": false,
|
| 412 |
-
"metadata": {
|
| 413 |
-
"version": 1.0
|
| 414 |
-
}
|
| 415 |
-
},
|
| 416 |
-
"xnli_ur": {
|
| 417 |
-
"task": "xnli_ur",
|
| 418 |
-
"group": "xnli",
|
| 419 |
-
"dataset_path": "xnli",
|
| 420 |
-
"dataset_name": "ur",
|
| 421 |
-
"training_split": "train",
|
| 422 |
-
"validation_split": "validation",
|
| 423 |
-
"doc_to_text": "",
|
| 424 |
-
"doc_to_target": "label",
|
| 425 |
-
"doc_to_choice": "{{[premise+\", صحیح? جی ہاں, \"+hypothesis,premise+\", صحیح? اس لئے, \"+hypothesis,premise+\", صحیح? نہیں, \"+hypothesis]}}",
|
| 426 |
-
"description": "",
|
| 427 |
-
"target_delimiter": " ",
|
| 428 |
-
"fewshot_delimiter": "\n\n",
|
| 429 |
-
"metric_list": [
|
| 430 |
-
{
|
| 431 |
-
"metric": "acc",
|
| 432 |
-
"aggregation": "mean",
|
| 433 |
-
"higher_is_better": true
|
| 434 |
-
}
|
| 435 |
-
],
|
| 436 |
-
"output_type": "multiple_choice",
|
| 437 |
-
"repeats": 1,
|
| 438 |
-
"should_decontaminate": false,
|
| 439 |
-
"metadata": {
|
| 440 |
-
"version": 1.0
|
| 441 |
-
}
|
| 442 |
-
},
|
| 443 |
-
"xnli_vi": {
|
| 444 |
-
"task": "xnli_vi",
|
| 445 |
-
"group": "xnli",
|
| 446 |
-
"dataset_path": "xnli",
|
| 447 |
-
"dataset_name": "vi",
|
| 448 |
-
"training_split": "train",
|
| 449 |
-
"validation_split": "validation",
|
| 450 |
-
"doc_to_text": "",
|
| 451 |
-
"doc_to_target": "label",
|
| 452 |
-
"doc_to_choice": "{{[premise+\", đúng? Vâng, \"+hypothesis,premise+\", đúng? Vì vậy, \"+hypothesis,premise+\", đúng? Không, \"+hypothesis]}}",
|
| 453 |
-
"description": "",
|
| 454 |
-
"target_delimiter": " ",
|
| 455 |
-
"fewshot_delimiter": "\n\n",
|
| 456 |
-
"metric_list": [
|
| 457 |
-
{
|
| 458 |
-
"metric": "acc",
|
| 459 |
-
"aggregation": "mean",
|
| 460 |
-
"higher_is_better": true
|
| 461 |
-
}
|
| 462 |
-
],
|
| 463 |
-
"output_type": "multiple_choice",
|
| 464 |
-
"repeats": 1,
|
| 465 |
-
"should_decontaminate": false,
|
| 466 |
-
"metadata": {
|
| 467 |
-
"version": 1.0
|
| 468 |
-
}
|
| 469 |
-
},
|
| 470 |
-
"xnli_zh": {
|
| 471 |
-
"task": "xnli_zh",
|
| 472 |
-
"group": "xnli",
|
| 473 |
-
"dataset_path": "xnli",
|
| 474 |
-
"dataset_name": "zh",
|
| 475 |
-
"training_split": "train",
|
| 476 |
-
"validation_split": "validation",
|
| 477 |
-
"doc_to_text": "",
|
| 478 |
-
"doc_to_target": "label",
|
| 479 |
-
"doc_to_choice": "{{[premise+\", 正确? 是的, \"+hypothesis,premise+\", 正确? 所以, \"+hypothesis,premise+\", 正确? 不是的, \"+hypothesis]}}",
|
| 480 |
-
"description": "",
|
| 481 |
-
"target_delimiter": " ",
|
| 482 |
-
"fewshot_delimiter": "\n\n",
|
| 483 |
-
"metric_list": [
|
| 484 |
-
{
|
| 485 |
-
"metric": "acc",
|
| 486 |
-
"aggregation": "mean",
|
| 487 |
-
"higher_is_better": true
|
| 488 |
-
}
|
| 489 |
-
],
|
| 490 |
-
"output_type": "multiple_choice",
|
| 491 |
-
"repeats": 1,
|
| 492 |
-
"should_decontaminate": false,
|
| 493 |
-
"metadata": {
|
| 494 |
-
"version": 1.0
|
| 495 |
-
}
|
| 496 |
-
}
|
| 497 |
-
},
|
| 498 |
-
"versions": {
|
| 499 |
-
"xnli": "N/A",
|
| 500 |
-
"xnli_ar": 1.0,
|
| 501 |
-
"xnli_bg": 1.0,
|
| 502 |
-
"xnli_de": 1.0,
|
| 503 |
-
"xnli_el": 1.0,
|
| 504 |
-
"xnli_en": 1.0,
|
| 505 |
-
"xnli_es": 1.0,
|
| 506 |
-
"xnli_fr": 1.0,
|
| 507 |
-
"xnli_hi": 1.0,
|
| 508 |
-
"xnli_ru": 1.0,
|
| 509 |
-
"xnli_sw": 1.0,
|
| 510 |
-
"xnli_th": 1.0,
|
| 511 |
-
"xnli_tr": 1.0,
|
| 512 |
-
"xnli_ur": 1.0,
|
| 513 |
-
"xnli_vi": 1.0,
|
| 514 |
-
"xnli_zh": 1.0
|
| 515 |
-
},
|
| 516 |
-
"n-shot": {
|
| 517 |
-
"xnli": 0,
|
| 518 |
-
"xnli_ar": 0,
|
| 519 |
-
"xnli_bg": 0,
|
| 520 |
-
"xnli_de": 0,
|
| 521 |
-
"xnli_el": 0,
|
| 522 |
-
"xnli_en": 0,
|
| 523 |
-
"xnli_es": 0,
|
| 524 |
-
"xnli_fr": 0,
|
| 525 |
-
"xnli_hi": 0,
|
| 526 |
-
"xnli_ru": 0,
|
| 527 |
-
"xnli_sw": 0,
|
| 528 |
-
"xnli_th": 0,
|
| 529 |
-
"xnli_tr": 0,
|
| 530 |
-
"xnli_ur": 0,
|
| 531 |
-
"xnli_vi": 0,
|
| 532 |
-
"xnli_zh": 0
|
| 533 |
-
},
|
| 534 |
-
"config": {
|
| 535 |
-
"model": "hf",
|
| 536 |
-
"model_args": "pretrained=togethercomputer/RedPajama-INCITE-7B-Base,dtype=bfloat16,trust_remote_code=True",
|
| 537 |
-
"batch_size": "auto",
|
| 538 |
-
"batch_sizes": [
|
| 539 |
-
8
|
| 540 |
-
],
|
| 541 |
-
"device": null,
|
| 542 |
-
"use_cache": null,
|
| 543 |
-
"limit": null,
|
| 544 |
-
"bootstrap_iters": 100000,
|
| 545 |
-
"gen_kwargs": null
|
| 546 |
-
},
|
| 547 |
-
"git_hash": "2c0a875"
|
| 548 |
-
}
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| 14 |
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"acc,none": 0.6385542168674698,
|
| 15 |
-
"acc_stderr,none": 0.053053439348320096,
|
| 16 |
-
"alias": " - xwinograd_fr"
|
| 17 |
-
},
|
| 18 |
-
"xwinograd_jp": {
|
| 19 |
-
"acc,none": 0.5620437956204379,
|
| 20 |
-
"acc_stderr,none": 0.016029414748731596,
|
| 21 |
-
"alias": " - xwinograd_jp"
|
| 22 |
-
},
|
| 23 |
-
"xwinograd_pt": {
|
| 24 |
-
"acc,none": 0.6653992395437263,
|
| 25 |
-
"acc_stderr,none": 0.02915103415331038,
|
| 26 |
-
"alias": " - xwinograd_pt"
|
| 27 |
-
},
|
| 28 |
-
"xwinograd_ru": {
|
| 29 |
-
"acc,none": 0.6222222222222222,
|
| 30 |
-
"acc_stderr,none": 0.0273606328610564,
|
| 31 |
-
"alias": " - xwinograd_ru"
|
| 32 |
-
},
|
| 33 |
-
"xwinograd_zh": {
|
| 34 |
-
"acc,none": 0.628968253968254,
|
| 35 |
-
"acc_stderr,none": 0.02153951426767635,
|
| 36 |
-
"alias": " - xwinograd_zh"
|
| 37 |
-
}
|
| 38 |
-
},
|
| 39 |
-
"groups": {
|
| 40 |
-
"xwinograd": {
|
| 41 |
-
"acc,none": 0.74331310406833,
|
| 42 |
-
"acc_stderr,none": 0.08408219267029617,
|
| 43 |
-
"alias": "xwinograd"
|
| 44 |
-
}
|
| 45 |
-
},
|
| 46 |
-
"configs": {
|
| 47 |
-
"xwinograd_en": {
|
| 48 |
-
"task": "xwinograd_en",
|
| 49 |
-
"group": [
|
| 50 |
-
"xwinograd"
|
| 51 |
-
],
|
| 52 |
-
"dataset_path": "Muennighoff/xwinograd",
|
| 53 |
-
"dataset_name": "en",
|
| 54 |
-
"test_split": "test",
|
| 55 |
-
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
| 56 |
-
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
| 57 |
-
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
| 58 |
-
"description": "",
|
| 59 |
-
"target_delimiter": " ",
|
| 60 |
-
"fewshot_delimiter": "\n\n",
|
| 61 |
-
"metric_list": [
|
| 62 |
-
{
|
| 63 |
-
"metric": "acc",
|
| 64 |
-
"aggregation": "mean",
|
| 65 |
-
"higher_is_better": true
|
| 66 |
-
}
|
| 67 |
-
],
|
| 68 |
-
"output_type": "multiple_choice",
|
| 69 |
-
"repeats": 1,
|
| 70 |
-
"should_decontaminate": false,
|
| 71 |
-
"metadata": {
|
| 72 |
-
"version": 1.0
|
| 73 |
-
}
|
| 74 |
-
},
|
| 75 |
-
"xwinograd_fr": {
|
| 76 |
-
"task": "xwinograd_fr",
|
| 77 |
-
"group": [
|
| 78 |
-
"xwinograd"
|
| 79 |
-
],
|
| 80 |
-
"dataset_path": "Muennighoff/xwinograd",
|
| 81 |
-
"dataset_name": "fr",
|
| 82 |
-
"test_split": "test",
|
| 83 |
-
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
| 84 |
-
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
| 85 |
-
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
| 86 |
-
"description": "",
|
| 87 |
-
"target_delimiter": " ",
|
| 88 |
-
"fewshot_delimiter": "\n\n",
|
| 89 |
-
"metric_list": [
|
| 90 |
-
{
|
| 91 |
-
"metric": "acc",
|
| 92 |
-
"aggregation": "mean",
|
| 93 |
-
"higher_is_better": true
|
| 94 |
-
}
|
| 95 |
-
],
|
| 96 |
-
"output_type": "multiple_choice",
|
| 97 |
-
"repeats": 1,
|
| 98 |
-
"should_decontaminate": false,
|
| 99 |
-
"metadata": {
|
| 100 |
-
"version": 1.0
|
| 101 |
-
}
|
| 102 |
-
},
|
| 103 |
-
"xwinograd_jp": {
|
| 104 |
-
"task": "xwinograd_jp",
|
| 105 |
-
"group": [
|
| 106 |
-
"xwinograd"
|
| 107 |
-
],
|
| 108 |
-
"dataset_path": "Muennighoff/xwinograd",
|
| 109 |
-
"dataset_name": "jp",
|
| 110 |
-
"test_split": "test",
|
| 111 |
-
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
| 112 |
-
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
| 113 |
-
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
| 114 |
-
"description": "",
|
| 115 |
-
"target_delimiter": " ",
|
| 116 |
-
"fewshot_delimiter": "\n\n",
|
| 117 |
-
"metric_list": [
|
| 118 |
-
{
|
| 119 |
-
"metric": "acc",
|
| 120 |
-
"aggregation": "mean",
|
| 121 |
-
"higher_is_better": true
|
| 122 |
-
}
|
| 123 |
-
],
|
| 124 |
-
"output_type": "multiple_choice",
|
| 125 |
-
"repeats": 1,
|
| 126 |
-
"should_decontaminate": false,
|
| 127 |
-
"metadata": {
|
| 128 |
-
"version": 1.0
|
| 129 |
-
}
|
| 130 |
-
},
|
| 131 |
-
"xwinograd_pt": {
|
| 132 |
-
"task": "xwinograd_pt",
|
| 133 |
-
"group": [
|
| 134 |
-
"xwinograd"
|
| 135 |
-
],
|
| 136 |
-
"dataset_path": "Muennighoff/xwinograd",
|
| 137 |
-
"dataset_name": "pt",
|
| 138 |
-
"test_split": "test",
|
| 139 |
-
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
| 140 |
-
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
| 141 |
-
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
| 142 |
-
"description": "",
|
| 143 |
-
"target_delimiter": " ",
|
| 144 |
-
"fewshot_delimiter": "\n\n",
|
| 145 |
-
"metric_list": [
|
| 146 |
-
{
|
| 147 |
-
"metric": "acc",
|
| 148 |
-
"aggregation": "mean",
|
| 149 |
-
"higher_is_better": true
|
| 150 |
-
}
|
| 151 |
-
],
|
| 152 |
-
"output_type": "multiple_choice",
|
| 153 |
-
"repeats": 1,
|
| 154 |
-
"should_decontaminate": false,
|
| 155 |
-
"metadata": {
|
| 156 |
-
"version": 1.0
|
| 157 |
-
}
|
| 158 |
-
},
|
| 159 |
-
"xwinograd_ru": {
|
| 160 |
-
"task": "xwinograd_ru",
|
| 161 |
-
"group": [
|
| 162 |
-
"xwinograd"
|
| 163 |
-
],
|
| 164 |
-
"dataset_path": "Muennighoff/xwinograd",
|
| 165 |
-
"dataset_name": "ru",
|
| 166 |
-
"test_split": "test",
|
| 167 |
-
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
| 168 |
-
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
| 169 |
-
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
| 170 |
-
"description": "",
|
| 171 |
-
"target_delimiter": " ",
|
| 172 |
-
"fewshot_delimiter": "\n\n",
|
| 173 |
-
"metric_list": [
|
| 174 |
-
{
|
| 175 |
-
"metric": "acc",
|
| 176 |
-
"aggregation": "mean",
|
| 177 |
-
"higher_is_better": true
|
| 178 |
-
}
|
| 179 |
-
],
|
| 180 |
-
"output_type": "multiple_choice",
|
| 181 |
-
"repeats": 1,
|
| 182 |
-
"should_decontaminate": false,
|
| 183 |
-
"metadata": {
|
| 184 |
-
"version": 1.0
|
| 185 |
-
}
|
| 186 |
-
},
|
| 187 |
-
"xwinograd_zh": {
|
| 188 |
-
"task": "xwinograd_zh",
|
| 189 |
-
"group": [
|
| 190 |
-
"xwinograd"
|
| 191 |
-
],
|
| 192 |
-
"dataset_path": "Muennighoff/xwinograd",
|
| 193 |
-
"dataset_name": "zh",
|
| 194 |
-
"test_split": "test",
|
| 195 |
-
"doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
|
| 196 |
-
"doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
|
| 197 |
-
"doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
|
| 198 |
-
"description": "",
|
| 199 |
-
"target_delimiter": " ",
|
| 200 |
-
"fewshot_delimiter": "\n\n",
|
| 201 |
-
"metric_list": [
|
| 202 |
-
{
|
| 203 |
-
"metric": "acc",
|
| 204 |
-
"aggregation": "mean",
|
| 205 |
-
"higher_is_better": true
|
| 206 |
-
}
|
| 207 |
-
],
|
| 208 |
-
"output_type": "multiple_choice",
|
| 209 |
-
"repeats": 1,
|
| 210 |
-
"should_decontaminate": false,
|
| 211 |
-
"metadata": {
|
| 212 |
-
"version": 1.0
|
| 213 |
-
}
|
| 214 |
-
}
|
| 215 |
-
},
|
| 216 |
-
"versions": {
|
| 217 |
-
"xwinograd": "N/A",
|
| 218 |
-
"xwinograd_en": 1.0,
|
| 219 |
-
"xwinograd_fr": 1.0,
|
| 220 |
-
"xwinograd_jp": 1.0,
|
| 221 |
-
"xwinograd_pt": 1.0,
|
| 222 |
-
"xwinograd_ru": 1.0,
|
| 223 |
-
"xwinograd_zh": 1.0
|
| 224 |
-
},
|
| 225 |
-
"n-shot": {
|
| 226 |
-
"xwinograd": 0,
|
| 227 |
-
"xwinograd_en": 0,
|
| 228 |
-
"xwinograd_fr": 0,
|
| 229 |
-
"xwinograd_jp": 0,
|
| 230 |
-
"xwinograd_pt": 0,
|
| 231 |
-
"xwinograd_ru": 0,
|
| 232 |
-
"xwinograd_zh": 0
|
| 233 |
-
},
|
| 234 |
-
"config": {
|
| 235 |
-
"model": "hf",
|
| 236 |
-
"model_args": "pretrained=togethercomputer/RedPajama-INCITE-7B-Base,dtype=bfloat16,trust_remote_code=True",
|
| 237 |
-
"batch_size": "auto",
|
| 238 |
-
"batch_sizes": [
|
| 239 |
-
16
|
| 240 |
-
],
|
| 241 |
-
"device": null,
|
| 242 |
-
"use_cache": null,
|
| 243 |
-
"limit": null,
|
| 244 |
-
"bootstrap_iters": 100000,
|
| 245 |
-
"gen_kwargs": null
|
| 246 |
-
},
|
| 247 |
-
"git_hash": "2c0a875"
|
| 248 |
-
}
|
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@@ -350,13 +350,15 @@
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lm-eval-output/allenai/OLMo-7B/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
CHANGED
|
@@ -1,13 +1,13 @@
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|
| 1 |
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|
| 2 |
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| 3 |
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| 4 |
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| 7 |
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| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
"blimp_anaphor_gender_agreement": {
|
|
@@ -16,23 +16,23 @@
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|
| 16 |
"alias": " - blimp_anaphor_gender_agreement"
|
| 17 |
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|
| 18 |
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|
| 19 |
-
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 24 |
-
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
-
"acc,none": 0.
|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
-
"acc,none": 0.
|
| 35 |
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"acc_stderr,none": 0.
|
| 36 |
"alias": " - blimp_causative"
|
| 37 |
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|
| 38 |
"blimp_complex_NP_island": {
|
|
@@ -41,113 +41,113 @@
|
|
| 41 |
"alias": " - blimp_complex_NP_island"
|
| 42 |
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|
| 43 |
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|
| 44 |
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"acc,none": 0.
|
| 45 |
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"acc_stderr,none": 0.
|
| 46 |
"alias": " - blimp_coordinate_structure_constraint_complex_left_branch"
|
| 47 |
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|
| 48 |
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|
| 49 |
-
"acc,none": 0.
|
| 50 |
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|
| 51 |
"alias": " - blimp_coordinate_structure_constraint_object_extraction"
|
| 52 |
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| 53 |
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|
| 54 |
"acc,none": 0.986,
|
| 55 |
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"acc_stderr,none": 0.
|
| 56 |
"alias": " - blimp_determiner_noun_agreement_1"
|
| 57 |
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| 58 |
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|
| 59 |
-
"acc,none": 0.
|
| 60 |
-
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|
| 61 |
"alias": " - blimp_determiner_noun_agreement_2"
|
| 62 |
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|
| 63 |
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|
| 64 |
-
"acc,none": 0.
|
| 65 |
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|
| 66 |
"alias": " - blimp_determiner_noun_agreement_irregular_1"
|
| 67 |
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|
| 68 |
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|
| 69 |
-
"acc,none": 0.
|
| 70 |
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"acc_stderr,none": 0.
|
| 71 |
"alias": " - blimp_determiner_noun_agreement_irregular_2"
|
| 72 |
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|
| 73 |
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|
| 74 |
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"acc,none": 0.
|
| 75 |
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|
| 76 |
"alias": " - blimp_determiner_noun_agreement_with_adj_2"
|
| 77 |
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|
| 78 |
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|
| 79 |
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"acc,none": 0.
|
| 80 |
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|
| 81 |
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|
| 82 |
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| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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"acc,none": 0.
|
| 90 |
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|
| 91 |
"alias": " - blimp_determiner_noun_agreement_with_adjective_1"
|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
"alias": " - blimp_distractor_agreement_relational_noun"
|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
"alias": " - blimp_distractor_agreement_relative_clause"
|
| 102 |
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|
| 103 |
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|
| 104 |
-
"acc,none": 0.
|
| 105 |
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|
| 106 |
"alias": " - blimp_drop_argument"
|
| 107 |
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|
| 108 |
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|
| 109 |
"acc,none": 0.812,
|
| 110 |
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|
| 111 |
"alias": " - blimp_ellipsis_n_bar_1"
|
| 112 |
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|
| 113 |
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|
| 114 |
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"acc,none": 0.
|
| 115 |
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|
| 116 |
"alias": " - blimp_ellipsis_n_bar_2"
|
| 117 |
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|
| 118 |
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|
| 119 |
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"acc,none": 0.
|
| 120 |
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|
| 121 |
"alias": " - blimp_existential_there_object_raising"
|
| 122 |
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|
| 123 |
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|
| 124 |
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"acc,none": 0.
|
| 125 |
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|
| 126 |
"alias": " - blimp_existential_there_quantifiers_1"
|
| 127 |
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|
| 128 |
"blimp_existential_there_quantifiers_2": {
|
| 129 |
"acc,none": 0.377,
|
| 130 |
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"acc_stderr,none": 0.
|
| 131 |
"alias": " - blimp_existential_there_quantifiers_2"
|
| 132 |
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|
| 133 |
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|
| 134 |
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"acc,none": 0.
|
| 135 |
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"acc_stderr,none": 0.
|
| 136 |
"alias": " - blimp_existential_there_subject_raising"
|
| 137 |
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|
| 138 |
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|
| 139 |
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"acc,none": 0.
|
| 140 |
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"acc_stderr,none": 0.
|
| 141 |
"alias": " - blimp_expletive_it_object_raising"
|
| 142 |
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|
| 143 |
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|
| 144 |
-
"acc,none": 0.
|
| 145 |
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"acc_stderr,none": 0.
|
| 146 |
"alias": " - blimp_inchoative"
|
| 147 |
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|
| 148 |
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|
| 149 |
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"acc,none": 0.
|
| 150 |
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"acc_stderr,none": 0.
|
| 151 |
"alias": " - blimp_intransitive"
|
| 152 |
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|
| 153 |
"blimp_irregular_past_participle_adjectives": {
|
|
@@ -156,68 +156,68 @@
|
|
| 156 |
"alias": " - blimp_irregular_past_participle_adjectives"
|
| 157 |
},
|
| 158 |
"blimp_irregular_past_participle_verbs": {
|
| 159 |
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"acc,none": 0.
|
| 160 |
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"acc_stderr,none": 0.
|
| 161 |
"alias": " - blimp_irregular_past_participle_verbs"
|
| 162 |
},
|
| 163 |
"blimp_irregular_plural_subject_verb_agreement_1": {
|
| 164 |
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"acc,none": 0.
|
| 165 |
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"acc_stderr,none": 0.
|
| 166 |
"alias": " - blimp_irregular_plural_subject_verb_agreement_1"
|
| 167 |
},
|
| 168 |
"blimp_irregular_plural_subject_verb_agreement_2": {
|
| 169 |
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"acc,none": 0.
|
| 170 |
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"acc_stderr,none": 0.
|
| 171 |
"alias": " - blimp_irregular_plural_subject_verb_agreement_2"
|
| 172 |
},
|
| 173 |
"blimp_left_branch_island_echo_question": {
|
| 174 |
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"acc,none": 0.
|
| 175 |
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"acc_stderr,none": 0.
|
| 176 |
"alias": " - blimp_left_branch_island_echo_question"
|
| 177 |
},
|
| 178 |
"blimp_left_branch_island_simple_question": {
|
| 179 |
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"acc,none": 0.
|
| 180 |
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"acc_stderr,none": 0.
|
| 181 |
"alias": " - blimp_left_branch_island_simple_question"
|
| 182 |
},
|
| 183 |
"blimp_matrix_question_npi_licensor_present": {
|
| 184 |
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"acc,none": 0.
|
| 185 |
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|
| 186 |
"alias": " - blimp_matrix_question_npi_licensor_present"
|
| 187 |
},
|
| 188 |
"blimp_npi_present_1": {
|
| 189 |
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"acc,none": 0.
|
| 190 |
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"acc_stderr,none": 0.
|
| 191 |
"alias": " - blimp_npi_present_1"
|
| 192 |
},
|
| 193 |
"blimp_npi_present_2": {
|
| 194 |
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"acc,none": 0.
|
| 195 |
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"acc_stderr,none": 0.
|
| 196 |
"alias": " - blimp_npi_present_2"
|
| 197 |
},
|
| 198 |
"blimp_only_npi_licensor_present": {
|
| 199 |
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"acc,none": 0.
|
| 200 |
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"acc_stderr,none": 0.
|
| 201 |
"alias": " - blimp_only_npi_licensor_present"
|
| 202 |
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|
| 203 |
"blimp_only_npi_scope": {
|
| 204 |
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"acc,none": 0.
|
| 205 |
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"acc_stderr,none": 0.
|
| 206 |
"alias": " - blimp_only_npi_scope"
|
| 207 |
},
|
| 208 |
"blimp_passive_1": {
|
| 209 |
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"acc,none": 0.
|
| 210 |
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|
| 211 |
"alias": " - blimp_passive_1"
|
| 212 |
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|
| 213 |
"blimp_passive_2": {
|
| 214 |
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"acc,none": 0.
|
| 215 |
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"acc_stderr,none": 0.
|
| 216 |
"alias": " - blimp_passive_2"
|
| 217 |
},
|
| 218 |
"blimp_principle_A_c_command": {
|
| 219 |
-
"acc,none": 0.
|
| 220 |
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"acc_stderr,none": 0.
|
| 221 |
"alias": " - blimp_principle_A_c_command"
|
| 222 |
},
|
| 223 |
"blimp_principle_A_case_1": {
|
|
@@ -226,23 +226,23 @@
|
|
| 226 |
"alias": " - blimp_principle_A_case_1"
|
| 227 |
},
|
| 228 |
"blimp_principle_A_case_2": {
|
| 229 |
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"acc,none": 0.
|
| 230 |
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"acc_stderr,none": 0.
|
| 231 |
"alias": " - blimp_principle_A_case_2"
|
| 232 |
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|
| 233 |
"blimp_principle_A_domain_1": {
|
| 234 |
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"acc,none": 0.
|
| 235 |
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|
| 236 |
"alias": " - blimp_principle_A_domain_1"
|
| 237 |
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|
| 238 |
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|
| 239 |
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"acc,none": 0.
|
| 240 |
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|
| 241 |
"alias": " - blimp_principle_A_domain_2"
|
| 242 |
},
|
| 243 |
"blimp_principle_A_domain_3": {
|
| 244 |
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"acc,none": 0.
|
| 245 |
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"acc_stderr,none": 0.
|
| 246 |
"alias": " - blimp_principle_A_domain_3"
|
| 247 |
},
|
| 248 |
"blimp_principle_A_reconstruction": {
|
|
@@ -251,13 +251,13 @@
|
|
| 251 |
"alias": " - blimp_principle_A_reconstruction"
|
| 252 |
},
|
| 253 |
"blimp_regular_plural_subject_verb_agreement_1": {
|
| 254 |
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"acc,none": 0.
|
| 255 |
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"acc_stderr,none": 0.
|
| 256 |
"alias": " - blimp_regular_plural_subject_verb_agreement_1"
|
| 257 |
},
|
| 258 |
"blimp_regular_plural_subject_verb_agreement_2": {
|
| 259 |
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"acc,none": 0.
|
| 260 |
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"acc_stderr,none": 0.
|
| 261 |
"alias": " - blimp_regular_plural_subject_verb_agreement_2"
|
| 262 |
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|
| 263 |
"blimp_sentential_negation_npi_licensor_present": {
|
|
@@ -266,73 +266,73 @@
|
|
| 266 |
"alias": " - blimp_sentential_negation_npi_licensor_present"
|
| 267 |
},
|
| 268 |
"blimp_sentential_negation_npi_scope": {
|
| 269 |
-
"acc,none": 0.
|
| 270 |
-
"acc_stderr,none": 0.
|
| 271 |
"alias": " - blimp_sentential_negation_npi_scope"
|
| 272 |
},
|
| 273 |
"blimp_sentential_subject_island": {
|
| 274 |
-
"acc,none": 0.
|
| 275 |
-
"acc_stderr,none": 0.
|
| 276 |
"alias": " - blimp_sentential_subject_island"
|
| 277 |
},
|
| 278 |
"blimp_superlative_quantifiers_1": {
|
| 279 |
-
"acc,none": 0.
|
| 280 |
-
"acc_stderr,none": 0.
|
| 281 |
"alias": " - blimp_superlative_quantifiers_1"
|
| 282 |
},
|
| 283 |
"blimp_superlative_quantifiers_2": {
|
| 284 |
-
"acc,none": 0.
|
| 285 |
-
"acc_stderr,none": 0.
|
| 286 |
"alias": " - blimp_superlative_quantifiers_2"
|
| 287 |
},
|
| 288 |
"blimp_tough_vs_raising_1": {
|
| 289 |
-
"acc,none": 0.
|
| 290 |
-
"acc_stderr,none": 0.
|
| 291 |
"alias": " - blimp_tough_vs_raising_1"
|
| 292 |
},
|
| 293 |
"blimp_tough_vs_raising_2": {
|
| 294 |
-
"acc,none": 0.
|
| 295 |
-
"acc_stderr,none": 0.
|
| 296 |
"alias": " - blimp_tough_vs_raising_2"
|
| 297 |
},
|
| 298 |
"blimp_transitive": {
|
| 299 |
-
"acc,none": 0.
|
| 300 |
-
"acc_stderr,none": 0.
|
| 301 |
"alias": " - blimp_transitive"
|
| 302 |
},
|
| 303 |
"blimp_wh_island": {
|
| 304 |
-
"acc,none": 0.
|
| 305 |
-
"acc_stderr,none": 0.
|
| 306 |
"alias": " - blimp_wh_island"
|
| 307 |
},
|
| 308 |
"blimp_wh_questions_object_gap": {
|
| 309 |
-
"acc,none": 0.
|
| 310 |
-
"acc_stderr,none": 0.
|
| 311 |
"alias": " - blimp_wh_questions_object_gap"
|
| 312 |
},
|
| 313 |
"blimp_wh_questions_subject_gap": {
|
| 314 |
-
"acc,none": 0.
|
| 315 |
-
"acc_stderr,none": 0.
|
| 316 |
"alias": " - blimp_wh_questions_subject_gap"
|
| 317 |
},
|
| 318 |
"blimp_wh_questions_subject_gap_long_distance": {
|
| 319 |
-
"acc,none": 0.
|
| 320 |
-
"acc_stderr,none": 0.
|
| 321 |
"alias": " - blimp_wh_questions_subject_gap_long_distance"
|
| 322 |
},
|
| 323 |
"blimp_wh_vs_that_no_gap": {
|
| 324 |
-
"acc,none": 0.
|
| 325 |
-
"acc_stderr,none": 0.
|
| 326 |
"alias": " - blimp_wh_vs_that_no_gap"
|
| 327 |
},
|
| 328 |
"blimp_wh_vs_that_no_gap_long_distance": {
|
| 329 |
-
"acc,none": 0.
|
| 330 |
-
"acc_stderr,none": 0.
|
| 331 |
"alias": " - blimp_wh_vs_that_no_gap_long_distance"
|
| 332 |
},
|
| 333 |
"blimp_wh_vs_that_with_gap": {
|
| 334 |
-
"acc,none": 0.
|
| 335 |
-
"acc_stderr,none": 0.
|
| 336 |
"alias": " - blimp_wh_vs_that_with_gap"
|
| 337 |
},
|
| 338 |
"blimp_wh_vs_that_with_gap_long_distance": {
|
|
@@ -343,8 +343,8 @@
|
|
| 343 |
},
|
| 344 |
"groups": {
|
| 345 |
"blimp": {
|
| 346 |
-
"acc,none": 0.
|
| 347 |
-
"acc_stderr,none": 0.
|
| 348 |
"alias": "blimp"
|
| 349 |
}
|
| 350 |
},
|
|
@@ -2235,13 +2235,15 @@
|
|
| 2235 |
"config": {
|
| 2236 |
"model": "hf",
|
| 2237 |
"model_args": "pretrained=allenai/OLMo-7B,dtype=bfloat16,trust_remote_code=True",
|
| 2238 |
-
"batch_size": "
|
| 2239 |
-
"batch_sizes": [
|
|
|
|
|
|
|
| 2240 |
"device": null,
|
| 2241 |
"use_cache": null,
|
| 2242 |
"limit": null,
|
| 2243 |
"bootstrap_iters": 100000,
|
| 2244 |
"gen_kwargs": null
|
| 2245 |
},
|
| 2246 |
-
"git_hash": "
|
| 2247 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"results": {
|
| 3 |
"blimp": {
|
| 4 |
+
"acc,none": 0.8316865671641791,
|
| 5 |
+
"acc_stderr,none": 0.1603584899107365,
|
| 6 |
"alias": "blimp"
|
| 7 |
},
|
| 8 |
"blimp_adjunct_island": {
|
| 9 |
+
"acc,none": 0.904,
|
| 10 |
+
"acc_stderr,none": 0.009320454434783215,
|
| 11 |
"alias": " - blimp_adjunct_island"
|
| 12 |
},
|
| 13 |
"blimp_anaphor_gender_agreement": {
|
|
|
|
| 16 |
"alias": " - blimp_anaphor_gender_agreement"
|
| 17 |
},
|
| 18 |
"blimp_anaphor_number_agreement": {
|
| 19 |
+
"acc,none": 0.994,
|
| 20 |
+
"acc_stderr,none": 0.0024433521993298428,
|
| 21 |
"alias": " - blimp_anaphor_number_agreement"
|
| 22 |
},
|
| 23 |
"blimp_animate_subject_passive": {
|
| 24 |
+
"acc,none": 0.807,
|
| 25 |
+
"acc_stderr,none": 0.012486268734370145,
|
| 26 |
"alias": " - blimp_animate_subject_passive"
|
| 27 |
},
|
| 28 |
"blimp_animate_subject_trans": {
|
| 29 |
+
"acc,none": 0.913,
|
| 30 |
+
"acc_stderr,none": 0.008916866630745918,
|
| 31 |
"alias": " - blimp_animate_subject_trans"
|
| 32 |
},
|
| 33 |
"blimp_causative": {
|
| 34 |
+
"acc,none": 0.728,
|
| 35 |
+
"acc_stderr,none": 0.014078856992462623,
|
| 36 |
"alias": " - blimp_causative"
|
| 37 |
},
|
| 38 |
"blimp_complex_NP_island": {
|
|
|
|
| 41 |
"alias": " - blimp_complex_NP_island"
|
| 42 |
},
|
| 43 |
"blimp_coordinate_structure_constraint_complex_left_branch": {
|
| 44 |
+
"acc,none": 0.82,
|
| 45 |
+
"acc_stderr,none": 0.012155153135511949,
|
| 46 |
"alias": " - blimp_coordinate_structure_constraint_complex_left_branch"
|
| 47 |
},
|
| 48 |
"blimp_coordinate_structure_constraint_object_extraction": {
|
| 49 |
+
"acc,none": 0.891,
|
| 50 |
+
"acc_stderr,none": 0.009859828407037188,
|
| 51 |
"alias": " - blimp_coordinate_structure_constraint_object_extraction"
|
| 52 |
},
|
| 53 |
"blimp_determiner_noun_agreement_1": {
|
| 54 |
"acc,none": 0.986,
|
| 55 |
+
"acc_stderr,none": 0.0037172325482565877,
|
| 56 |
"alias": " - blimp_determiner_noun_agreement_1"
|
| 57 |
},
|
| 58 |
"blimp_determiner_noun_agreement_2": {
|
| 59 |
+
"acc,none": 0.973,
|
| 60 |
+
"acc_stderr,none": 0.005128089049275288,
|
| 61 |
"alias": " - blimp_determiner_noun_agreement_2"
|
| 62 |
},
|
| 63 |
"blimp_determiner_noun_agreement_irregular_1": {
|
| 64 |
+
"acc,none": 0.933,
|
| 65 |
+
"acc_stderr,none": 0.00791034598317755,
|
| 66 |
"alias": " - blimp_determiner_noun_agreement_irregular_1"
|
| 67 |
},
|
| 68 |
"blimp_determiner_noun_agreement_irregular_2": {
|
| 69 |
+
"acc,none": 0.954,
|
| 70 |
+
"acc_stderr,none": 0.006627814717380719,
|
| 71 |
"alias": " - blimp_determiner_noun_agreement_irregular_2"
|
| 72 |
},
|
| 73 |
"blimp_determiner_noun_agreement_with_adj_2": {
|
| 74 |
+
"acc,none": 0.95,
|
| 75 |
+
"acc_stderr,none": 0.0068954729748979,
|
| 76 |
"alias": " - blimp_determiner_noun_agreement_with_adj_2"
|
| 77 |
},
|
| 78 |
"blimp_determiner_noun_agreement_with_adj_irregular_1": {
|
| 79 |
+
"acc,none": 0.879,
|
| 80 |
+
"acc_stderr,none": 0.010318210380946088,
|
| 81 |
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_1"
|
| 82 |
},
|
| 83 |
"blimp_determiner_noun_agreement_with_adj_irregular_2": {
|
| 84 |
+
"acc,none": 0.931,
|
| 85 |
+
"acc_stderr,none": 0.00801893405031516,
|
| 86 |
"alias": " - blimp_determiner_noun_agreement_with_adj_irregular_2"
|
| 87 |
},
|
| 88 |
"blimp_determiner_noun_agreement_with_adjective_1": {
|
| 89 |
+
"acc,none": 0.973,
|
| 90 |
+
"acc_stderr,none": 0.00512808904927529,
|
| 91 |
"alias": " - blimp_determiner_noun_agreement_with_adjective_1"
|
| 92 |
},
|
| 93 |
"blimp_distractor_agreement_relational_noun": {
|
| 94 |
+
"acc,none": 0.923,
|
| 95 |
+
"acc_stderr,none": 0.008434580140240648,
|
| 96 |
"alias": " - blimp_distractor_agreement_relational_noun"
|
| 97 |
},
|
| 98 |
"blimp_distractor_agreement_relative_clause": {
|
| 99 |
+
"acc,none": 0.717,
|
| 100 |
+
"acc_stderr,none": 0.014251810906481728,
|
| 101 |
"alias": " - blimp_distractor_agreement_relative_clause"
|
| 102 |
},
|
| 103 |
"blimp_drop_argument": {
|
| 104 |
+
"acc,none": 0.747,
|
| 105 |
+
"acc_stderr,none": 0.01375427861358708,
|
| 106 |
"alias": " - blimp_drop_argument"
|
| 107 |
},
|
| 108 |
"blimp_ellipsis_n_bar_1": {
|
| 109 |
"acc,none": 0.812,
|
| 110 |
+
"acc_stderr,none": 0.012361586015103744,
|
| 111 |
"alias": " - blimp_ellipsis_n_bar_1"
|
| 112 |
},
|
| 113 |
"blimp_ellipsis_n_bar_2": {
|
| 114 |
+
"acc,none": 0.949,
|
| 115 |
+
"acc_stderr,none": 0.006960420062571421,
|
| 116 |
"alias": " - blimp_ellipsis_n_bar_2"
|
| 117 |
},
|
| 118 |
"blimp_existential_there_object_raising": {
|
| 119 |
+
"acc,none": 0.864,
|
| 120 |
+
"acc_stderr,none": 0.010845350230472988,
|
| 121 |
"alias": " - blimp_existential_there_object_raising"
|
| 122 |
},
|
| 123 |
"blimp_existential_there_quantifiers_1": {
|
| 124 |
+
"acc,none": 0.985,
|
| 125 |
+
"acc_stderr,none": 0.0038457495745030067,
|
| 126 |
"alias": " - blimp_existential_there_quantifiers_1"
|
| 127 |
},
|
| 128 |
"blimp_existential_there_quantifiers_2": {
|
| 129 |
"acc,none": 0.377,
|
| 130 |
+
"acc_stderr,none": 0.015333170125779847,
|
| 131 |
"alias": " - blimp_existential_there_quantifiers_2"
|
| 132 |
},
|
| 133 |
"blimp_existential_there_subject_raising": {
|
| 134 |
+
"acc,none": 0.911,
|
| 135 |
+
"acc_stderr,none": 0.009008893392651523,
|
| 136 |
"alias": " - blimp_existential_there_subject_raising"
|
| 137 |
},
|
| 138 |
"blimp_expletive_it_object_raising": {
|
| 139 |
+
"acc,none": 0.826,
|
| 140 |
+
"acc_stderr,none": 0.01199449323097343,
|
| 141 |
"alias": " - blimp_expletive_it_object_raising"
|
| 142 |
},
|
| 143 |
"blimp_inchoative": {
|
| 144 |
+
"acc,none": 0.68,
|
| 145 |
+
"acc_stderr,none": 0.014758652303574874,
|
| 146 |
"alias": " - blimp_inchoative"
|
| 147 |
},
|
| 148 |
"blimp_intransitive": {
|
| 149 |
+
"acc,none": 0.791,
|
| 150 |
+
"acc_stderr,none": 0.012864077288499321,
|
| 151 |
"alias": " - blimp_intransitive"
|
| 152 |
},
|
| 153 |
"blimp_irregular_past_participle_adjectives": {
|
|
|
|
| 156 |
"alias": " - blimp_irregular_past_participle_adjectives"
|
| 157 |
},
|
| 158 |
"blimp_irregular_past_participle_verbs": {
|
| 159 |
+
"acc,none": 0.906,
|
| 160 |
+
"acc_stderr,none": 0.009233052000787736,
|
| 161 |
"alias": " - blimp_irregular_past_participle_verbs"
|
| 162 |
},
|
| 163 |
"blimp_irregular_plural_subject_verb_agreement_1": {
|
| 164 |
+
"acc,none": 0.928,
|
| 165 |
+
"acc_stderr,none": 0.008178195576218681,
|
| 166 |
"alias": " - blimp_irregular_plural_subject_verb_agreement_1"
|
| 167 |
},
|
| 168 |
"blimp_irregular_plural_subject_verb_agreement_2": {
|
| 169 |
+
"acc,none": 0.932,
|
| 170 |
+
"acc_stderr,none": 0.007964887911291603,
|
| 171 |
"alias": " - blimp_irregular_plural_subject_verb_agreement_2"
|
| 172 |
},
|
| 173 |
"blimp_left_branch_island_echo_question": {
|
| 174 |
+
"acc,none": 0.648,
|
| 175 |
+
"acc_stderr,none": 0.015110404505648661,
|
| 176 |
"alias": " - blimp_left_branch_island_echo_question"
|
| 177 |
},
|
| 178 |
"blimp_left_branch_island_simple_question": {
|
| 179 |
+
"acc,none": 0.911,
|
| 180 |
+
"acc_stderr,none": 0.009008893392651526,
|
| 181 |
"alias": " - blimp_left_branch_island_simple_question"
|
| 182 |
},
|
| 183 |
"blimp_matrix_question_npi_licensor_present": {
|
| 184 |
+
"acc,none": 0.607,
|
| 185 |
+
"acc_stderr,none": 0.015452824654081496,
|
| 186 |
"alias": " - blimp_matrix_question_npi_licensor_present"
|
| 187 |
},
|
| 188 |
"blimp_npi_present_1": {
|
| 189 |
+
"acc,none": 0.674,
|
| 190 |
+
"acc_stderr,none": 0.014830507204541038,
|
| 191 |
"alias": " - blimp_npi_present_1"
|
| 192 |
},
|
| 193 |
"blimp_npi_present_2": {
|
| 194 |
+
"acc,none": 0.73,
|
| 195 |
+
"acc_stderr,none": 0.014046255632633915,
|
| 196 |
"alias": " - blimp_npi_present_2"
|
| 197 |
},
|
| 198 |
"blimp_only_npi_licensor_present": {
|
| 199 |
+
"acc,none": 0.974,
|
| 200 |
+
"acc_stderr,none": 0.005034813735318216,
|
| 201 |
"alias": " - blimp_only_npi_licensor_present"
|
| 202 |
},
|
| 203 |
"blimp_only_npi_scope": {
|
| 204 |
+
"acc,none": 0.706,
|
| 205 |
+
"acc_stderr,none": 0.01441429054000822,
|
| 206 |
"alias": " - blimp_only_npi_scope"
|
| 207 |
},
|
| 208 |
"blimp_passive_1": {
|
| 209 |
+
"acc,none": 0.895,
|
| 210 |
+
"acc_stderr,none": 0.009698921026024971,
|
| 211 |
"alias": " - blimp_passive_1"
|
| 212 |
},
|
| 213 |
"blimp_passive_2": {
|
| 214 |
+
"acc,none": 0.906,
|
| 215 |
+
"acc_stderr,none": 0.009233052000787728,
|
| 216 |
"alias": " - blimp_passive_2"
|
| 217 |
},
|
| 218 |
"blimp_principle_A_c_command": {
|
| 219 |
+
"acc,none": 0.741,
|
| 220 |
+
"acc_stderr,none": 0.01386041525752791,
|
| 221 |
"alias": " - blimp_principle_A_c_command"
|
| 222 |
},
|
| 223 |
"blimp_principle_A_case_1": {
|
|
|
|
| 226 |
"alias": " - blimp_principle_A_case_1"
|
| 227 |
},
|
| 228 |
"blimp_principle_A_case_2": {
|
| 229 |
+
"acc,none": 0.963,
|
| 230 |
+
"acc_stderr,none": 0.005972157622389646,
|
| 231 |
"alias": " - blimp_principle_A_case_2"
|
| 232 |
},
|
| 233 |
"blimp_principle_A_domain_1": {
|
| 234 |
+
"acc,none": 0.999,
|
| 235 |
+
"acc_stderr,none": 0.0010000000000000124,
|
| 236 |
"alias": " - blimp_principle_A_domain_1"
|
| 237 |
},
|
| 238 |
"blimp_principle_A_domain_2": {
|
| 239 |
+
"acc,none": 0.835,
|
| 240 |
+
"acc_stderr,none": 0.011743632866916164,
|
| 241 |
"alias": " - blimp_principle_A_domain_2"
|
| 242 |
},
|
| 243 |
"blimp_principle_A_domain_3": {
|
| 244 |
+
"acc,none": 0.739,
|
| 245 |
+
"acc_stderr,none": 0.013895037677965136,
|
| 246 |
"alias": " - blimp_principle_A_domain_3"
|
| 247 |
},
|
| 248 |
"blimp_principle_A_reconstruction": {
|
|
|
|
| 251 |
"alias": " - blimp_principle_A_reconstruction"
|
| 252 |
},
|
| 253 |
"blimp_regular_plural_subject_verb_agreement_1": {
|
| 254 |
+
"acc,none": 0.965,
|
| 255 |
+
"acc_stderr,none": 0.005814534272734963,
|
| 256 |
"alias": " - blimp_regular_plural_subject_verb_agreement_1"
|
| 257 |
},
|
| 258 |
"blimp_regular_plural_subject_verb_agreement_2": {
|
| 259 |
+
"acc,none": 0.931,
|
| 260 |
+
"acc_stderr,none": 0.008018934050315146,
|
| 261 |
"alias": " - blimp_regular_plural_subject_verb_agreement_2"
|
| 262 |
},
|
| 263 |
"blimp_sentential_negation_npi_licensor_present": {
|
|
|
|
| 266 |
"alias": " - blimp_sentential_negation_npi_licensor_present"
|
| 267 |
},
|
| 268 |
"blimp_sentential_negation_npi_scope": {
|
| 269 |
+
"acc,none": 0.759,
|
| 270 |
+
"acc_stderr,none": 0.013531522534515419,
|
| 271 |
"alias": " - blimp_sentential_negation_npi_scope"
|
| 272 |
},
|
| 273 |
"blimp_sentential_subject_island": {
|
| 274 |
+
"acc,none": 0.559,
|
| 275 |
+
"acc_stderr,none": 0.01570877989424268,
|
| 276 |
"alias": " - blimp_sentential_subject_island"
|
| 277 |
},
|
| 278 |
"blimp_superlative_quantifiers_1": {
|
| 279 |
+
"acc,none": 0.892,
|
| 280 |
+
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| 97 |
-
"acc_norm,none": 0.2857142857142857,
|
| 98 |
-
"acc_norm_stderr,none": 0.10101525445522108,
|
| 99 |
-
"alias": " - ceval-valid_computer_architecture"
|
| 100 |
-
},
|
| 101 |
-
"ceval-valid_computer_network": {
|
| 102 |
-
"acc,none": 0.42105263157894735,
|
| 103 |
-
"acc_stderr,none": 0.11637279966159299,
|
| 104 |
-
"acc_norm,none": 0.42105263157894735,
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| 105 |
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"acc_norm_stderr,none": 0.11637279966159299,
|
| 106 |
-
"alias": " - ceval-valid_computer_network"
|
| 107 |
-
},
|
| 108 |
-
"ceval-valid_discrete_mathematics": {
|
| 109 |
-
"acc,none": 0.1875,
|
| 110 |
-
"acc_stderr,none": 0.10077822185373188,
|
| 111 |
-
"acc_norm,none": 0.1875,
|
| 112 |
-
"acc_norm_stderr,none": 0.10077822185373188,
|
| 113 |
-
"alias": " - ceval-valid_discrete_mathematics"
|
| 114 |
-
},
|
| 115 |
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|
| 116 |
-
"acc,none": 0.2413793103448276,
|
| 117 |
-
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|
| 118 |
-
"acc_norm,none": 0.2413793103448276,
|
| 119 |
-
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|
| 120 |
-
"alias": " - ceval-valid_education_science"
|
| 121 |
-
},
|
| 122 |
-
"ceval-valid_electrical_engineer": {
|
| 123 |
-
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|
| 124 |
-
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|
| 125 |
-
"acc_norm,none": 0.35135135135135137,
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| 126 |
-
"acc_norm_stderr,none": 0.0795654132101608,
|
| 127 |
-
"alias": " - ceval-valid_electrical_engineer"
|
| 128 |
-
},
|
| 129 |
-
"ceval-valid_environmental_impact_assessment_engineer": {
|
| 130 |
-
"acc,none": 0.25806451612903225,
|
| 131 |
-
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|
| 132 |
-
"acc_norm,none": 0.25806451612903225,
|
| 133 |
-
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|
| 134 |
-
"alias": " - ceval-valid_environmental_impact_assessment_engineer"
|
| 135 |
-
},
|
| 136 |
-
"ceval-valid_fire_engineer": {
|
| 137 |
-
"acc,none": 0.22580645161290322,
|
| 138 |
-
"acc_stderr,none": 0.07633651333031763,
|
| 139 |
-
"acc_norm,none": 0.22580645161290322,
|
| 140 |
-
"acc_norm_stderr,none": 0.07633651333031763,
|
| 141 |
-
"alias": " - ceval-valid_fire_engineer"
|
| 142 |
-
},
|
| 143 |
-
"ceval-valid_high_school_biology": {
|
| 144 |
-
"acc,none": 0.21052631578947367,
|
| 145 |
-
"acc_stderr,none": 0.0960916767552923,
|
| 146 |
-
"acc_norm,none": 0.21052631578947367,
|
| 147 |
-
"acc_norm_stderr,none": 0.0960916767552923,
|
| 148 |
-
"alias": " - ceval-valid_high_school_biology"
|
| 149 |
-
},
|
| 150 |
-
"ceval-valid_high_school_chemistry": {
|
| 151 |
-
"acc,none": 0.3684210526315789,
|
| 152 |
-
"acc_stderr,none": 0.1136972052352256,
|
| 153 |
-
"acc_norm,none": 0.3684210526315789,
|
| 154 |
-
"acc_norm_stderr,none": 0.1136972052352256,
|
| 155 |
-
"alias": " - ceval-valid_high_school_chemistry"
|
| 156 |
-
},
|
| 157 |
-
"ceval-valid_high_school_chinese": {
|
| 158 |
-
"acc,none": 0.10526315789473684,
|
| 159 |
-
"acc_stderr,none": 0.0723351864143449,
|
| 160 |
-
"acc_norm,none": 0.10526315789473684,
|
| 161 |
-
"acc_norm_stderr,none": 0.0723351864143449,
|
| 162 |
-
"alias": " - ceval-valid_high_school_chinese"
|
| 163 |
-
},
|
| 164 |
-
"ceval-valid_high_school_geography": {
|
| 165 |
-
"acc,none": 0.3157894736842105,
|
| 166 |
-
"acc_stderr,none": 0.10956136839295434,
|
| 167 |
-
"acc_norm,none": 0.3157894736842105,
|
| 168 |
-
"acc_norm_stderr,none": 0.10956136839295434,
|
| 169 |
-
"alias": " - ceval-valid_high_school_geography"
|
| 170 |
-
},
|
| 171 |
-
"ceval-valid_high_school_history": {
|
| 172 |
-
"acc,none": 0.15,
|
| 173 |
-
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|
| 174 |
-
"acc_norm,none": 0.15,
|
| 175 |
-
"acc_norm_stderr,none": 0.0819178021909125,
|
| 176 |
-
"alias": " - ceval-valid_high_school_history"
|
| 177 |
-
},
|
| 178 |
-
"ceval-valid_high_school_mathematics": {
|
| 179 |
-
"acc,none": 0.2777777777777778,
|
| 180 |
-
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|
| 181 |
-
"acc_norm,none": 0.2777777777777778,
|
| 182 |
-
"acc_norm_stderr,none": 0.1086324845659782,
|
| 183 |
-
"alias": " - ceval-valid_high_school_mathematics"
|
| 184 |
-
},
|
| 185 |
-
"ceval-valid_high_school_physics": {
|
| 186 |
-
"acc,none": 0.3157894736842105,
|
| 187 |
-
"acc_stderr,none": 0.10956136839295433,
|
| 188 |
-
"acc_norm,none": 0.3157894736842105,
|
| 189 |
-
"acc_norm_stderr,none": 0.10956136839295433,
|
| 190 |
-
"alias": " - ceval-valid_high_school_physics"
|
| 191 |
-
},
|
| 192 |
-
"ceval-valid_high_school_politics": {
|
| 193 |
-
"acc,none": 0.10526315789473684,
|
| 194 |
-
"acc_stderr,none": 0.07233518641434492,
|
| 195 |
-
"acc_norm,none": 0.10526315789473684,
|
| 196 |
-
"acc_norm_stderr,none": 0.07233518641434492,
|
| 197 |
-
"alias": " - ceval-valid_high_school_politics"
|
| 198 |
-
},
|
| 199 |
-
"ceval-valid_ideological_and_moral_cultivation": {
|
| 200 |
-
"acc,none": 0.15789473684210525,
|
| 201 |
-
"acc_stderr,none": 0.08594700851870798,
|
| 202 |
-
"acc_norm,none": 0.15789473684210525,
|
| 203 |
-
"acc_norm_stderr,none": 0.08594700851870798,
|
| 204 |
-
"alias": " - ceval-valid_ideological_and_moral_cultivation"
|
| 205 |
-
},
|
| 206 |
-
"ceval-valid_law": {
|
| 207 |
-
"acc,none": 0.3333333333333333,
|
| 208 |
-
"acc_stderr,none": 0.0982946374365981,
|
| 209 |
-
"acc_norm,none": 0.3333333333333333,
|
| 210 |
-
"acc_norm_stderr,none": 0.0982946374365981,
|
| 211 |
-
"alias": " - ceval-valid_law"
|
| 212 |
-
},
|
| 213 |
-
"ceval-valid_legal_professional": {
|
| 214 |
-
"acc,none": 0.17391304347826086,
|
| 215 |
-
"acc_stderr,none": 0.08081046758996391,
|
| 216 |
-
"acc_norm,none": 0.17391304347826086,
|
| 217 |
-
"acc_norm_stderr,none": 0.08081046758996391,
|
| 218 |
-
"alias": " - ceval-valid_legal_professional"
|
| 219 |
-
},
|
| 220 |
-
"ceval-valid_logic": {
|
| 221 |
-
"acc,none": 0.22727272727272727,
|
| 222 |
-
"acc_stderr,none": 0.09144861547306321,
|
| 223 |
-
"acc_norm,none": 0.22727272727272727,
|
| 224 |
-
"acc_norm_stderr,none": 0.09144861547306321,
|
| 225 |
-
"alias": " - ceval-valid_logic"
|
| 226 |
-
},
|
| 227 |
-
"ceval-valid_mao_zedong_thought": {
|
| 228 |
-
"acc,none": 0.2916666666666667,
|
| 229 |
-
"acc_stderr,none": 0.09477598811252415,
|
| 230 |
-
"acc_norm,none": 0.2916666666666667,
|
| 231 |
-
"acc_norm_stderr,none": 0.09477598811252415,
|
| 232 |
-
"alias": " - ceval-valid_mao_zedong_thought"
|
| 233 |
-
},
|
| 234 |
-
"ceval-valid_marxism": {
|
| 235 |
-
"acc,none": 0.21052631578947367,
|
| 236 |
-
"acc_stderr,none": 0.0960916767552923,
|
| 237 |
-
"acc_norm,none": 0.21052631578947367,
|
| 238 |
-
"acc_norm_stderr,none": 0.0960916767552923,
|
| 239 |
-
"alias": " - ceval-valid_marxism"
|
| 240 |
-
},
|
| 241 |
-
"ceval-valid_metrology_engineer": {
|
| 242 |
-
"acc,none": 0.25,
|
| 243 |
-
"acc_stderr,none": 0.09028938981432691,
|
| 244 |
-
"acc_norm,none": 0.25,
|
| 245 |
-
"acc_norm_stderr,none": 0.09028938981432691,
|
| 246 |
-
"alias": " - ceval-valid_metrology_engineer"
|
| 247 |
-
},
|
| 248 |
-
"ceval-valid_middle_school_biology": {
|
| 249 |
-
"acc,none": 0.23809523809523808,
|
| 250 |
-
"acc_stderr,none": 0.09523809523809523,
|
| 251 |
-
"acc_norm,none": 0.23809523809523808,
|
| 252 |
-
"acc_norm_stderr,none": 0.09523809523809523,
|
| 253 |
-
"alias": " - ceval-valid_middle_school_biology"
|
| 254 |
-
},
|
| 255 |
-
"ceval-valid_middle_school_chemistry": {
|
| 256 |
-
"acc,none": 0.25,
|
| 257 |
-
"acc_stderr,none": 0.09933992677987828,
|
| 258 |
-
"acc_norm,none": 0.25,
|
| 259 |
-
"acc_norm_stderr,none": 0.09933992677987828,
|
| 260 |
-
"alias": " - ceval-valid_middle_school_chemistry"
|
| 261 |
-
},
|
| 262 |
-
"ceval-valid_middle_school_geography": {
|
| 263 |
-
"acc,none": 0.08333333333333333,
|
| 264 |
-
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|
| 265 |
-
"acc_norm,none": 0.08333333333333333,
|
| 266 |
-
"acc_norm_stderr,none": 0.08333333333333331,
|
| 267 |
-
"alias": " - ceval-valid_middle_school_geography"
|
| 268 |
-
},
|
| 269 |
-
"ceval-valid_middle_school_history": {
|
| 270 |
-
"acc,none": 0.45454545454545453,
|
| 271 |
-
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|
| 272 |
-
"acc_norm,none": 0.45454545454545453,
|
| 273 |
-
"acc_norm_stderr,none": 0.10865714630312667,
|
| 274 |
-
"alias": " - ceval-valid_middle_school_history"
|
| 275 |
-
},
|
| 276 |
-
"ceval-valid_middle_school_mathematics": {
|
| 277 |
-
"acc,none": 0.3684210526315789,
|
| 278 |
-
"acc_stderr,none": 0.11369720523522558,
|
| 279 |
-
"acc_norm,none": 0.3684210526315789,
|
| 280 |
-
"acc_norm_stderr,none": 0.11369720523522558,
|
| 281 |
-
"alias": " - ceval-valid_middle_school_mathematics"
|
| 282 |
-
},
|
| 283 |
-
"ceval-valid_middle_school_physics": {
|
| 284 |
-
"acc,none": 0.47368421052631576,
|
| 285 |
-
"acc_stderr,none": 0.11768778828946262,
|
| 286 |
-
"acc_norm,none": 0.47368421052631576,
|
| 287 |
-
"acc_norm_stderr,none": 0.11768778828946262,
|
| 288 |
-
"alias": " - ceval-valid_middle_school_physics"
|
| 289 |
-
},
|
| 290 |
-
"ceval-valid_middle_school_politics": {
|
| 291 |
-
"acc,none": 0.2857142857142857,
|
| 292 |
-
"acc_stderr,none": 0.10101525445522108,
|
| 293 |
-
"acc_norm,none": 0.2857142857142857,
|
| 294 |
-
"acc_norm_stderr,none": 0.10101525445522108,
|
| 295 |
-
"alias": " - ceval-valid_middle_school_politics"
|
| 296 |
-
},
|
| 297 |
-
"ceval-valid_modern_chinese_history": {
|
| 298 |
-
"acc,none": 0.21739130434782608,
|
| 299 |
-
"acc_stderr,none": 0.08793911249520547,
|
| 300 |
-
"acc_norm,none": 0.21739130434782608,
|
| 301 |
-
"acc_norm_stderr,none": 0.08793911249520547,
|
| 302 |
-
"alias": " - ceval-valid_modern_chinese_history"
|
| 303 |
-
},
|
| 304 |
-
"ceval-valid_operating_system": {
|
| 305 |
-
"acc,none": 0.10526315789473684,
|
| 306 |
-
"acc_stderr,none": 0.07233518641434492,
|
| 307 |
-
"acc_norm,none": 0.10526315789473684,
|
| 308 |
-
"acc_norm_stderr,none": 0.07233518641434492,
|
| 309 |
-
"alias": " - ceval-valid_operating_system"
|
| 310 |
-
},
|
| 311 |
-
"ceval-valid_physician": {
|
| 312 |
-
"acc,none": 0.20408163265306123,
|
| 313 |
-
"acc_stderr,none": 0.05817221556628253,
|
| 314 |
-
"acc_norm,none": 0.20408163265306123,
|
| 315 |
-
"acc_norm_stderr,none": 0.05817221556628253,
|
| 316 |
-
"alias": " - ceval-valid_physician"
|
| 317 |
-
},
|
| 318 |
-
"ceval-valid_plant_protection": {
|
| 319 |
-
"acc,none": 0.3181818181818182,
|
| 320 |
-
"acc_stderr,none": 0.10163945352271771,
|
| 321 |
-
"acc_norm,none": 0.3181818181818182,
|
| 322 |
-
"acc_norm_stderr,none": 0.10163945352271771,
|
| 323 |
-
"alias": " - ceval-valid_plant_protection"
|
| 324 |
-
},
|
| 325 |
-
"ceval-valid_probability_and_statistics": {
|
| 326 |
-
"acc,none": 0.2222222222222222,
|
| 327 |
-
"acc_stderr,none": 0.1008316903303367,
|
| 328 |
-
"acc_norm,none": 0.2222222222222222,
|
| 329 |
-
"acc_norm_stderr,none": 0.1008316903303367,
|
| 330 |
-
"alias": " - ceval-valid_probability_and_statistics"
|
| 331 |
-
},
|
| 332 |
-
"ceval-valid_professional_tour_guide": {
|
| 333 |
-
"acc,none": 0.4482758620689655,
|
| 334 |
-
"acc_stderr,none": 0.09398415777506855,
|
| 335 |
-
"acc_norm,none": 0.4482758620689655,
|
| 336 |
-
"acc_norm_stderr,none": 0.09398415777506855,
|
| 337 |
-
"alias": " - ceval-valid_professional_tour_guide"
|
| 338 |
-
},
|
| 339 |
-
"ceval-valid_sports_science": {
|
| 340 |
-
"acc,none": 0.15789473684210525,
|
| 341 |
-
"acc_stderr,none": 0.08594700851870798,
|
| 342 |
-
"acc_norm,none": 0.15789473684210525,
|
| 343 |
-
"acc_norm_stderr,none": 0.08594700851870798,
|
| 344 |
-
"alias": " - ceval-valid_sports_science"
|
| 345 |
-
},
|
| 346 |
-
"ceval-valid_tax_accountant": {
|
| 347 |
-
"acc,none": 0.24489795918367346,
|
| 348 |
-
"acc_stderr,none": 0.062069005411206316,
|
| 349 |
-
"acc_norm,none": 0.24489795918367346,
|
| 350 |
-
"acc_norm_stderr,none": 0.062069005411206316,
|
| 351 |
-
"alias": " - ceval-valid_tax_accountant"
|
| 352 |
-
},
|
| 353 |
-
"ceval-valid_teacher_qualification": {
|
| 354 |
-
"acc,none": 0.22727272727272727,
|
| 355 |
-
"acc_stderr,none": 0.06390760676613884,
|
| 356 |
-
"acc_norm,none": 0.22727272727272727,
|
| 357 |
-
"acc_norm_stderr,none": 0.06390760676613884,
|
| 358 |
-
"alias": " - ceval-valid_teacher_qualification"
|
| 359 |
-
},
|
| 360 |
-
"ceval-valid_urban_and_rural_planner": {
|
| 361 |
-
"acc,none": 0.21739130434782608,
|
| 362 |
-
"acc_stderr,none": 0.06148754619013454,
|
| 363 |
-
"acc_norm,none": 0.21739130434782608,
|
| 364 |
-
"acc_norm_stderr,none": 0.06148754619013454,
|
| 365 |
-
"alias": " - ceval-valid_urban_and_rural_planner"
|
| 366 |
-
},
|
| 367 |
-
"ceval-valid_veterinary_medicine": {
|
| 368 |
-
"acc,none": 0.13043478260869565,
|
| 369 |
-
"acc_stderr,none": 0.07180198468215394,
|
| 370 |
-
"acc_norm,none": 0.13043478260869565,
|
| 371 |
-
"acc_norm_stderr,none": 0.07180198468215394,
|
| 372 |
-
"alias": " - ceval-valid_veterinary_medicine"
|
| 373 |
-
}
|
| 374 |
-
},
|
| 375 |
-
"groups": {
|
| 376 |
-
"ceval-valid": {
|
| 377 |
-
"acc,none": 0.24962852897473997,
|
| 378 |
-
"acc_stderr,none": 0.11387085890117267,
|
| 379 |
-
"acc_norm,none": 0.24962852897473997,
|
| 380 |
-
"acc_norm_stderr,none": 0.11387085890117267,
|
| 381 |
-
"alias": "ceval-valid"
|
| 382 |
-
}
|
| 383 |
-
},
|
| 384 |
-
"configs": {
|
| 385 |
-
"ceval-valid_accountant": {
|
| 386 |
-
"task": "ceval-valid_accountant",
|
| 387 |
-
"group": "ceval-valid",
|
| 388 |
-
"dataset_path": "ceval/ceval-exam",
|
| 389 |
-
"dataset_name": "accountant",
|
| 390 |
-
"validation_split": "val",
|
| 391 |
-
"fewshot_split": "dev",
|
| 392 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 393 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 394 |
-
"doc_to_choice": [
|
| 395 |
-
"A",
|
| 396 |
-
"B",
|
| 397 |
-
"C",
|
| 398 |
-
"D"
|
| 399 |
-
],
|
| 400 |
-
"description": "以下是中国关于注册会计师的单项选择题，请选出其中的正确答案。\n\n",
|
| 401 |
-
"target_delimiter": " ",
|
| 402 |
-
"fewshot_delimiter": "\n\n",
|
| 403 |
-
"fewshot_config": {
|
| 404 |
-
"sampler": "first_n"
|
| 405 |
-
},
|
| 406 |
-
"metric_list": [
|
| 407 |
-
{
|
| 408 |
-
"metric": "acc",
|
| 409 |
-
"aggregation": "mean",
|
| 410 |
-
"higher_is_better": true
|
| 411 |
-
},
|
| 412 |
-
{
|
| 413 |
-
"metric": "acc_norm",
|
| 414 |
-
"aggregation": "mean",
|
| 415 |
-
"higher_is_better": true
|
| 416 |
-
}
|
| 417 |
-
],
|
| 418 |
-
"output_type": "multiple_choice",
|
| 419 |
-
"repeats": 1,
|
| 420 |
-
"should_decontaminate": false,
|
| 421 |
-
"metadata": {
|
| 422 |
-
"version": 1.0
|
| 423 |
-
}
|
| 424 |
-
},
|
| 425 |
-
"ceval-valid_advanced_mathematics": {
|
| 426 |
-
"task": "ceval-valid_advanced_mathematics",
|
| 427 |
-
"group": "ceval-valid",
|
| 428 |
-
"dataset_path": "ceval/ceval-exam",
|
| 429 |
-
"dataset_name": "advanced_mathematics",
|
| 430 |
-
"validation_split": "val",
|
| 431 |
-
"fewshot_split": "dev",
|
| 432 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 433 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 434 |
-
"doc_to_choice": [
|
| 435 |
-
"A",
|
| 436 |
-
"B",
|
| 437 |
-
"C",
|
| 438 |
-
"D"
|
| 439 |
-
],
|
| 440 |
-
"description": "以下是中国关于高等数学的单项选择题，请选出其中的正确答案。\n\n",
|
| 441 |
-
"target_delimiter": " ",
|
| 442 |
-
"fewshot_delimiter": "\n\n",
|
| 443 |
-
"fewshot_config": {
|
| 444 |
-
"sampler": "first_n"
|
| 445 |
-
},
|
| 446 |
-
"metric_list": [
|
| 447 |
-
{
|
| 448 |
-
"metric": "acc",
|
| 449 |
-
"aggregation": "mean",
|
| 450 |
-
"higher_is_better": true
|
| 451 |
-
},
|
| 452 |
-
{
|
| 453 |
-
"metric": "acc_norm",
|
| 454 |
-
"aggregation": "mean",
|
| 455 |
-
"higher_is_better": true
|
| 456 |
-
}
|
| 457 |
-
],
|
| 458 |
-
"output_type": "multiple_choice",
|
| 459 |
-
"repeats": 1,
|
| 460 |
-
"should_decontaminate": false,
|
| 461 |
-
"metadata": {
|
| 462 |
-
"version": 1.0
|
| 463 |
-
}
|
| 464 |
-
},
|
| 465 |
-
"ceval-valid_art_studies": {
|
| 466 |
-
"task": "ceval-valid_art_studies",
|
| 467 |
-
"group": "ceval-valid",
|
| 468 |
-
"dataset_path": "ceval/ceval-exam",
|
| 469 |
-
"dataset_name": "art_studies",
|
| 470 |
-
"validation_split": "val",
|
| 471 |
-
"fewshot_split": "dev",
|
| 472 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 473 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 474 |
-
"doc_to_choice": [
|
| 475 |
-
"A",
|
| 476 |
-
"B",
|
| 477 |
-
"C",
|
| 478 |
-
"D"
|
| 479 |
-
],
|
| 480 |
-
"description": "以下是中国关于艺术学的单项选择题，请选出其中的正确答案。\n\n",
|
| 481 |
-
"target_delimiter": " ",
|
| 482 |
-
"fewshot_delimiter": "\n\n",
|
| 483 |
-
"fewshot_config": {
|
| 484 |
-
"sampler": "first_n"
|
| 485 |
-
},
|
| 486 |
-
"metric_list": [
|
| 487 |
-
{
|
| 488 |
-
"metric": "acc",
|
| 489 |
-
"aggregation": "mean",
|
| 490 |
-
"higher_is_better": true
|
| 491 |
-
},
|
| 492 |
-
{
|
| 493 |
-
"metric": "acc_norm",
|
| 494 |
-
"aggregation": "mean",
|
| 495 |
-
"higher_is_better": true
|
| 496 |
-
}
|
| 497 |
-
],
|
| 498 |
-
"output_type": "multiple_choice",
|
| 499 |
-
"repeats": 1,
|
| 500 |
-
"should_decontaminate": false,
|
| 501 |
-
"metadata": {
|
| 502 |
-
"version": 1.0
|
| 503 |
-
}
|
| 504 |
-
},
|
| 505 |
-
"ceval-valid_basic_medicine": {
|
| 506 |
-
"task": "ceval-valid_basic_medicine",
|
| 507 |
-
"group": "ceval-valid",
|
| 508 |
-
"dataset_path": "ceval/ceval-exam",
|
| 509 |
-
"dataset_name": "basic_medicine",
|
| 510 |
-
"validation_split": "val",
|
| 511 |
-
"fewshot_split": "dev",
|
| 512 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 513 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 514 |
-
"doc_to_choice": [
|
| 515 |
-
"A",
|
| 516 |
-
"B",
|
| 517 |
-
"C",
|
| 518 |
-
"D"
|
| 519 |
-
],
|
| 520 |
-
"description": "以下是中国关于基础医学的单项选择题，请选出其中的正确答案。\n\n",
|
| 521 |
-
"target_delimiter": " ",
|
| 522 |
-
"fewshot_delimiter": "\n\n",
|
| 523 |
-
"fewshot_config": {
|
| 524 |
-
"sampler": "first_n"
|
| 525 |
-
},
|
| 526 |
-
"metric_list": [
|
| 527 |
-
{
|
| 528 |
-
"metric": "acc",
|
| 529 |
-
"aggregation": "mean",
|
| 530 |
-
"higher_is_better": true
|
| 531 |
-
},
|
| 532 |
-
{
|
| 533 |
-
"metric": "acc_norm",
|
| 534 |
-
"aggregation": "mean",
|
| 535 |
-
"higher_is_better": true
|
| 536 |
-
}
|
| 537 |
-
],
|
| 538 |
-
"output_type": "multiple_choice",
|
| 539 |
-
"repeats": 1,
|
| 540 |
-
"should_decontaminate": false,
|
| 541 |
-
"metadata": {
|
| 542 |
-
"version": 1.0
|
| 543 |
-
}
|
| 544 |
-
},
|
| 545 |
-
"ceval-valid_business_administration": {
|
| 546 |
-
"task": "ceval-valid_business_administration",
|
| 547 |
-
"group": "ceval-valid",
|
| 548 |
-
"dataset_path": "ceval/ceval-exam",
|
| 549 |
-
"dataset_name": "business_administration",
|
| 550 |
-
"validation_split": "val",
|
| 551 |
-
"fewshot_split": "dev",
|
| 552 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答���：",
|
| 553 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 554 |
-
"doc_to_choice": [
|
| 555 |
-
"A",
|
| 556 |
-
"B",
|
| 557 |
-
"C",
|
| 558 |
-
"D"
|
| 559 |
-
],
|
| 560 |
-
"description": "以下是中国关于工商管理的单项选择题，请选出其中的正确答案。\n\n",
|
| 561 |
-
"target_delimiter": " ",
|
| 562 |
-
"fewshot_delimiter": "\n\n",
|
| 563 |
-
"fewshot_config": {
|
| 564 |
-
"sampler": "first_n"
|
| 565 |
-
},
|
| 566 |
-
"metric_list": [
|
| 567 |
-
{
|
| 568 |
-
"metric": "acc",
|
| 569 |
-
"aggregation": "mean",
|
| 570 |
-
"higher_is_better": true
|
| 571 |
-
},
|
| 572 |
-
{
|
| 573 |
-
"metric": "acc_norm",
|
| 574 |
-
"aggregation": "mean",
|
| 575 |
-
"higher_is_better": true
|
| 576 |
-
}
|
| 577 |
-
],
|
| 578 |
-
"output_type": "multiple_choice",
|
| 579 |
-
"repeats": 1,
|
| 580 |
-
"should_decontaminate": false,
|
| 581 |
-
"metadata": {
|
| 582 |
-
"version": 1.0
|
| 583 |
-
}
|
| 584 |
-
},
|
| 585 |
-
"ceval-valid_chinese_language_and_literature": {
|
| 586 |
-
"task": "ceval-valid_chinese_language_and_literature",
|
| 587 |
-
"group": "ceval-valid",
|
| 588 |
-
"dataset_path": "ceval/ceval-exam",
|
| 589 |
-
"dataset_name": "chinese_language_and_literature",
|
| 590 |
-
"validation_split": "val",
|
| 591 |
-
"fewshot_split": "dev",
|
| 592 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 593 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 594 |
-
"doc_to_choice": [
|
| 595 |
-
"A",
|
| 596 |
-
"B",
|
| 597 |
-
"C",
|
| 598 |
-
"D"
|
| 599 |
-
],
|
| 600 |
-
"description": "以下是中国关于中国语言文学的单项选择题，请选出其中的正确答案。\n\n",
|
| 601 |
-
"target_delimiter": " ",
|
| 602 |
-
"fewshot_delimiter": "\n\n",
|
| 603 |
-
"fewshot_config": {
|
| 604 |
-
"sampler": "first_n"
|
| 605 |
-
},
|
| 606 |
-
"metric_list": [
|
| 607 |
-
{
|
| 608 |
-
"metric": "acc",
|
| 609 |
-
"aggregation": "mean",
|
| 610 |
-
"higher_is_better": true
|
| 611 |
-
},
|
| 612 |
-
{
|
| 613 |
-
"metric": "acc_norm",
|
| 614 |
-
"aggregation": "mean",
|
| 615 |
-
"higher_is_better": true
|
| 616 |
-
}
|
| 617 |
-
],
|
| 618 |
-
"output_type": "multiple_choice",
|
| 619 |
-
"repeats": 1,
|
| 620 |
-
"should_decontaminate": false,
|
| 621 |
-
"metadata": {
|
| 622 |
-
"version": 1.0
|
| 623 |
-
}
|
| 624 |
-
},
|
| 625 |
-
"ceval-valid_civil_servant": {
|
| 626 |
-
"task": "ceval-valid_civil_servant",
|
| 627 |
-
"group": "ceval-valid",
|
| 628 |
-
"dataset_path": "ceval/ceval-exam",
|
| 629 |
-
"dataset_name": "civil_servant",
|
| 630 |
-
"validation_split": "val",
|
| 631 |
-
"fewshot_split": "dev",
|
| 632 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 633 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 634 |
-
"doc_to_choice": [
|
| 635 |
-
"A",
|
| 636 |
-
"B",
|
| 637 |
-
"C",
|
| 638 |
-
"D"
|
| 639 |
-
],
|
| 640 |
-
"description": "以下是中国关于公务员的单项选择题，请选出其中的正确答案。\n\n",
|
| 641 |
-
"target_delimiter": " ",
|
| 642 |
-
"fewshot_delimiter": "\n\n",
|
| 643 |
-
"fewshot_config": {
|
| 644 |
-
"sampler": "first_n"
|
| 645 |
-
},
|
| 646 |
-
"metric_list": [
|
| 647 |
-
{
|
| 648 |
-
"metric": "acc",
|
| 649 |
-
"aggregation": "mean",
|
| 650 |
-
"higher_is_better": true
|
| 651 |
-
},
|
| 652 |
-
{
|
| 653 |
-
"metric": "acc_norm",
|
| 654 |
-
"aggregation": "mean",
|
| 655 |
-
"higher_is_better": true
|
| 656 |
-
}
|
| 657 |
-
],
|
| 658 |
-
"output_type": "multiple_choice",
|
| 659 |
-
"repeats": 1,
|
| 660 |
-
"should_decontaminate": false,
|
| 661 |
-
"metadata": {
|
| 662 |
-
"version": 1.0
|
| 663 |
-
}
|
| 664 |
-
},
|
| 665 |
-
"ceval-valid_clinical_medicine": {
|
| 666 |
-
"task": "ceval-valid_clinical_medicine",
|
| 667 |
-
"group": "ceval-valid",
|
| 668 |
-
"dataset_path": "ceval/ceval-exam",
|
| 669 |
-
"dataset_name": "clinical_medicine",
|
| 670 |
-
"validation_split": "val",
|
| 671 |
-
"fewshot_split": "dev",
|
| 672 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 673 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 674 |
-
"doc_to_choice": [
|
| 675 |
-
"A",
|
| 676 |
-
"B",
|
| 677 |
-
"C",
|
| 678 |
-
"D"
|
| 679 |
-
],
|
| 680 |
-
"description": "以下是中国关于临床医学的单项选择题，请选出其中的正确答案。\n\n",
|
| 681 |
-
"target_delimiter": " ",
|
| 682 |
-
"fewshot_delimiter": "\n\n",
|
| 683 |
-
"fewshot_config": {
|
| 684 |
-
"sampler": "first_n"
|
| 685 |
-
},
|
| 686 |
-
"metric_list": [
|
| 687 |
-
{
|
| 688 |
-
"metric": "acc",
|
| 689 |
-
"aggregation": "mean",
|
| 690 |
-
"higher_is_better": true
|
| 691 |
-
},
|
| 692 |
-
{
|
| 693 |
-
"metric": "acc_norm",
|
| 694 |
-
"aggregation": "mean",
|
| 695 |
-
"higher_is_better": true
|
| 696 |
-
}
|
| 697 |
-
],
|
| 698 |
-
"output_type": "multiple_choice",
|
| 699 |
-
"repeats": 1,
|
| 700 |
-
"should_decontaminate": false,
|
| 701 |
-
"metadata": {
|
| 702 |
-
"version": 1.0
|
| 703 |
-
}
|
| 704 |
-
},
|
| 705 |
-
"ceval-valid_college_chemistry": {
|
| 706 |
-
"task": "ceval-valid_college_chemistry",
|
| 707 |
-
"group": "ceval-valid",
|
| 708 |
-
"dataset_path": "ceval/ceval-exam",
|
| 709 |
-
"dataset_name": "college_chemistry",
|
| 710 |
-
"validation_split": "val",
|
| 711 |
-
"fewshot_split": "dev",
|
| 712 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 713 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 714 |
-
"doc_to_choice": [
|
| 715 |
-
"A",
|
| 716 |
-
"B",
|
| 717 |
-
"C",
|
| 718 |
-
"D"
|
| 719 |
-
],
|
| 720 |
-
"description": "以下是中国关于��学化学的单项选择题，请选出其中的正确答案。\n\n",
|
| 721 |
-
"target_delimiter": " ",
|
| 722 |
-
"fewshot_delimiter": "\n\n",
|
| 723 |
-
"fewshot_config": {
|
| 724 |
-
"sampler": "first_n"
|
| 725 |
-
},
|
| 726 |
-
"metric_list": [
|
| 727 |
-
{
|
| 728 |
-
"metric": "acc",
|
| 729 |
-
"aggregation": "mean",
|
| 730 |
-
"higher_is_better": true
|
| 731 |
-
},
|
| 732 |
-
{
|
| 733 |
-
"metric": "acc_norm",
|
| 734 |
-
"aggregation": "mean",
|
| 735 |
-
"higher_is_better": true
|
| 736 |
-
}
|
| 737 |
-
],
|
| 738 |
-
"output_type": "multiple_choice",
|
| 739 |
-
"repeats": 1,
|
| 740 |
-
"should_decontaminate": false,
|
| 741 |
-
"metadata": {
|
| 742 |
-
"version": 1.0
|
| 743 |
-
}
|
| 744 |
-
},
|
| 745 |
-
"ceval-valid_college_economics": {
|
| 746 |
-
"task": "ceval-valid_college_economics",
|
| 747 |
-
"group": "ceval-valid",
|
| 748 |
-
"dataset_path": "ceval/ceval-exam",
|
| 749 |
-
"dataset_name": "college_economics",
|
| 750 |
-
"validation_split": "val",
|
| 751 |
-
"fewshot_split": "dev",
|
| 752 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 753 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 754 |
-
"doc_to_choice": [
|
| 755 |
-
"A",
|
| 756 |
-
"B",
|
| 757 |
-
"C",
|
| 758 |
-
"D"
|
| 759 |
-
],
|
| 760 |
-
"description": "以下是中国关于大学经济学的单项选择题，请选出其中的正确答案。\n\n",
|
| 761 |
-
"target_delimiter": " ",
|
| 762 |
-
"fewshot_delimiter": "\n\n",
|
| 763 |
-
"fewshot_config": {
|
| 764 |
-
"sampler": "first_n"
|
| 765 |
-
},
|
| 766 |
-
"metric_list": [
|
| 767 |
-
{
|
| 768 |
-
"metric": "acc",
|
| 769 |
-
"aggregation": "mean",
|
| 770 |
-
"higher_is_better": true
|
| 771 |
-
},
|
| 772 |
-
{
|
| 773 |
-
"metric": "acc_norm",
|
| 774 |
-
"aggregation": "mean",
|
| 775 |
-
"higher_is_better": true
|
| 776 |
-
}
|
| 777 |
-
],
|
| 778 |
-
"output_type": "multiple_choice",
|
| 779 |
-
"repeats": 1,
|
| 780 |
-
"should_decontaminate": false,
|
| 781 |
-
"metadata": {
|
| 782 |
-
"version": 1.0
|
| 783 |
-
}
|
| 784 |
-
},
|
| 785 |
-
"ceval-valid_college_physics": {
|
| 786 |
-
"task": "ceval-valid_college_physics",
|
| 787 |
-
"group": "ceval-valid",
|
| 788 |
-
"dataset_path": "ceval/ceval-exam",
|
| 789 |
-
"dataset_name": "college_physics",
|
| 790 |
-
"validation_split": "val",
|
| 791 |
-
"fewshot_split": "dev",
|
| 792 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 793 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 794 |
-
"doc_to_choice": [
|
| 795 |
-
"A",
|
| 796 |
-
"B",
|
| 797 |
-
"C",
|
| 798 |
-
"D"
|
| 799 |
-
],
|
| 800 |
-
"description": "以下是中国关于大学物理的单项选择题，请选出其中的正确答案。\n\n",
|
| 801 |
-
"target_delimiter": " ",
|
| 802 |
-
"fewshot_delimiter": "\n\n",
|
| 803 |
-
"fewshot_config": {
|
| 804 |
-
"sampler": "first_n"
|
| 805 |
-
},
|
| 806 |
-
"metric_list": [
|
| 807 |
-
{
|
| 808 |
-
"metric": "acc",
|
| 809 |
-
"aggregation": "mean",
|
| 810 |
-
"higher_is_better": true
|
| 811 |
-
},
|
| 812 |
-
{
|
| 813 |
-
"metric": "acc_norm",
|
| 814 |
-
"aggregation": "mean",
|
| 815 |
-
"higher_is_better": true
|
| 816 |
-
}
|
| 817 |
-
],
|
| 818 |
-
"output_type": "multiple_choice",
|
| 819 |
-
"repeats": 1,
|
| 820 |
-
"should_decontaminate": false,
|
| 821 |
-
"metadata": {
|
| 822 |
-
"version": 1.0
|
| 823 |
-
}
|
| 824 |
-
},
|
| 825 |
-
"ceval-valid_college_programming": {
|
| 826 |
-
"task": "ceval-valid_college_programming",
|
| 827 |
-
"group": "ceval-valid",
|
| 828 |
-
"dataset_path": "ceval/ceval-exam",
|
| 829 |
-
"dataset_name": "college_programming",
|
| 830 |
-
"validation_split": "val",
|
| 831 |
-
"fewshot_split": "dev",
|
| 832 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 833 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 834 |
-
"doc_to_choice": [
|
| 835 |
-
"A",
|
| 836 |
-
"B",
|
| 837 |
-
"C",
|
| 838 |
-
"D"
|
| 839 |
-
],
|
| 840 |
-
"description": "以下是中国关于大学编程的单项选择题，请选出其中的正确答案。\n\n",
|
| 841 |
-
"target_delimiter": " ",
|
| 842 |
-
"fewshot_delimiter": "\n\n",
|
| 843 |
-
"fewshot_config": {
|
| 844 |
-
"sampler": "first_n"
|
| 845 |
-
},
|
| 846 |
-
"metric_list": [
|
| 847 |
-
{
|
| 848 |
-
"metric": "acc",
|
| 849 |
-
"aggregation": "mean",
|
| 850 |
-
"higher_is_better": true
|
| 851 |
-
},
|
| 852 |
-
{
|
| 853 |
-
"metric": "acc_norm",
|
| 854 |
-
"aggregation": "mean",
|
| 855 |
-
"higher_is_better": true
|
| 856 |
-
}
|
| 857 |
-
],
|
| 858 |
-
"output_type": "multiple_choice",
|
| 859 |
-
"repeats": 1,
|
| 860 |
-
"should_decontaminate": false,
|
| 861 |
-
"metadata": {
|
| 862 |
-
"version": 1.0
|
| 863 |
-
}
|
| 864 |
-
},
|
| 865 |
-
"ceval-valid_computer_architecture": {
|
| 866 |
-
"task": "ceval-valid_computer_architecture",
|
| 867 |
-
"group": "ceval-valid",
|
| 868 |
-
"dataset_path": "ceval/ceval-exam",
|
| 869 |
-
"dataset_name": "computer_architecture",
|
| 870 |
-
"validation_split": "val",
|
| 871 |
-
"fewshot_split": "dev",
|
| 872 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 873 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 874 |
-
"doc_to_choice": [
|
| 875 |
-
"A",
|
| 876 |
-
"B",
|
| 877 |
-
"C",
|
| 878 |
-
"D"
|
| 879 |
-
],
|
| 880 |
-
"description": "以下是中国关于计算机组成的单项选择题，请选出其中的正确答案。\n\n",
|
| 881 |
-
"target_delimiter": " ",
|
| 882 |
-
"fewshot_delimiter": "\n\n",
|
| 883 |
-
"fewshot_config": {
|
| 884 |
-
"sampler": "first_n"
|
| 885 |
-
},
|
| 886 |
-
"metric_list": [
|
| 887 |
-
{
|
| 888 |
-
"metric": "acc",
|
| 889 |
-
"aggregation": "mean",
|
| 890 |
-
"higher_is_better": true
|
| 891 |
-
},
|
| 892 |
-
{
|
| 893 |
-
"metric": "acc_norm",
|
| 894 |
-
"aggregation": "mean",
|
| 895 |
-
"higher_is_better": true
|
| 896 |
-
}
|
| 897 |
-
],
|
| 898 |
-
"output_type": "multiple_choice",
|
| 899 |
-
"repeats": 1,
|
| 900 |
-
"should_decontaminate": false,
|
| 901 |
-
"metadata": {
|
| 902 |
-
"version": 1.0
|
| 903 |
-
}
|
| 904 |
-
},
|
| 905 |
-
"ceval-valid_computer_network": {
|
| 906 |
-
"task": "ceval-valid_computer_network",
|
| 907 |
-
"group": "ceval-valid",
|
| 908 |
-
"dataset_path": "ceval/ceval-exam",
|
| 909 |
-
"dataset_name": "computer_network",
|
| 910 |
-
"validation_split": "val",
|
| 911 |
-
"fewshot_split": "dev",
|
| 912 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 913 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 914 |
-
"doc_to_choice": [
|
| 915 |
-
"A",
|
| 916 |
-
"B",
|
| 917 |
-
"C",
|
| 918 |
-
"D"
|
| 919 |
-
],
|
| 920 |
-
"description": "以下是中国关于计算机网络的单项选择题，请选出其中的正确答案。\n\n",
|
| 921 |
-
"target_delimiter": " ",
|
| 922 |
-
"fewshot_delimiter": "\n\n",
|
| 923 |
-
"fewshot_config": {
|
| 924 |
-
"sampler": "first_n"
|
| 925 |
-
},
|
| 926 |
-
"metric_list": [
|
| 927 |
-
{
|
| 928 |
-
"metric": "acc",
|
| 929 |
-
"aggregation": "mean",
|
| 930 |
-
"higher_is_better": true
|
| 931 |
-
},
|
| 932 |
-
{
|
| 933 |
-
"metric": "acc_norm",
|
| 934 |
-
"aggregation": "mean",
|
| 935 |
-
"higher_is_better": true
|
| 936 |
-
}
|
| 937 |
-
],
|
| 938 |
-
"output_type": "multiple_choice",
|
| 939 |
-
"repeats": 1,
|
| 940 |
-
"should_decontaminate": false,
|
| 941 |
-
"metadata": {
|
| 942 |
-
"version": 1.0
|
| 943 |
-
}
|
| 944 |
-
},
|
| 945 |
-
"ceval-valid_discrete_mathematics": {
|
| 946 |
-
"task": "ceval-valid_discrete_mathematics",
|
| 947 |
-
"group": "ceval-valid",
|
| 948 |
-
"dataset_path": "ceval/ceval-exam",
|
| 949 |
-
"dataset_name": "discrete_mathematics",
|
| 950 |
-
"validation_split": "val",
|
| 951 |
-
"fewshot_split": "dev",
|
| 952 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 953 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 954 |
-
"doc_to_choice": [
|
| 955 |
-
"A",
|
| 956 |
-
"B",
|
| 957 |
-
"C",
|
| 958 |
-
"D"
|
| 959 |
-
],
|
| 960 |
-
"description": "以下是中国关于离散数学的单项选择题，请选出其中的正确答案。\n\n",
|
| 961 |
-
"target_delimiter": " ",
|
| 962 |
-
"fewshot_delimiter": "\n\n",
|
| 963 |
-
"fewshot_config": {
|
| 964 |
-
"sampler": "first_n"
|
| 965 |
-
},
|
| 966 |
-
"metric_list": [
|
| 967 |
-
{
|
| 968 |
-
"metric": "acc",
|
| 969 |
-
"aggregation": "mean",
|
| 970 |
-
"higher_is_better": true
|
| 971 |
-
},
|
| 972 |
-
{
|
| 973 |
-
"metric": "acc_norm",
|
| 974 |
-
"aggregation": "mean",
|
| 975 |
-
"higher_is_better": true
|
| 976 |
-
}
|
| 977 |
-
],
|
| 978 |
-
"output_type": "multiple_choice",
|
| 979 |
-
"repeats": 1,
|
| 980 |
-
"should_decontaminate": false,
|
| 981 |
-
"metadata": {
|
| 982 |
-
"version": 1.0
|
| 983 |
-
}
|
| 984 |
-
},
|
| 985 |
-
"ceval-valid_education_science": {
|
| 986 |
-
"task": "ceval-valid_education_science",
|
| 987 |
-
"group": "ceval-valid",
|
| 988 |
-
"dataset_path": "ceval/ceval-exam",
|
| 989 |
-
"dataset_name": "education_science",
|
| 990 |
-
"validation_split": "val",
|
| 991 |
-
"fewshot_split": "dev",
|
| 992 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 993 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 994 |
-
"doc_to_choice": [
|
| 995 |
-
"A",
|
| 996 |
-
"B",
|
| 997 |
-
"C",
|
| 998 |
-
"D"
|
| 999 |
-
],
|
| 1000 |
-
"description": "以下是中国关于教育学的单项选择题，请选出其中的正确答案。\n\n",
|
| 1001 |
-
"target_delimiter": " ",
|
| 1002 |
-
"fewshot_delimiter": "\n\n",
|
| 1003 |
-
"fewshot_config": {
|
| 1004 |
-
"sampler": "first_n"
|
| 1005 |
-
},
|
| 1006 |
-
"metric_list": [
|
| 1007 |
-
{
|
| 1008 |
-
"metric": "acc",
|
| 1009 |
-
"aggregation": "mean",
|
| 1010 |
-
"higher_is_better": true
|
| 1011 |
-
},
|
| 1012 |
-
{
|
| 1013 |
-
"metric": "acc_norm",
|
| 1014 |
-
"aggregation": "mean",
|
| 1015 |
-
"higher_is_better": true
|
| 1016 |
-
}
|
| 1017 |
-
],
|
| 1018 |
-
"output_type": "multiple_choice",
|
| 1019 |
-
"repeats": 1,
|
| 1020 |
-
"should_decontaminate": false,
|
| 1021 |
-
"metadata": {
|
| 1022 |
-
"version": 1.0
|
| 1023 |
-
}
|
| 1024 |
-
},
|
| 1025 |
-
"ceval-valid_electrical_engineer": {
|
| 1026 |
-
"task": "ceval-valid_electrical_engineer",
|
| 1027 |
-
"group": "ceval-valid",
|
| 1028 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1029 |
-
"dataset_name": "electrical_engineer",
|
| 1030 |
-
"validation_split": "val",
|
| 1031 |
-
"fewshot_split": "dev",
|
| 1032 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1033 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1034 |
-
"doc_to_choice": [
|
| 1035 |
-
"A",
|
| 1036 |
-
"B",
|
| 1037 |
-
"C",
|
| 1038 |
-
"D"
|
| 1039 |
-
],
|
| 1040 |
-
"description": "以下是中国关于注册电气工程师的单项选择题，请选出其中的正确答案。\n\n",
|
| 1041 |
-
"target_delimiter": " ",
|
| 1042 |
-
"fewshot_delimiter": "\n\n",
|
| 1043 |
-
"fewshot_config": {
|
| 1044 |
-
"sampler": "first_n"
|
| 1045 |
-
},
|
| 1046 |
-
"metric_list": [
|
| 1047 |
-
{
|
| 1048 |
-
"metric": "acc",
|
| 1049 |
-
"aggregation": "mean",
|
| 1050 |
-
"higher_is_better": true
|
| 1051 |
-
},
|
| 1052 |
-
{
|
| 1053 |
-
"metric": "acc_norm",
|
| 1054 |
-
"aggregation": "mean",
|
| 1055 |
-
"higher_is_better": true
|
| 1056 |
-
}
|
| 1057 |
-
],
|
| 1058 |
-
"output_type": "multiple_choice",
|
| 1059 |
-
"repeats": 1,
|
| 1060 |
-
"should_decontaminate": false,
|
| 1061 |
-
"metadata": {
|
| 1062 |
-
"version": 1.0
|
| 1063 |
-
}
|
| 1064 |
-
},
|
| 1065 |
-
"ceval-valid_environmental_impact_assessment_engineer": {
|
| 1066 |
-
"task": "ceval-valid_environmental_impact_assessment_engineer",
|
| 1067 |
-
"group": "ceval-valid",
|
| 1068 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1069 |
-
"dataset_name": "environmental_impact_assessment_engineer",
|
| 1070 |
-
"validation_split": "val",
|
| 1071 |
-
"fewshot_split": "dev",
|
| 1072 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1073 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1074 |
-
"doc_to_choice": [
|
| 1075 |
-
"A",
|
| 1076 |
-
"B",
|
| 1077 |
-
"C",
|
| 1078 |
-
"D"
|
| 1079 |
-
],
|
| 1080 |
-
"description": "以下是中国关于环境影响评价工程师的单项选择题，请选出其中的正确答案。\n\n",
|
| 1081 |
-
"target_delimiter": " ",
|
| 1082 |
-
"fewshot_delimiter": "\n\n",
|
| 1083 |
-
"fewshot_config": {
|
| 1084 |
-
"sampler": "first_n"
|
| 1085 |
-
},
|
| 1086 |
-
"metric_list": [
|
| 1087 |
-
{
|
| 1088 |
-
"metric": "acc",
|
| 1089 |
-
"aggregation": "mean",
|
| 1090 |
-
"higher_is_better": true
|
| 1091 |
-
},
|
| 1092 |
-
{
|
| 1093 |
-
"metric": "acc_norm",
|
| 1094 |
-
"aggregation": "mean",
|
| 1095 |
-
"higher_is_better": true
|
| 1096 |
-
}
|
| 1097 |
-
],
|
| 1098 |
-
"output_type": "multiple_choice",
|
| 1099 |
-
"repeats": 1,
|
| 1100 |
-
"should_decontaminate": false,
|
| 1101 |
-
"metadata": {
|
| 1102 |
-
"version": 1.0
|
| 1103 |
-
}
|
| 1104 |
-
},
|
| 1105 |
-
"ceval-valid_fire_engineer": {
|
| 1106 |
-
"task": "ceval-valid_fire_engineer",
|
| 1107 |
-
"group": "ceval-valid",
|
| 1108 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1109 |
-
"dataset_name": "fire_engineer",
|
| 1110 |
-
"validation_split": "val",
|
| 1111 |
-
"fewshot_split": "dev",
|
| 1112 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1113 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1114 |
-
"doc_to_choice": [
|
| 1115 |
-
"A",
|
| 1116 |
-
"B",
|
| 1117 |
-
"C",
|
| 1118 |
-
"D"
|
| 1119 |
-
],
|
| 1120 |
-
"description": "以下是中国关于注册消防工程师的单项选择题，请选出其中的正确答案。\n\n",
|
| 1121 |
-
"target_delimiter": " ",
|
| 1122 |
-
"fewshot_delimiter": "\n\n",
|
| 1123 |
-
"fewshot_config": {
|
| 1124 |
-
"sampler": "first_n"
|
| 1125 |
-
},
|
| 1126 |
-
"metric_list": [
|
| 1127 |
-
{
|
| 1128 |
-
"metric": "acc",
|
| 1129 |
-
"aggregation": "mean",
|
| 1130 |
-
"higher_is_better": true
|
| 1131 |
-
},
|
| 1132 |
-
{
|
| 1133 |
-
"metric": "acc_norm",
|
| 1134 |
-
"aggregation": "mean",
|
| 1135 |
-
"higher_is_better": true
|
| 1136 |
-
}
|
| 1137 |
-
],
|
| 1138 |
-
"output_type": "multiple_choice",
|
| 1139 |
-
"repeats": 1,
|
| 1140 |
-
"should_decontaminate": false,
|
| 1141 |
-
"metadata": {
|
| 1142 |
-
"version": 1.0
|
| 1143 |
-
}
|
| 1144 |
-
},
|
| 1145 |
-
"ceval-valid_high_school_biology": {
|
| 1146 |
-
"task": "ceval-valid_high_school_biology",
|
| 1147 |
-
"group": "ceval-valid",
|
| 1148 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1149 |
-
"dataset_name": "high_school_biology",
|
| 1150 |
-
"validation_split": "val",
|
| 1151 |
-
"fewshot_split": "dev",
|
| 1152 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1153 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1154 |
-
"doc_to_choice": [
|
| 1155 |
-
"A",
|
| 1156 |
-
"B",
|
| 1157 |
-
"C",
|
| 1158 |
-
"D"
|
| 1159 |
-
],
|
| 1160 |
-
"description": "以下是中国关于高中生物的单项选择题，请选出其中的正确答案。\n\n",
|
| 1161 |
-
"target_delimiter": " ",
|
| 1162 |
-
"fewshot_delimiter": "\n\n",
|
| 1163 |
-
"fewshot_config": {
|
| 1164 |
-
"sampler": "first_n"
|
| 1165 |
-
},
|
| 1166 |
-
"metric_list": [
|
| 1167 |
-
{
|
| 1168 |
-
"metric": "acc",
|
| 1169 |
-
"aggregation": "mean",
|
| 1170 |
-
"higher_is_better": true
|
| 1171 |
-
},
|
| 1172 |
-
{
|
| 1173 |
-
"metric": "acc_norm",
|
| 1174 |
-
"aggregation": "mean",
|
| 1175 |
-
"higher_is_better": true
|
| 1176 |
-
}
|
| 1177 |
-
],
|
| 1178 |
-
"output_type": "multiple_choice",
|
| 1179 |
-
"repeats": 1,
|
| 1180 |
-
"should_decontaminate": false,
|
| 1181 |
-
"metadata": {
|
| 1182 |
-
"version": 1.0
|
| 1183 |
-
}
|
| 1184 |
-
},
|
| 1185 |
-
"ceval-valid_high_school_chemistry": {
|
| 1186 |
-
"task": "ceval-valid_high_school_chemistry",
|
| 1187 |
-
"group": "ceval-valid",
|
| 1188 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1189 |
-
"dataset_name": "high_school_chemistry",
|
| 1190 |
-
"validation_split": "val",
|
| 1191 |
-
"fewshot_split": "dev",
|
| 1192 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1193 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1194 |
-
"doc_to_choice": [
|
| 1195 |
-
"A",
|
| 1196 |
-
"B",
|
| 1197 |
-
"C",
|
| 1198 |
-
"D"
|
| 1199 |
-
],
|
| 1200 |
-
"description": "以下是中国关于高中化学的单项选择题，请选出其中的正确答案。\n\n",
|
| 1201 |
-
"target_delimiter": " ",
|
| 1202 |
-
"fewshot_delimiter": "\n\n",
|
| 1203 |
-
"fewshot_config": {
|
| 1204 |
-
"sampler": "first_n"
|
| 1205 |
-
},
|
| 1206 |
-
"metric_list": [
|
| 1207 |
-
{
|
| 1208 |
-
"metric": "acc",
|
| 1209 |
-
"aggregation": "mean",
|
| 1210 |
-
"higher_is_better": true
|
| 1211 |
-
},
|
| 1212 |
-
{
|
| 1213 |
-
"metric": "acc_norm",
|
| 1214 |
-
"aggregation": "mean",
|
| 1215 |
-
"higher_is_better": true
|
| 1216 |
-
}
|
| 1217 |
-
],
|
| 1218 |
-
"output_type": "multiple_choice",
|
| 1219 |
-
"repeats": 1,
|
| 1220 |
-
"should_decontaminate": false,
|
| 1221 |
-
"metadata": {
|
| 1222 |
-
"version": 1.0
|
| 1223 |
-
}
|
| 1224 |
-
},
|
| 1225 |
-
"ceval-valid_high_school_chinese": {
|
| 1226 |
-
"task": "ceval-valid_high_school_chinese",
|
| 1227 |
-
"group": "ceval-valid",
|
| 1228 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1229 |
-
"dataset_name": "high_school_chinese",
|
| 1230 |
-
"validation_split": "val",
|
| 1231 |
-
"fewshot_split": "dev",
|
| 1232 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1233 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1234 |
-
"doc_to_choice": [
|
| 1235 |
-
"A",
|
| 1236 |
-
"B",
|
| 1237 |
-
"C",
|
| 1238 |
-
"D"
|
| 1239 |
-
],
|
| 1240 |
-
"description": "以下是中国关于高中语文的单项选择题，请选出其中的正确答案。\n\n",
|
| 1241 |
-
"target_delimiter": " ",
|
| 1242 |
-
"fewshot_delimiter": "\n\n",
|
| 1243 |
-
"fewshot_config": {
|
| 1244 |
-
"sampler": "first_n"
|
| 1245 |
-
},
|
| 1246 |
-
"metric_list": [
|
| 1247 |
-
{
|
| 1248 |
-
"metric": "acc",
|
| 1249 |
-
"aggregation": "mean",
|
| 1250 |
-
"higher_is_better": true
|
| 1251 |
-
},
|
| 1252 |
-
{
|
| 1253 |
-
"metric": "acc_norm",
|
| 1254 |
-
"aggregation": "mean",
|
| 1255 |
-
"higher_is_better": true
|
| 1256 |
-
}
|
| 1257 |
-
],
|
| 1258 |
-
"output_type": "multiple_choice",
|
| 1259 |
-
"repeats": 1,
|
| 1260 |
-
"should_decontaminate": false,
|
| 1261 |
-
"metadata": {
|
| 1262 |
-
"version": 1.0
|
| 1263 |
-
}
|
| 1264 |
-
},
|
| 1265 |
-
"ceval-valid_high_school_geography": {
|
| 1266 |
-
"task": "ceval-valid_high_school_geography",
|
| 1267 |
-
"group": "ceval-valid",
|
| 1268 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1269 |
-
"dataset_name": "high_school_geography",
|
| 1270 |
-
"validation_split": "val",
|
| 1271 |
-
"fewshot_split": "dev",
|
| 1272 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1273 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1274 |
-
"doc_to_choice": [
|
| 1275 |
-
"A",
|
| 1276 |
-
"B",
|
| 1277 |
-
"C",
|
| 1278 |
-
"D"
|
| 1279 |
-
],
|
| 1280 |
-
"description": "以下是中国关于高中地理的单项选择题，请选出其中的正确答案。\n\n",
|
| 1281 |
-
"target_delimiter": " ",
|
| 1282 |
-
"fewshot_delimiter": "\n\n",
|
| 1283 |
-
"fewshot_config": {
|
| 1284 |
-
"sampler": "first_n"
|
| 1285 |
-
},
|
| 1286 |
-
"metric_list": [
|
| 1287 |
-
{
|
| 1288 |
-
"metric": "acc",
|
| 1289 |
-
"aggregation": "mean",
|
| 1290 |
-
"higher_is_better": true
|
| 1291 |
-
},
|
| 1292 |
-
{
|
| 1293 |
-
"metric": "acc_norm",
|
| 1294 |
-
"aggregation": "mean",
|
| 1295 |
-
"higher_is_better": true
|
| 1296 |
-
}
|
| 1297 |
-
],
|
| 1298 |
-
"output_type": "multiple_choice",
|
| 1299 |
-
"repeats": 1,
|
| 1300 |
-
"should_decontaminate": false,
|
| 1301 |
-
"metadata": {
|
| 1302 |
-
"version": 1.0
|
| 1303 |
-
}
|
| 1304 |
-
},
|
| 1305 |
-
"ceval-valid_high_school_history": {
|
| 1306 |
-
"task": "ceval-valid_high_school_history",
|
| 1307 |
-
"group": "ceval-valid",
|
| 1308 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1309 |
-
"dataset_name": "high_school_history",
|
| 1310 |
-
"validation_split": "val",
|
| 1311 |
-
"fewshot_split": "dev",
|
| 1312 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1313 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1314 |
-
"doc_to_choice": [
|
| 1315 |
-
"A",
|
| 1316 |
-
"B",
|
| 1317 |
-
"C",
|
| 1318 |
-
"D"
|
| 1319 |
-
],
|
| 1320 |
-
"description": "以下是中国关于高中历史的单项选择题，请选出其中的正确答案。\n\n",
|
| 1321 |
-
"target_delimiter": " ",
|
| 1322 |
-
"fewshot_delimiter": "\n\n",
|
| 1323 |
-
"fewshot_config": {
|
| 1324 |
-
"sampler": "first_n"
|
| 1325 |
-
},
|
| 1326 |
-
"metric_list": [
|
| 1327 |
-
{
|
| 1328 |
-
"metric": "acc",
|
| 1329 |
-
"aggregation": "mean",
|
| 1330 |
-
"higher_is_better": true
|
| 1331 |
-
},
|
| 1332 |
-
{
|
| 1333 |
-
"metric": "acc_norm",
|
| 1334 |
-
"aggregation": "mean",
|
| 1335 |
-
"higher_is_better": true
|
| 1336 |
-
}
|
| 1337 |
-
],
|
| 1338 |
-
"output_type": "multiple_choice",
|
| 1339 |
-
"repeats": 1,
|
| 1340 |
-
"should_decontaminate": false,
|
| 1341 |
-
"metadata": {
|
| 1342 |
-
"version": 1.0
|
| 1343 |
-
}
|
| 1344 |
-
},
|
| 1345 |
-
"ceval-valid_high_school_mathematics": {
|
| 1346 |
-
"task": "ceval-valid_high_school_mathematics",
|
| 1347 |
-
"group": "ceval-valid",
|
| 1348 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1349 |
-
"dataset_name": "high_school_mathematics",
|
| 1350 |
-
"validation_split": "val",
|
| 1351 |
-
"fewshot_split": "dev",
|
| 1352 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1353 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1354 |
-
"doc_to_choice": [
|
| 1355 |
-
"A",
|
| 1356 |
-
"B",
|
| 1357 |
-
"C",
|
| 1358 |
-
"D"
|
| 1359 |
-
],
|
| 1360 |
-
"description": "以下是中国关于高中数学的单项选择题，请选出其中的正确答案。\n\n",
|
| 1361 |
-
"target_delimiter": " ",
|
| 1362 |
-
"fewshot_delimiter": "\n\n",
|
| 1363 |
-
"fewshot_config": {
|
| 1364 |
-
"sampler": "first_n"
|
| 1365 |
-
},
|
| 1366 |
-
"metric_list": [
|
| 1367 |
-
{
|
| 1368 |
-
"metric": "acc",
|
| 1369 |
-
"aggregation": "mean",
|
| 1370 |
-
"higher_is_better": true
|
| 1371 |
-
},
|
| 1372 |
-
{
|
| 1373 |
-
"metric": "acc_norm",
|
| 1374 |
-
"aggregation": "mean",
|
| 1375 |
-
"higher_is_better": true
|
| 1376 |
-
}
|
| 1377 |
-
],
|
| 1378 |
-
"output_type": "multiple_choice",
|
| 1379 |
-
"repeats": 1,
|
| 1380 |
-
"should_decontaminate": false,
|
| 1381 |
-
"metadata": {
|
| 1382 |
-
"version": 1.0
|
| 1383 |
-
}
|
| 1384 |
-
},
|
| 1385 |
-
"ceval-valid_high_school_physics": {
|
| 1386 |
-
"task": "ceval-valid_high_school_physics",
|
| 1387 |
-
"group": "ceval-valid",
|
| 1388 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1389 |
-
"dataset_name": "high_school_physics",
|
| 1390 |
-
"validation_split": "val",
|
| 1391 |
-
"fewshot_split": "dev",
|
| 1392 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1393 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1394 |
-
"doc_to_choice": [
|
| 1395 |
-
"A",
|
| 1396 |
-
"B",
|
| 1397 |
-
"C",
|
| 1398 |
-
"D"
|
| 1399 |
-
],
|
| 1400 |
-
"description": "以下是中国关于高中物理的单项选择题，请选出其中的正确答案。\n\n",
|
| 1401 |
-
"target_delimiter": " ",
|
| 1402 |
-
"fewshot_delimiter": "\n\n",
|
| 1403 |
-
"fewshot_config": {
|
| 1404 |
-
"sampler": "first_n"
|
| 1405 |
-
},
|
| 1406 |
-
"metric_list": [
|
| 1407 |
-
{
|
| 1408 |
-
"metric": "acc",
|
| 1409 |
-
"aggregation": "mean",
|
| 1410 |
-
"higher_is_better": true
|
| 1411 |
-
},
|
| 1412 |
-
{
|
| 1413 |
-
"metric": "acc_norm",
|
| 1414 |
-
"aggregation": "mean",
|
| 1415 |
-
"higher_is_better": true
|
| 1416 |
-
}
|
| 1417 |
-
],
|
| 1418 |
-
"output_type": "multiple_choice",
|
| 1419 |
-
"repeats": 1,
|
| 1420 |
-
"should_decontaminate": false,
|
| 1421 |
-
"metadata": {
|
| 1422 |
-
"version": 1.0
|
| 1423 |
-
}
|
| 1424 |
-
},
|
| 1425 |
-
"ceval-valid_high_school_politics": {
|
| 1426 |
-
"task": "ceval-valid_high_school_politics",
|
| 1427 |
-
"group": "ceval-valid",
|
| 1428 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1429 |
-
"dataset_name": "high_school_politics",
|
| 1430 |
-
"validation_split": "val",
|
| 1431 |
-
"fewshot_split": "dev",
|
| 1432 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1433 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1434 |
-
"doc_to_choice": [
|
| 1435 |
-
"A",
|
| 1436 |
-
"B",
|
| 1437 |
-
"C",
|
| 1438 |
-
"D"
|
| 1439 |
-
],
|
| 1440 |
-
"description": "以下是中国关于高中政治的单项选择题，请选出其中的正确答案。\n\n",
|
| 1441 |
-
"target_delimiter": " ",
|
| 1442 |
-
"fewshot_delimiter": "\n\n",
|
| 1443 |
-
"fewshot_config": {
|
| 1444 |
-
"sampler": "first_n"
|
| 1445 |
-
},
|
| 1446 |
-
"metric_list": [
|
| 1447 |
-
{
|
| 1448 |
-
"metric": "acc",
|
| 1449 |
-
"aggregation": "mean",
|
| 1450 |
-
"higher_is_better": true
|
| 1451 |
-
},
|
| 1452 |
-
{
|
| 1453 |
-
"metric": "acc_norm",
|
| 1454 |
-
"aggregation": "mean",
|
| 1455 |
-
"higher_is_better": true
|
| 1456 |
-
}
|
| 1457 |
-
],
|
| 1458 |
-
"output_type": "multiple_choice",
|
| 1459 |
-
"repeats": 1,
|
| 1460 |
-
"should_decontaminate": false,
|
| 1461 |
-
"metadata": {
|
| 1462 |
-
"version": 1.0
|
| 1463 |
-
}
|
| 1464 |
-
},
|
| 1465 |
-
"ceval-valid_ideological_and_moral_cultivation": {
|
| 1466 |
-
"task": "ceval-valid_ideological_and_moral_cultivation",
|
| 1467 |
-
"group": "ceval-valid",
|
| 1468 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1469 |
-
"dataset_name": "ideological_and_moral_cultivation",
|
| 1470 |
-
"validation_split": "val",
|
| 1471 |
-
"fewshot_split": "dev",
|
| 1472 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1473 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1474 |
-
"doc_to_choice": [
|
| 1475 |
-
"A",
|
| 1476 |
-
"B",
|
| 1477 |
-
"C",
|
| 1478 |
-
"D"
|
| 1479 |
-
],
|
| 1480 |
-
"description": "以下是中国关于思想道德修养与法律基础的单项选择题，请选出其中的正确答案。\n\n",
|
| 1481 |
-
"target_delimiter": " ",
|
| 1482 |
-
"fewshot_delimiter": "\n\n",
|
| 1483 |
-
"fewshot_config": {
|
| 1484 |
-
"sampler": "first_n"
|
| 1485 |
-
},
|
| 1486 |
-
"metric_list": [
|
| 1487 |
-
{
|
| 1488 |
-
"metric": "acc",
|
| 1489 |
-
"aggregation": "mean",
|
| 1490 |
-
"higher_is_better": true
|
| 1491 |
-
},
|
| 1492 |
-
{
|
| 1493 |
-
"metric": "acc_norm",
|
| 1494 |
-
"aggregation": "mean",
|
| 1495 |
-
"higher_is_better": true
|
| 1496 |
-
}
|
| 1497 |
-
],
|
| 1498 |
-
"output_type": "multiple_choice",
|
| 1499 |
-
"repeats": 1,
|
| 1500 |
-
"should_decontaminate": false,
|
| 1501 |
-
"metadata": {
|
| 1502 |
-
"version": 1.0
|
| 1503 |
-
}
|
| 1504 |
-
},
|
| 1505 |
-
"ceval-valid_law": {
|
| 1506 |
-
"task": "ceval-valid_law",
|
| 1507 |
-
"group": "ceval-valid",
|
| 1508 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1509 |
-
"dataset_name": "law",
|
| 1510 |
-
"validation_split": "val",
|
| 1511 |
-
"fewshot_split": "dev",
|
| 1512 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1513 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1514 |
-
"doc_to_choice": [
|
| 1515 |
-
"A",
|
| 1516 |
-
"B",
|
| 1517 |
-
"C",
|
| 1518 |
-
"D"
|
| 1519 |
-
],
|
| 1520 |
-
"description": "以下是中国关于法学的单项选择题，请选出其中的正确答案。\n\n",
|
| 1521 |
-
"target_delimiter": " ",
|
| 1522 |
-
"fewshot_delimiter": "\n\n",
|
| 1523 |
-
"fewshot_config": {
|
| 1524 |
-
"sampler": "first_n"
|
| 1525 |
-
},
|
| 1526 |
-
"metric_list": [
|
| 1527 |
-
{
|
| 1528 |
-
"metric": "acc",
|
| 1529 |
-
"aggregation": "mean",
|
| 1530 |
-
"higher_is_better": true
|
| 1531 |
-
},
|
| 1532 |
-
{
|
| 1533 |
-
"metric": "acc_norm",
|
| 1534 |
-
"aggregation": "mean",
|
| 1535 |
-
"higher_is_better": true
|
| 1536 |
-
}
|
| 1537 |
-
],
|
| 1538 |
-
"output_type": "multiple_choice",
|
| 1539 |
-
"repeats": 1,
|
| 1540 |
-
"should_decontaminate": false,
|
| 1541 |
-
"metadata": {
|
| 1542 |
-
"version": 1.0
|
| 1543 |
-
}
|
| 1544 |
-
},
|
| 1545 |
-
"ceval-valid_legal_professional": {
|
| 1546 |
-
"task": "ceval-valid_legal_professional",
|
| 1547 |
-
"group": "ceval-valid",
|
| 1548 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1549 |
-
"dataset_name": "legal_professional",
|
| 1550 |
-
"validation_split": "val",
|
| 1551 |
-
"fewshot_split": "dev",
|
| 1552 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1553 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1554 |
-
"doc_to_choice": [
|
| 1555 |
-
"A",
|
| 1556 |
-
"B",
|
| 1557 |
-
"C",
|
| 1558 |
-
"D"
|
| 1559 |
-
],
|
| 1560 |
-
"description": "以下是中国关于法律职业资格的单项选择题，请选出其中的正确答案。\n\n",
|
| 1561 |
-
"target_delimiter": " ",
|
| 1562 |
-
"fewshot_delimiter": "\n\n",
|
| 1563 |
-
"fewshot_config": {
|
| 1564 |
-
"sampler": "first_n"
|
| 1565 |
-
},
|
| 1566 |
-
"metric_list": [
|
| 1567 |
-
{
|
| 1568 |
-
"metric": "acc",
|
| 1569 |
-
"aggregation": "mean",
|
| 1570 |
-
"higher_is_better": true
|
| 1571 |
-
},
|
| 1572 |
-
{
|
| 1573 |
-
"metric": "acc_norm",
|
| 1574 |
-
"aggregation": "mean",
|
| 1575 |
-
"higher_is_better": true
|
| 1576 |
-
}
|
| 1577 |
-
],
|
| 1578 |
-
"output_type": "multiple_choice",
|
| 1579 |
-
"repeats": 1,
|
| 1580 |
-
"should_decontaminate": false,
|
| 1581 |
-
"metadata": {
|
| 1582 |
-
"version": 1.0
|
| 1583 |
-
}
|
| 1584 |
-
},
|
| 1585 |
-
"ceval-valid_logic": {
|
| 1586 |
-
"task": "ceval-valid_logic",
|
| 1587 |
-
"group": "ceval-valid",
|
| 1588 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1589 |
-
"dataset_name": "logic",
|
| 1590 |
-
"validation_split": "val",
|
| 1591 |
-
"fewshot_split": "dev",
|
| 1592 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1593 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1594 |
-
"doc_to_choice": [
|
| 1595 |
-
"A",
|
| 1596 |
-
"B",
|
| 1597 |
-
"C",
|
| 1598 |
-
"D"
|
| 1599 |
-
],
|
| 1600 |
-
"description": "以下是中国关于逻辑学的单项选择题，请选出其中的正确答案。\n\n",
|
| 1601 |
-
"target_delimiter": " ",
|
| 1602 |
-
"fewshot_delimiter": "\n\n",
|
| 1603 |
-
"fewshot_config": {
|
| 1604 |
-
"sampler": "first_n"
|
| 1605 |
-
},
|
| 1606 |
-
"metric_list": [
|
| 1607 |
-
{
|
| 1608 |
-
"metric": "acc",
|
| 1609 |
-
"aggregation": "mean",
|
| 1610 |
-
"higher_is_better": true
|
| 1611 |
-
},
|
| 1612 |
-
{
|
| 1613 |
-
"metric": "acc_norm",
|
| 1614 |
-
"aggregation": "mean",
|
| 1615 |
-
"higher_is_better": true
|
| 1616 |
-
}
|
| 1617 |
-
],
|
| 1618 |
-
"output_type": "multiple_choice",
|
| 1619 |
-
"repeats": 1,
|
| 1620 |
-
"should_decontaminate": false,
|
| 1621 |
-
"metadata": {
|
| 1622 |
-
"version": 1.0
|
| 1623 |
-
}
|
| 1624 |
-
},
|
| 1625 |
-
"ceval-valid_mao_zedong_thought": {
|
| 1626 |
-
"task": "ceval-valid_mao_zedong_thought",
|
| 1627 |
-
"group": "ceval-valid",
|
| 1628 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1629 |
-
"dataset_name": "mao_zedong_thought",
|
| 1630 |
-
"validation_split": "val",
|
| 1631 |
-
"fewshot_split": "dev",
|
| 1632 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1633 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1634 |
-
"doc_to_choice": [
|
| 1635 |
-
"A",
|
| 1636 |
-
"B",
|
| 1637 |
-
"C",
|
| 1638 |
-
"D"
|
| 1639 |
-
],
|
| 1640 |
-
"description": "以下是中国关于毛泽东思想和中国特色社会主义理论体系概论的单项选择题，请选出其中的正确答案。\n\n",
|
| 1641 |
-
"target_delimiter": " ",
|
| 1642 |
-
"fewshot_delimiter": "\n\n",
|
| 1643 |
-
"fewshot_config": {
|
| 1644 |
-
"sampler": "first_n"
|
| 1645 |
-
},
|
| 1646 |
-
"metric_list": [
|
| 1647 |
-
{
|
| 1648 |
-
"metric": "acc",
|
| 1649 |
-
"aggregation": "mean",
|
| 1650 |
-
"higher_is_better": true
|
| 1651 |
-
},
|
| 1652 |
-
{
|
| 1653 |
-
"metric": "acc_norm",
|
| 1654 |
-
"aggregation": "mean",
|
| 1655 |
-
"higher_is_better": true
|
| 1656 |
-
}
|
| 1657 |
-
],
|
| 1658 |
-
"output_type": "multiple_choice",
|
| 1659 |
-
"repeats": 1,
|
| 1660 |
-
"should_decontaminate": false,
|
| 1661 |
-
"metadata": {
|
| 1662 |
-
"version": 1.0
|
| 1663 |
-
}
|
| 1664 |
-
},
|
| 1665 |
-
"ceval-valid_marxism": {
|
| 1666 |
-
"task": "ceval-valid_marxism",
|
| 1667 |
-
"group": "ceval-valid",
|
| 1668 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1669 |
-
"dataset_name": "marxism",
|
| 1670 |
-
"validation_split": "val",
|
| 1671 |
-
"fewshot_split": "dev",
|
| 1672 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1673 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1674 |
-
"doc_to_choice": [
|
| 1675 |
-
"A",
|
| 1676 |
-
"B",
|
| 1677 |
-
"C",
|
| 1678 |
-
"D"
|
| 1679 |
-
],
|
| 1680 |
-
"description": "以下是中国关于马克思主义基本原理的单项选择题，请选出其中的正确答案。\n\n",
|
| 1681 |
-
"target_delimiter": " ",
|
| 1682 |
-
"fewshot_delimiter": "\n\n",
|
| 1683 |
-
"fewshot_config": {
|
| 1684 |
-
"sampler": "first_n"
|
| 1685 |
-
},
|
| 1686 |
-
"metric_list": [
|
| 1687 |
-
{
|
| 1688 |
-
"metric": "acc",
|
| 1689 |
-
"aggregation": "mean",
|
| 1690 |
-
"higher_is_better": true
|
| 1691 |
-
},
|
| 1692 |
-
{
|
| 1693 |
-
"metric": "acc_norm",
|
| 1694 |
-
"aggregation": "mean",
|
| 1695 |
-
"higher_is_better": true
|
| 1696 |
-
}
|
| 1697 |
-
],
|
| 1698 |
-
"output_type": "multiple_choice",
|
| 1699 |
-
"repeats": 1,
|
| 1700 |
-
"should_decontaminate": false,
|
| 1701 |
-
"metadata": {
|
| 1702 |
-
"version": 1.0
|
| 1703 |
-
}
|
| 1704 |
-
},
|
| 1705 |
-
"ceval-valid_metrology_engineer": {
|
| 1706 |
-
"task": "ceval-valid_metrology_engineer",
|
| 1707 |
-
"group": "ceval-valid",
|
| 1708 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1709 |
-
"dataset_name": "metrology_engineer",
|
| 1710 |
-
"validation_split": "val",
|
| 1711 |
-
"fewshot_split": "dev",
|
| 1712 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1713 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1714 |
-
"doc_to_choice": [
|
| 1715 |
-
"A",
|
| 1716 |
-
"B",
|
| 1717 |
-
"C",
|
| 1718 |
-
"D"
|
| 1719 |
-
],
|
| 1720 |
-
"description": "以下是中国关于注册计量师的单���选择题，请选出其中的正确答案。\n\n",
|
| 1721 |
-
"target_delimiter": " ",
|
| 1722 |
-
"fewshot_delimiter": "\n\n",
|
| 1723 |
-
"fewshot_config": {
|
| 1724 |
-
"sampler": "first_n"
|
| 1725 |
-
},
|
| 1726 |
-
"metric_list": [
|
| 1727 |
-
{
|
| 1728 |
-
"metric": "acc",
|
| 1729 |
-
"aggregation": "mean",
|
| 1730 |
-
"higher_is_better": true
|
| 1731 |
-
},
|
| 1732 |
-
{
|
| 1733 |
-
"metric": "acc_norm",
|
| 1734 |
-
"aggregation": "mean",
|
| 1735 |
-
"higher_is_better": true
|
| 1736 |
-
}
|
| 1737 |
-
],
|
| 1738 |
-
"output_type": "multiple_choice",
|
| 1739 |
-
"repeats": 1,
|
| 1740 |
-
"should_decontaminate": false,
|
| 1741 |
-
"metadata": {
|
| 1742 |
-
"version": 1.0
|
| 1743 |
-
}
|
| 1744 |
-
},
|
| 1745 |
-
"ceval-valid_middle_school_biology": {
|
| 1746 |
-
"task": "ceval-valid_middle_school_biology",
|
| 1747 |
-
"group": "ceval-valid",
|
| 1748 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1749 |
-
"dataset_name": "middle_school_biology",
|
| 1750 |
-
"validation_split": "val",
|
| 1751 |
-
"fewshot_split": "dev",
|
| 1752 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1753 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1754 |
-
"doc_to_choice": [
|
| 1755 |
-
"A",
|
| 1756 |
-
"B",
|
| 1757 |
-
"C",
|
| 1758 |
-
"D"
|
| 1759 |
-
],
|
| 1760 |
-
"description": "以下是中国关于初中生物的单项选择题，请选出其中的正确答案。\n\n",
|
| 1761 |
-
"target_delimiter": " ",
|
| 1762 |
-
"fewshot_delimiter": "\n\n",
|
| 1763 |
-
"fewshot_config": {
|
| 1764 |
-
"sampler": "first_n"
|
| 1765 |
-
},
|
| 1766 |
-
"metric_list": [
|
| 1767 |
-
{
|
| 1768 |
-
"metric": "acc",
|
| 1769 |
-
"aggregation": "mean",
|
| 1770 |
-
"higher_is_better": true
|
| 1771 |
-
},
|
| 1772 |
-
{
|
| 1773 |
-
"metric": "acc_norm",
|
| 1774 |
-
"aggregation": "mean",
|
| 1775 |
-
"higher_is_better": true
|
| 1776 |
-
}
|
| 1777 |
-
],
|
| 1778 |
-
"output_type": "multiple_choice",
|
| 1779 |
-
"repeats": 1,
|
| 1780 |
-
"should_decontaminate": false,
|
| 1781 |
-
"metadata": {
|
| 1782 |
-
"version": 1.0
|
| 1783 |
-
}
|
| 1784 |
-
},
|
| 1785 |
-
"ceval-valid_middle_school_chemistry": {
|
| 1786 |
-
"task": "ceval-valid_middle_school_chemistry",
|
| 1787 |
-
"group": "ceval-valid",
|
| 1788 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1789 |
-
"dataset_name": "middle_school_chemistry",
|
| 1790 |
-
"validation_split": "val",
|
| 1791 |
-
"fewshot_split": "dev",
|
| 1792 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1793 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1794 |
-
"doc_to_choice": [
|
| 1795 |
-
"A",
|
| 1796 |
-
"B",
|
| 1797 |
-
"C",
|
| 1798 |
-
"D"
|
| 1799 |
-
],
|
| 1800 |
-
"description": "以下是中国关于初中化学的单项选择题，请选出其中的正确答案。\n\n",
|
| 1801 |
-
"target_delimiter": " ",
|
| 1802 |
-
"fewshot_delimiter": "\n\n",
|
| 1803 |
-
"fewshot_config": {
|
| 1804 |
-
"sampler": "first_n"
|
| 1805 |
-
},
|
| 1806 |
-
"metric_list": [
|
| 1807 |
-
{
|
| 1808 |
-
"metric": "acc",
|
| 1809 |
-
"aggregation": "mean",
|
| 1810 |
-
"higher_is_better": true
|
| 1811 |
-
},
|
| 1812 |
-
{
|
| 1813 |
-
"metric": "acc_norm",
|
| 1814 |
-
"aggregation": "mean",
|
| 1815 |
-
"higher_is_better": true
|
| 1816 |
-
}
|
| 1817 |
-
],
|
| 1818 |
-
"output_type": "multiple_choice",
|
| 1819 |
-
"repeats": 1,
|
| 1820 |
-
"should_decontaminate": false,
|
| 1821 |
-
"metadata": {
|
| 1822 |
-
"version": 1.0
|
| 1823 |
-
}
|
| 1824 |
-
},
|
| 1825 |
-
"ceval-valid_middle_school_geography": {
|
| 1826 |
-
"task": "ceval-valid_middle_school_geography",
|
| 1827 |
-
"group": "ceval-valid",
|
| 1828 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1829 |
-
"dataset_name": "middle_school_geography",
|
| 1830 |
-
"validation_split": "val",
|
| 1831 |
-
"fewshot_split": "dev",
|
| 1832 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1833 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1834 |
-
"doc_to_choice": [
|
| 1835 |
-
"A",
|
| 1836 |
-
"B",
|
| 1837 |
-
"C",
|
| 1838 |
-
"D"
|
| 1839 |
-
],
|
| 1840 |
-
"description": "以下是中国关于初中地理的单项选择题，请选出其中的正确答案。\n\n",
|
| 1841 |
-
"target_delimiter": " ",
|
| 1842 |
-
"fewshot_delimiter": "\n\n",
|
| 1843 |
-
"fewshot_config": {
|
| 1844 |
-
"sampler": "first_n"
|
| 1845 |
-
},
|
| 1846 |
-
"metric_list": [
|
| 1847 |
-
{
|
| 1848 |
-
"metric": "acc",
|
| 1849 |
-
"aggregation": "mean",
|
| 1850 |
-
"higher_is_better": true
|
| 1851 |
-
},
|
| 1852 |
-
{
|
| 1853 |
-
"metric": "acc_norm",
|
| 1854 |
-
"aggregation": "mean",
|
| 1855 |
-
"higher_is_better": true
|
| 1856 |
-
}
|
| 1857 |
-
],
|
| 1858 |
-
"output_type": "multiple_choice",
|
| 1859 |
-
"repeats": 1,
|
| 1860 |
-
"should_decontaminate": false,
|
| 1861 |
-
"metadata": {
|
| 1862 |
-
"version": 1.0
|
| 1863 |
-
}
|
| 1864 |
-
},
|
| 1865 |
-
"ceval-valid_middle_school_history": {
|
| 1866 |
-
"task": "ceval-valid_middle_school_history",
|
| 1867 |
-
"group": "ceval-valid",
|
| 1868 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1869 |
-
"dataset_name": "middle_school_history",
|
| 1870 |
-
"validation_split": "val",
|
| 1871 |
-
"fewshot_split": "dev",
|
| 1872 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1873 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1874 |
-
"doc_to_choice": [
|
| 1875 |
-
"A",
|
| 1876 |
-
"B",
|
| 1877 |
-
"C",
|
| 1878 |
-
"D"
|
| 1879 |
-
],
|
| 1880 |
-
"description": "以下是中国关于初中历史的单项选择题，请选出其中的正确答案。\n\n",
|
| 1881 |
-
"target_delimiter": " ",
|
| 1882 |
-
"fewshot_delimiter": "\n\n",
|
| 1883 |
-
"fewshot_config": {
|
| 1884 |
-
"sampler": "first_n"
|
| 1885 |
-
},
|
| 1886 |
-
"metric_list": [
|
| 1887 |
-
{
|
| 1888 |
-
"metric": "acc",
|
| 1889 |
-
"aggregation": "mean",
|
| 1890 |
-
"higher_is_better": true
|
| 1891 |
-
},
|
| 1892 |
-
{
|
| 1893 |
-
"metric": "acc_norm",
|
| 1894 |
-
"aggregation": "mean",
|
| 1895 |
-
"higher_is_better": true
|
| 1896 |
-
}
|
| 1897 |
-
],
|
| 1898 |
-
"output_type": "multiple_choice",
|
| 1899 |
-
"repeats": 1,
|
| 1900 |
-
"should_decontaminate": false,
|
| 1901 |
-
"metadata": {
|
| 1902 |
-
"version": 1.0
|
| 1903 |
-
}
|
| 1904 |
-
},
|
| 1905 |
-
"ceval-valid_middle_school_mathematics": {
|
| 1906 |
-
"task": "ceval-valid_middle_school_mathematics",
|
| 1907 |
-
"group": "ceval-valid",
|
| 1908 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1909 |
-
"dataset_name": "middle_school_mathematics",
|
| 1910 |
-
"validation_split": "val",
|
| 1911 |
-
"fewshot_split": "dev",
|
| 1912 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1913 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1914 |
-
"doc_to_choice": [
|
| 1915 |
-
"A",
|
| 1916 |
-
"B",
|
| 1917 |
-
"C",
|
| 1918 |
-
"D"
|
| 1919 |
-
],
|
| 1920 |
-
"description": "以下是中国关于初中数学的单项选择题，请选出其中的正确答案。\n\n",
|
| 1921 |
-
"target_delimiter": " ",
|
| 1922 |
-
"fewshot_delimiter": "\n\n",
|
| 1923 |
-
"fewshot_config": {
|
| 1924 |
-
"sampler": "first_n"
|
| 1925 |
-
},
|
| 1926 |
-
"metric_list": [
|
| 1927 |
-
{
|
| 1928 |
-
"metric": "acc",
|
| 1929 |
-
"aggregation": "mean",
|
| 1930 |
-
"higher_is_better": true
|
| 1931 |
-
},
|
| 1932 |
-
{
|
| 1933 |
-
"metric": "acc_norm",
|
| 1934 |
-
"aggregation": "mean",
|
| 1935 |
-
"higher_is_better": true
|
| 1936 |
-
}
|
| 1937 |
-
],
|
| 1938 |
-
"output_type": "multiple_choice",
|
| 1939 |
-
"repeats": 1,
|
| 1940 |
-
"should_decontaminate": false,
|
| 1941 |
-
"metadata": {
|
| 1942 |
-
"version": 1.0
|
| 1943 |
-
}
|
| 1944 |
-
},
|
| 1945 |
-
"ceval-valid_middle_school_physics": {
|
| 1946 |
-
"task": "ceval-valid_middle_school_physics",
|
| 1947 |
-
"group": "ceval-valid",
|
| 1948 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1949 |
-
"dataset_name": "middle_school_physics",
|
| 1950 |
-
"validation_split": "val",
|
| 1951 |
-
"fewshot_split": "dev",
|
| 1952 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1953 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1954 |
-
"doc_to_choice": [
|
| 1955 |
-
"A",
|
| 1956 |
-
"B",
|
| 1957 |
-
"C",
|
| 1958 |
-
"D"
|
| 1959 |
-
],
|
| 1960 |
-
"description": "以下是中国关于初中物理的单项选择题，请选出其中的正确答案。\n\n",
|
| 1961 |
-
"target_delimiter": " ",
|
| 1962 |
-
"fewshot_delimiter": "\n\n",
|
| 1963 |
-
"fewshot_config": {
|
| 1964 |
-
"sampler": "first_n"
|
| 1965 |
-
},
|
| 1966 |
-
"metric_list": [
|
| 1967 |
-
{
|
| 1968 |
-
"metric": "acc",
|
| 1969 |
-
"aggregation": "mean",
|
| 1970 |
-
"higher_is_better": true
|
| 1971 |
-
},
|
| 1972 |
-
{
|
| 1973 |
-
"metric": "acc_norm",
|
| 1974 |
-
"aggregation": "mean",
|
| 1975 |
-
"higher_is_better": true
|
| 1976 |
-
}
|
| 1977 |
-
],
|
| 1978 |
-
"output_type": "multiple_choice",
|
| 1979 |
-
"repeats": 1,
|
| 1980 |
-
"should_decontaminate": false,
|
| 1981 |
-
"metadata": {
|
| 1982 |
-
"version": 1.0
|
| 1983 |
-
}
|
| 1984 |
-
},
|
| 1985 |
-
"ceval-valid_middle_school_politics": {
|
| 1986 |
-
"task": "ceval-valid_middle_school_politics",
|
| 1987 |
-
"group": "ceval-valid",
|
| 1988 |
-
"dataset_path": "ceval/ceval-exam",
|
| 1989 |
-
"dataset_name": "middle_school_politics",
|
| 1990 |
-
"validation_split": "val",
|
| 1991 |
-
"fewshot_split": "dev",
|
| 1992 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 1993 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 1994 |
-
"doc_to_choice": [
|
| 1995 |
-
"A",
|
| 1996 |
-
"B",
|
| 1997 |
-
"C",
|
| 1998 |
-
"D"
|
| 1999 |
-
],
|
| 2000 |
-
"description": "以下是中国关于初中政治的单项选择题，请选出其中的正确答案。\n\n",
|
| 2001 |
-
"target_delimiter": " ",
|
| 2002 |
-
"fewshot_delimiter": "\n\n",
|
| 2003 |
-
"fewshot_config": {
|
| 2004 |
-
"sampler": "first_n"
|
| 2005 |
-
},
|
| 2006 |
-
"metric_list": [
|
| 2007 |
-
{
|
| 2008 |
-
"metric": "acc",
|
| 2009 |
-
"aggregation": "mean",
|
| 2010 |
-
"higher_is_better": true
|
| 2011 |
-
},
|
| 2012 |
-
{
|
| 2013 |
-
"metric": "acc_norm",
|
| 2014 |
-
"aggregation": "mean",
|
| 2015 |
-
"higher_is_better": true
|
| 2016 |
-
}
|
| 2017 |
-
],
|
| 2018 |
-
"output_type": "multiple_choice",
|
| 2019 |
-
"repeats": 1,
|
| 2020 |
-
"should_decontaminate": false,
|
| 2021 |
-
"metadata": {
|
| 2022 |
-
"version": 1.0
|
| 2023 |
-
}
|
| 2024 |
-
},
|
| 2025 |
-
"ceval-valid_modern_chinese_history": {
|
| 2026 |
-
"task": "ceval-valid_modern_chinese_history",
|
| 2027 |
-
"group": "ceval-valid",
|
| 2028 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2029 |
-
"dataset_name": "modern_chinese_history",
|
| 2030 |
-
"validation_split": "val",
|
| 2031 |
-
"fewshot_split": "dev",
|
| 2032 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2033 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2034 |
-
"doc_to_choice": [
|
| 2035 |
-
"A",
|
| 2036 |
-
"B",
|
| 2037 |
-
"C",
|
| 2038 |
-
"D"
|
| 2039 |
-
],
|
| 2040 |
-
"description": "以下是中国关于近代史纲要的单项选择题，请选出其中的正确答案。\n\n",
|
| 2041 |
-
"target_delimiter": " ",
|
| 2042 |
-
"fewshot_delimiter": "\n\n",
|
| 2043 |
-
"fewshot_config": {
|
| 2044 |
-
"sampler": "first_n"
|
| 2045 |
-
},
|
| 2046 |
-
"metric_list": [
|
| 2047 |
-
{
|
| 2048 |
-
"metric": "acc",
|
| 2049 |
-
"aggregation": "mean",
|
| 2050 |
-
"higher_is_better": true
|
| 2051 |
-
},
|
| 2052 |
-
{
|
| 2053 |
-
"metric": "acc_norm",
|
| 2054 |
-
"aggregation": "mean",
|
| 2055 |
-
"higher_is_better": true
|
| 2056 |
-
}
|
| 2057 |
-
],
|
| 2058 |
-
"output_type": "multiple_choice",
|
| 2059 |
-
"repeats": 1,
|
| 2060 |
-
"should_decontaminate": false,
|
| 2061 |
-
"metadata": {
|
| 2062 |
-
"version": 1.0
|
| 2063 |
-
}
|
| 2064 |
-
},
|
| 2065 |
-
"ceval-valid_operating_system": {
|
| 2066 |
-
"task": "ceval-valid_operating_system",
|
| 2067 |
-
"group": "ceval-valid",
|
| 2068 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2069 |
-
"dataset_name": "operating_system",
|
| 2070 |
-
"validation_split": "val",
|
| 2071 |
-
"fewshot_split": "dev",
|
| 2072 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2073 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2074 |
-
"doc_to_choice": [
|
| 2075 |
-
"A",
|
| 2076 |
-
"B",
|
| 2077 |
-
"C",
|
| 2078 |
-
"D"
|
| 2079 |
-
],
|
| 2080 |
-
"description": "以下是中国关于操作系统的单项选择题，请选出其中的正确答案。\n\n",
|
| 2081 |
-
"target_delimiter": " ",
|
| 2082 |
-
"fewshot_delimiter": "\n\n",
|
| 2083 |
-
"fewshot_config": {
|
| 2084 |
-
"sampler": "first_n"
|
| 2085 |
-
},
|
| 2086 |
-
"metric_list": [
|
| 2087 |
-
{
|
| 2088 |
-
"metric": "acc",
|
| 2089 |
-
"aggregation": "mean",
|
| 2090 |
-
"higher_is_better": true
|
| 2091 |
-
},
|
| 2092 |
-
{
|
| 2093 |
-
"metric": "acc_norm",
|
| 2094 |
-
"aggregation": "mean",
|
| 2095 |
-
"higher_is_better": true
|
| 2096 |
-
}
|
| 2097 |
-
],
|
| 2098 |
-
"output_type": "multiple_choice",
|
| 2099 |
-
"repeats": 1,
|
| 2100 |
-
"should_decontaminate": false,
|
| 2101 |
-
"metadata": {
|
| 2102 |
-
"version": 1.0
|
| 2103 |
-
}
|
| 2104 |
-
},
|
| 2105 |
-
"ceval-valid_physician": {
|
| 2106 |
-
"task": "ceval-valid_physician",
|
| 2107 |
-
"group": "ceval-valid",
|
| 2108 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2109 |
-
"dataset_name": "physician",
|
| 2110 |
-
"validation_split": "val",
|
| 2111 |
-
"fewshot_split": "dev",
|
| 2112 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2113 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2114 |
-
"doc_to_choice": [
|
| 2115 |
-
"A",
|
| 2116 |
-
"B",
|
| 2117 |
-
"C",
|
| 2118 |
-
"D"
|
| 2119 |
-
],
|
| 2120 |
-
"description": "以下是中国关于医师资格的单项选择题，请选出其中的正确答案。\n\n",
|
| 2121 |
-
"target_delimiter": " ",
|
| 2122 |
-
"fewshot_delimiter": "\n\n",
|
| 2123 |
-
"fewshot_config": {
|
| 2124 |
-
"sampler": "first_n"
|
| 2125 |
-
},
|
| 2126 |
-
"metric_list": [
|
| 2127 |
-
{
|
| 2128 |
-
"metric": "acc",
|
| 2129 |
-
"aggregation": "mean",
|
| 2130 |
-
"higher_is_better": true
|
| 2131 |
-
},
|
| 2132 |
-
{
|
| 2133 |
-
"metric": "acc_norm",
|
| 2134 |
-
"aggregation": "mean",
|
| 2135 |
-
"higher_is_better": true
|
| 2136 |
-
}
|
| 2137 |
-
],
|
| 2138 |
-
"output_type": "multiple_choice",
|
| 2139 |
-
"repeats": 1,
|
| 2140 |
-
"should_decontaminate": false,
|
| 2141 |
-
"metadata": {
|
| 2142 |
-
"version": 1.0
|
| 2143 |
-
}
|
| 2144 |
-
},
|
| 2145 |
-
"ceval-valid_plant_protection": {
|
| 2146 |
-
"task": "ceval-valid_plant_protection",
|
| 2147 |
-
"group": "ceval-valid",
|
| 2148 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2149 |
-
"dataset_name": "plant_protection",
|
| 2150 |
-
"validation_split": "val",
|
| 2151 |
-
"fewshot_split": "dev",
|
| 2152 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2153 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2154 |
-
"doc_to_choice": [
|
| 2155 |
-
"A",
|
| 2156 |
-
"B",
|
| 2157 |
-
"C",
|
| 2158 |
-
"D"
|
| 2159 |
-
],
|
| 2160 |
-
"description": "以下是中国关于植物保护的单项选择题，请选出其中的正确答案。\n\n",
|
| 2161 |
-
"target_delimiter": " ",
|
| 2162 |
-
"fewshot_delimiter": "\n\n",
|
| 2163 |
-
"fewshot_config": {
|
| 2164 |
-
"sampler": "first_n"
|
| 2165 |
-
},
|
| 2166 |
-
"metric_list": [
|
| 2167 |
-
{
|
| 2168 |
-
"metric": "acc",
|
| 2169 |
-
"aggregation": "mean",
|
| 2170 |
-
"higher_is_better": true
|
| 2171 |
-
},
|
| 2172 |
-
{
|
| 2173 |
-
"metric": "acc_norm",
|
| 2174 |
-
"aggregation": "mean",
|
| 2175 |
-
"higher_is_better": true
|
| 2176 |
-
}
|
| 2177 |
-
],
|
| 2178 |
-
"output_type": "multiple_choice",
|
| 2179 |
-
"repeats": 1,
|
| 2180 |
-
"should_decontaminate": false,
|
| 2181 |
-
"metadata": {
|
| 2182 |
-
"version": 1.0
|
| 2183 |
-
}
|
| 2184 |
-
},
|
| 2185 |
-
"ceval-valid_probability_and_statistics": {
|
| 2186 |
-
"task": "ceval-valid_probability_and_statistics",
|
| 2187 |
-
"group": "ceval-valid",
|
| 2188 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2189 |
-
"dataset_name": "probability_and_statistics",
|
| 2190 |
-
"validation_split": "val",
|
| 2191 |
-
"fewshot_split": "dev",
|
| 2192 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2193 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2194 |
-
"doc_to_choice": [
|
| 2195 |
-
"A",
|
| 2196 |
-
"B",
|
| 2197 |
-
"C",
|
| 2198 |
-
"D"
|
| 2199 |
-
],
|
| 2200 |
-
"description": "以下是中国关于概率统计的单项选择题，请选出其中的正确答案。\n\n",
|
| 2201 |
-
"target_delimiter": " ",
|
| 2202 |
-
"fewshot_delimiter": "\n\n",
|
| 2203 |
-
"fewshot_config": {
|
| 2204 |
-
"sampler": "first_n"
|
| 2205 |
-
},
|
| 2206 |
-
"metric_list": [
|
| 2207 |
-
{
|
| 2208 |
-
"metric": "acc",
|
| 2209 |
-
"aggregation": "mean",
|
| 2210 |
-
"higher_is_better": true
|
| 2211 |
-
},
|
| 2212 |
-
{
|
| 2213 |
-
"metric": "acc_norm",
|
| 2214 |
-
"aggregation": "mean",
|
| 2215 |
-
"higher_is_better": true
|
| 2216 |
-
}
|
| 2217 |
-
],
|
| 2218 |
-
"output_type": "multiple_choice",
|
| 2219 |
-
"repeats": 1,
|
| 2220 |
-
"should_decontaminate": false,
|
| 2221 |
-
"metadata": {
|
| 2222 |
-
"version": 1.0
|
| 2223 |
-
}
|
| 2224 |
-
},
|
| 2225 |
-
"ceval-valid_professional_tour_guide": {
|
| 2226 |
-
"task": "ceval-valid_professional_tour_guide",
|
| 2227 |
-
"group": "ceval-valid",
|
| 2228 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2229 |
-
"dataset_name": "professional_tour_guide",
|
| 2230 |
-
"validation_split": "val",
|
| 2231 |
-
"fewshot_split": "dev",
|
| 2232 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2233 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2234 |
-
"doc_to_choice": [
|
| 2235 |
-
"A",
|
| 2236 |
-
"B",
|
| 2237 |
-
"C",
|
| 2238 |
-
"D"
|
| 2239 |
-
],
|
| 2240 |
-
"description": "以下是中国关于导游资格的单项选择题，请选出其中的正确答案。\n\n",
|
| 2241 |
-
"target_delimiter": " ",
|
| 2242 |
-
"fewshot_delimiter": "\n\n",
|
| 2243 |
-
"fewshot_config": {
|
| 2244 |
-
"sampler": "first_n"
|
| 2245 |
-
},
|
| 2246 |
-
"metric_list": [
|
| 2247 |
-
{
|
| 2248 |
-
"metric": "acc",
|
| 2249 |
-
"aggregation": "mean",
|
| 2250 |
-
"higher_is_better": true
|
| 2251 |
-
},
|
| 2252 |
-
{
|
| 2253 |
-
"metric": "acc_norm",
|
| 2254 |
-
"aggregation": "mean",
|
| 2255 |
-
"higher_is_better": true
|
| 2256 |
-
}
|
| 2257 |
-
],
|
| 2258 |
-
"output_type": "multiple_choice",
|
| 2259 |
-
"repeats": 1,
|
| 2260 |
-
"should_decontaminate": false,
|
| 2261 |
-
"metadata": {
|
| 2262 |
-
"version": 1.0
|
| 2263 |
-
}
|
| 2264 |
-
},
|
| 2265 |
-
"ceval-valid_sports_science": {
|
| 2266 |
-
"task": "ceval-valid_sports_science",
|
| 2267 |
-
"group": "ceval-valid",
|
| 2268 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2269 |
-
"dataset_name": "sports_science",
|
| 2270 |
-
"validation_split": "val",
|
| 2271 |
-
"fewshot_split": "dev",
|
| 2272 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2273 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2274 |
-
"doc_to_choice": [
|
| 2275 |
-
"A",
|
| 2276 |
-
"B",
|
| 2277 |
-
"C",
|
| 2278 |
-
"D"
|
| 2279 |
-
],
|
| 2280 |
-
"description": "以下是中国关于体育学的单项选择题，请选出其中的正确答案。\n\n",
|
| 2281 |
-
"target_delimiter": " ",
|
| 2282 |
-
"fewshot_delimiter": "\n\n",
|
| 2283 |
-
"fewshot_config": {
|
| 2284 |
-
"sampler": "first_n"
|
| 2285 |
-
},
|
| 2286 |
-
"metric_list": [
|
| 2287 |
-
{
|
| 2288 |
-
"metric": "acc",
|
| 2289 |
-
"aggregation": "mean",
|
| 2290 |
-
"higher_is_better": true
|
| 2291 |
-
},
|
| 2292 |
-
{
|
| 2293 |
-
"metric": "acc_norm",
|
| 2294 |
-
"aggregation": "mean",
|
| 2295 |
-
"higher_is_better": true
|
| 2296 |
-
}
|
| 2297 |
-
],
|
| 2298 |
-
"output_type": "multiple_choice",
|
| 2299 |
-
"repeats": 1,
|
| 2300 |
-
"should_decontaminate": false,
|
| 2301 |
-
"metadata": {
|
| 2302 |
-
"version": 1.0
|
| 2303 |
-
}
|
| 2304 |
-
},
|
| 2305 |
-
"ceval-valid_tax_accountant": {
|
| 2306 |
-
"task": "ceval-valid_tax_accountant",
|
| 2307 |
-
"group": "ceval-valid",
|
| 2308 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2309 |
-
"dataset_name": "tax_accountant",
|
| 2310 |
-
"validation_split": "val",
|
| 2311 |
-
"fewshot_split": "dev",
|
| 2312 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2313 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2314 |
-
"doc_to_choice": [
|
| 2315 |
-
"A",
|
| 2316 |
-
"B",
|
| 2317 |
-
"C",
|
| 2318 |
-
"D"
|
| 2319 |
-
],
|
| 2320 |
-
"description": "以下是中国关于税务师的单项选择题，请选出其中的正确答案。\n\n",
|
| 2321 |
-
"target_delimiter": " ",
|
| 2322 |
-
"fewshot_delimiter": "\n\n",
|
| 2323 |
-
"fewshot_config": {
|
| 2324 |
-
"sampler": "first_n"
|
| 2325 |
-
},
|
| 2326 |
-
"metric_list": [
|
| 2327 |
-
{
|
| 2328 |
-
"metric": "acc",
|
| 2329 |
-
"aggregation": "mean",
|
| 2330 |
-
"higher_is_better": true
|
| 2331 |
-
},
|
| 2332 |
-
{
|
| 2333 |
-
"metric": "acc_norm",
|
| 2334 |
-
"aggregation": "mean",
|
| 2335 |
-
"higher_is_better": true
|
| 2336 |
-
}
|
| 2337 |
-
],
|
| 2338 |
-
"output_type": "multiple_choice",
|
| 2339 |
-
"repeats": 1,
|
| 2340 |
-
"should_decontaminate": false,
|
| 2341 |
-
"metadata": {
|
| 2342 |
-
"version": 1.0
|
| 2343 |
-
}
|
| 2344 |
-
},
|
| 2345 |
-
"ceval-valid_teacher_qualification": {
|
| 2346 |
-
"task": "ceval-valid_teacher_qualification",
|
| 2347 |
-
"group": "ceval-valid",
|
| 2348 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2349 |
-
"dataset_name": "teacher_qualification",
|
| 2350 |
-
"validation_split": "val",
|
| 2351 |
-
"fewshot_split": "dev",
|
| 2352 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2353 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2354 |
-
"doc_to_choice": [
|
| 2355 |
-
"A",
|
| 2356 |
-
"B",
|
| 2357 |
-
"C",
|
| 2358 |
-
"D"
|
| 2359 |
-
],
|
| 2360 |
-
"description": "以下是中国关于教师资格的单项选择题，请选出其中的正确答案。\n\n",
|
| 2361 |
-
"target_delimiter": " ",
|
| 2362 |
-
"fewshot_delimiter": "\n\n",
|
| 2363 |
-
"fewshot_config": {
|
| 2364 |
-
"sampler": "first_n"
|
| 2365 |
-
},
|
| 2366 |
-
"metric_list": [
|
| 2367 |
-
{
|
| 2368 |
-
"metric": "acc",
|
| 2369 |
-
"aggregation": "mean",
|
| 2370 |
-
"higher_is_better": true
|
| 2371 |
-
},
|
| 2372 |
-
{
|
| 2373 |
-
"metric": "acc_norm",
|
| 2374 |
-
"aggregation": "mean",
|
| 2375 |
-
"higher_is_better": true
|
| 2376 |
-
}
|
| 2377 |
-
],
|
| 2378 |
-
"output_type": "multiple_choice",
|
| 2379 |
-
"repeats": 1,
|
| 2380 |
-
"should_decontaminate": false,
|
| 2381 |
-
"metadata": {
|
| 2382 |
-
"version": 1.0
|
| 2383 |
-
}
|
| 2384 |
-
},
|
| 2385 |
-
"ceval-valid_urban_and_rural_planner": {
|
| 2386 |
-
"task": "ceval-valid_urban_and_rural_planner",
|
| 2387 |
-
"group": "ceval-valid",
|
| 2388 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2389 |
-
"dataset_name": "urban_and_rural_planner",
|
| 2390 |
-
"validation_split": "val",
|
| 2391 |
-
"fewshot_split": "dev",
|
| 2392 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2393 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2394 |
-
"doc_to_choice": [
|
| 2395 |
-
"A",
|
| 2396 |
-
"B",
|
| 2397 |
-
"C",
|
| 2398 |
-
"D"
|
| 2399 |
-
],
|
| 2400 |
-
"description": "以下是中国关于注册城乡规划师的单项选择题，请选出其中的正确答案。\n\n",
|
| 2401 |
-
"target_delimiter": " ",
|
| 2402 |
-
"fewshot_delimiter": "\n\n",
|
| 2403 |
-
"fewshot_config": {
|
| 2404 |
-
"sampler": "first_n"
|
| 2405 |
-
},
|
| 2406 |
-
"metric_list": [
|
| 2407 |
-
{
|
| 2408 |
-
"metric": "acc",
|
| 2409 |
-
"aggregation": "mean",
|
| 2410 |
-
"higher_is_better": true
|
| 2411 |
-
},
|
| 2412 |
-
{
|
| 2413 |
-
"metric": "acc_norm",
|
| 2414 |
-
"aggregation": "mean",
|
| 2415 |
-
"higher_is_better": true
|
| 2416 |
-
}
|
| 2417 |
-
],
|
| 2418 |
-
"output_type": "multiple_choice",
|
| 2419 |
-
"repeats": 1,
|
| 2420 |
-
"should_decontaminate": false,
|
| 2421 |
-
"metadata": {
|
| 2422 |
-
"version": 1.0
|
| 2423 |
-
}
|
| 2424 |
-
},
|
| 2425 |
-
"ceval-valid_veterinary_medicine": {
|
| 2426 |
-
"task": "ceval-valid_veterinary_medicine",
|
| 2427 |
-
"group": "ceval-valid",
|
| 2428 |
-
"dataset_path": "ceval/ceval-exam",
|
| 2429 |
-
"dataset_name": "veterinary_medicine",
|
| 2430 |
-
"validation_split": "val",
|
| 2431 |
-
"fewshot_split": "dev",
|
| 2432 |
-
"doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案：",
|
| 2433 |
-
"doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
|
| 2434 |
-
"doc_to_choice": [
|
| 2435 |
-
"A",
|
| 2436 |
-
"B",
|
| 2437 |
-
"C",
|
| 2438 |
-
"D"
|
| 2439 |
-
],
|
| 2440 |
-
"description": "以下是中国关于兽医学的单项选择题，请选出其中的正确答案。\n\n",
|
| 2441 |
-
"target_delimiter": " ",
|
| 2442 |
-
"fewshot_delimiter": "\n\n",
|
| 2443 |
-
"fewshot_config": {
|
| 2444 |
-
"sampler": "first_n"
|
| 2445 |
-
},
|
| 2446 |
-
"metric_list": [
|
| 2447 |
-
{
|
| 2448 |
-
"metric": "acc",
|
| 2449 |
-
"aggregation": "mean",
|
| 2450 |
-
"higher_is_better": true
|
| 2451 |
-
},
|
| 2452 |
-
{
|
| 2453 |
-
"metric": "acc_norm",
|
| 2454 |
-
"aggregation": "mean",
|
| 2455 |
-
"higher_is_better": true
|
| 2456 |
-
}
|
| 2457 |
-
],
|
| 2458 |
-
"output_type": "multiple_choice",
|
| 2459 |
-
"repeats": 1,
|
| 2460 |
-
"should_decontaminate": false,
|
| 2461 |
-
"metadata": {
|
| 2462 |
-
"version": 1.0
|
| 2463 |
-
}
|
| 2464 |
-
}
|
| 2465 |
-
},
|
| 2466 |
-
"versions": {
|
| 2467 |
-
"ceval-valid": "N/A",
|
| 2468 |
-
"ceval-valid_accountant": 1.0,
|
| 2469 |
-
"ceval-valid_advanced_mathematics": 1.0,
|
| 2470 |
-
"ceval-valid_art_studies": 1.0,
|
| 2471 |
-
"ceval-valid_basic_medicine": 1.0,
|
| 2472 |
-
"ceval-valid_business_administration": 1.0,
|
| 2473 |
-
"ceval-valid_chinese_language_and_literature": 1.0,
|
| 2474 |
-
"ceval-valid_civil_servant": 1.0,
|
| 2475 |
-
"ceval-valid_clinical_medicine": 1.0,
|
| 2476 |
-
"ceval-valid_college_chemistry": 1.0,
|
| 2477 |
-
"ceval-valid_college_economics": 1.0,
|
| 2478 |
-
"ceval-valid_college_physics": 1.0,
|
| 2479 |
-
"ceval-valid_college_programming": 1.0,
|
| 2480 |
-
"ceval-valid_computer_architecture": 1.0,
|
| 2481 |
-
"ceval-valid_computer_network": 1.0,
|
| 2482 |
-
"ceval-valid_discrete_mathematics": 1.0,
|
| 2483 |
-
"ceval-valid_education_science": 1.0,
|
| 2484 |
-
"ceval-valid_electrical_engineer": 1.0,
|
| 2485 |
-
"ceval-valid_environmental_impact_assessment_engineer": 1.0,
|
| 2486 |
-
"ceval-valid_fire_engineer": 1.0,
|
| 2487 |
-
"ceval-valid_high_school_biology": 1.0,
|
| 2488 |
-
"ceval-valid_high_school_chemistry": 1.0,
|
| 2489 |
-
"ceval-valid_high_school_chinese": 1.0,
|
| 2490 |
-
"ceval-valid_high_school_geography": 1.0,
|
| 2491 |
-
"ceval-valid_high_school_history": 1.0,
|
| 2492 |
-
"ceval-valid_high_school_mathematics": 1.0,
|
| 2493 |
-
"ceval-valid_high_school_physics": 1.0,
|
| 2494 |
-
"ceval-valid_high_school_politics": 1.0,
|
| 2495 |
-
"ceval-valid_ideological_and_moral_cultivation": 1.0,
|
| 2496 |
-
"ceval-valid_law": 1.0,
|
| 2497 |
-
"ceval-valid_legal_professional": 1.0,
|
| 2498 |
-
"ceval-valid_logic": 1.0,
|
| 2499 |
-
"ceval-valid_mao_zedong_thought": 1.0,
|
| 2500 |
-
"ceval-valid_marxism": 1.0,
|
| 2501 |
-
"ceval-valid_metrology_engineer": 1.0,
|
| 2502 |
-
"ceval-valid_middle_school_biology": 1.0,
|
| 2503 |
-
"ceval-valid_middle_school_chemistry": 1.0,
|
| 2504 |
-
"ceval-valid_middle_school_geography": 1.0,
|
| 2505 |
-
"ceval-valid_middle_school_history": 1.0,
|
| 2506 |
-
"ceval-valid_middle_school_mathematics": 1.0,
|
| 2507 |
-
"ceval-valid_middle_school_physics": 1.0,
|
| 2508 |
-
"ceval-valid_middle_school_politics": 1.0,
|
| 2509 |
-
"ceval-valid_modern_chinese_history": 1.0,
|
| 2510 |
-
"ceval-valid_operating_system": 1.0,
|
| 2511 |
-
"ceval-valid_physician": 1.0,
|
| 2512 |
-
"ceval-valid_plant_protection": 1.0,
|
| 2513 |
-
"ceval-valid_probability_and_statistics": 1.0,
|
| 2514 |
-
"ceval-valid_professional_tour_guide": 1.0,
|
| 2515 |
-
"ceval-valid_sports_science": 1.0,
|
| 2516 |
-
"ceval-valid_tax_accountant": 1.0,
|
| 2517 |
-
"ceval-valid_teacher_qualification": 1.0,
|
| 2518 |
-
"ceval-valid_urban_and_rural_planner": 1.0,
|
| 2519 |
-
"ceval-valid_veterinary_medicine": 1.0
|
| 2520 |
-
},
|
| 2521 |
-
"n-shot": {
|
| 2522 |
-
"ceval-valid": 0,
|
| 2523 |
-
"ceval-valid_accountant": 0,
|
| 2524 |
-
"ceval-valid_advanced_mathematics": 0,
|
| 2525 |
-
"ceval-valid_art_studies": 0,
|
| 2526 |
-
"ceval-valid_basic_medicine": 0,
|
| 2527 |
-
"ceval-valid_business_administration": 0,
|
| 2528 |
-
"ceval-valid_chinese_language_and_literature": 0,
|
| 2529 |
-
"ceval-valid_civil_servant": 0,
|
| 2530 |
-
"ceval-valid_clinical_medicine": 0,
|
| 2531 |
-
"ceval-valid_college_chemistry": 0,
|
| 2532 |
-
"ceval-valid_college_economics": 0,
|
| 2533 |
-
"ceval-valid_college_physics": 0,
|
| 2534 |
-
"ceval-valid_college_programming": 0,
|
| 2535 |
-
"ceval-valid_computer_architecture": 0,
|
| 2536 |
-
"ceval-valid_computer_network": 0,
|
| 2537 |
-
"ceval-valid_discrete_mathematics": 0,
|
| 2538 |
-
"ceval-valid_education_science": 0,
|
| 2539 |
-
"ceval-valid_electrical_engineer": 0,
|
| 2540 |
-
"ceval-valid_environmental_impact_assessment_engineer": 0,
|
| 2541 |
-
"ceval-valid_fire_engineer": 0,
|
| 2542 |
-
"ceval-valid_high_school_biology": 0,
|
| 2543 |
-
"ceval-valid_high_school_chemistry": 0,
|
| 2544 |
-
"ceval-valid_high_school_chinese": 0,
|
| 2545 |
-
"ceval-valid_high_school_geography": 0,
|
| 2546 |
-
"ceval-valid_high_school_history": 0,
|
| 2547 |
-
"ceval-valid_high_school_mathematics": 0,
|
| 2548 |
-
"ceval-valid_high_school_physics": 0,
|
| 2549 |
-
"ceval-valid_high_school_politics": 0,
|
| 2550 |
-
"ceval-valid_ideological_and_moral_cultivation": 0,
|
| 2551 |
-
"ceval-valid_law": 0,
|
| 2552 |
-
"ceval-valid_legal_professional": 0,
|
| 2553 |
-
"ceval-valid_logic": 0,
|
| 2554 |
-
"ceval-valid_mao_zedong_thought": 0,
|
| 2555 |
-
"ceval-valid_marxism": 0,
|
| 2556 |
-
"ceval-valid_metrology_engineer": 0,
|
| 2557 |
-
"ceval-valid_middle_school_biology": 0,
|
| 2558 |
-
"ceval-valid_middle_school_chemistry": 0,
|
| 2559 |
-
"ceval-valid_middle_school_geography": 0,
|
| 2560 |
-
"ceval-valid_middle_school_history": 0,
|
| 2561 |
-
"ceval-valid_middle_school_mathematics": 0,
|
| 2562 |
-
"ceval-valid_middle_school_physics": 0,
|
| 2563 |
-
"ceval-valid_middle_school_politics": 0,
|
| 2564 |
-
"ceval-valid_modern_chinese_history": 0,
|
| 2565 |
-
"ceval-valid_operating_system": 0,
|
| 2566 |
-
"ceval-valid_physician": 0,
|
| 2567 |
-
"ceval-valid_plant_protection": 0,
|
| 2568 |
-
"ceval-valid_probability_and_statistics": 0,
|
| 2569 |
-
"ceval-valid_professional_tour_guide": 0,
|
| 2570 |
-
"ceval-valid_sports_science": 0,
|
| 2571 |
-
"ceval-valid_tax_accountant": 0,
|
| 2572 |
-
"ceval-valid_teacher_qualification": 0,
|
| 2573 |
-
"ceval-valid_urban_and_rural_planner": 0,
|
| 2574 |
-
"ceval-valid_veterinary_medicine": 0
|
| 2575 |
-
},
|
| 2576 |
-
"config": {
|
| 2577 |
-
"model": "hf",
|
| 2578 |
-
"model_args": "pretrained=allenai/OLMo-7B,dtype=bfloat16,trust_remote_code=True",
|
| 2579 |
-
"batch_size": "2",
|
| 2580 |
-
"batch_sizes": [],
|
| 2581 |
-
"device": null,
|
| 2582 |
-
"use_cache": null,
|
| 2583 |
-
"limit": null,
|
| 2584 |
-
"bootstrap_iters": 100000,
|
| 2585 |
-
"gen_kwargs": null
|
| 2586 |
-
},
|
| 2587 |
-
"git_hash": "4701655"
|
| 2588 |
-
}
|
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|
lm-eval-output/allenai/OLMo-7B/ceval-valid/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f000647be6eea5529f603c75503e3332301c0bd4aa7f76edcbbb38001ab4cc9c
|
| 3 |
+
size 79965
|
lm-eval-output/allenai/OLMo-7B/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
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| 3 |
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size 2305507
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lm-eval-output/allenai/OLMo-7B/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
CHANGED
|
@@ -1,38 +1,38 @@
|
|
| 1 |
{
|
| 2 |
"results": {
|
| 3 |
"cmmlu": {
|
| 4 |
-
"acc,none": 0.
|
| 5 |
-
"acc_stderr,none": 0.
|
| 6 |
-
"acc_norm,none": 0.
|
| 7 |
-
"acc_norm_stderr,none": 0.
|
| 8 |
"alias": "cmmlu"
|
| 9 |
},
|
| 10 |
"cmmlu_agronomy": {
|
| 11 |
-
"acc,none": 0.
|
| 12 |
-
"acc_stderr,none": 0.
|
| 13 |
-
"acc_norm,none": 0.
|
| 14 |
-
"acc_norm_stderr,none": 0.
|
| 15 |
"alias": " - cmmlu_agronomy"
|
| 16 |
},
|
| 17 |
"cmmlu_anatomy": {
|
| 18 |
-
"acc,none": 0.
|
| 19 |
-
"acc_stderr,none": 0.
|
| 20 |
-
"acc_norm,none": 0.
|
| 21 |
-
"acc_norm_stderr,none": 0.
|
| 22 |
"alias": " - cmmlu_anatomy"
|
| 23 |
},
|
| 24 |
"cmmlu_ancient_chinese": {
|
| 25 |
-
"acc,none": 0.
|
| 26 |
-
"acc_stderr,none": 0.
|
| 27 |
-
"acc_norm,none": 0.
|
| 28 |
-
"acc_norm_stderr,none": 0.
|
| 29 |
"alias": " - cmmlu_ancient_chinese"
|
| 30 |
},
|
| 31 |
"cmmlu_arts": {
|
| 32 |
-
"acc,none": 0.
|
| 33 |
-
"acc_stderr,none": 0.
|
| 34 |
-
"acc_norm,none": 0.
|
| 35 |
-
"acc_norm_stderr,none": 0.
|
| 36 |
"alias": " - cmmlu_arts"
|
| 37 |
},
|
| 38 |
"cmmlu_astronomy": {
|
|
@@ -43,122 +43,122 @@
|
|
| 43 |
"alias": " - cmmlu_astronomy"
|
| 44 |
},
|
| 45 |
"cmmlu_business_ethics": {
|
| 46 |
-
"acc,none": 0.
|
| 47 |
-
"acc_stderr,none": 0.
|
| 48 |
-
"acc_norm,none": 0.
|
| 49 |
-
"acc_norm_stderr,none": 0.
|
| 50 |
"alias": " - cmmlu_business_ethics"
|
| 51 |
},
|
| 52 |
"cmmlu_chinese_civil_service_exam": {
|
| 53 |
-
"acc,none": 0.
|
| 54 |
-
"acc_stderr,none": 0.
|
| 55 |
-
"acc_norm,none": 0.
|
| 56 |
-
"acc_norm_stderr,none": 0.
|
| 57 |
"alias": " - cmmlu_chinese_civil_service_exam"
|
| 58 |
},
|
| 59 |
"cmmlu_chinese_driving_rule": {
|
| 60 |
-
"acc,none": 0.
|
| 61 |
-
"acc_stderr,none": 0.
|
| 62 |
-
"acc_norm,none": 0.
|
| 63 |
-
"acc_norm_stderr,none": 0.
|
| 64 |
"alias": " - cmmlu_chinese_driving_rule"
|
| 65 |
},
|
| 66 |
"cmmlu_chinese_food_culture": {
|
| 67 |
-
"acc,none": 0.
|
| 68 |
-
"acc_stderr,none": 0.
|
| 69 |
-
"acc_norm,none": 0.
|
| 70 |
-
"acc_norm_stderr,none": 0.
|
| 71 |
"alias": " - cmmlu_chinese_food_culture"
|
| 72 |
},
|
| 73 |
"cmmlu_chinese_foreign_policy": {
|
| 74 |
-
"acc,none": 0.
|
| 75 |
-
"acc_stderr,none": 0.
|
| 76 |
-
"acc_norm,none": 0.
|
| 77 |
-
"acc_norm_stderr,none": 0.
|
| 78 |
"alias": " - cmmlu_chinese_foreign_policy"
|
| 79 |
},
|
| 80 |
"cmmlu_chinese_history": {
|
| 81 |
-
"acc,none": 0.
|
| 82 |
-
"acc_stderr,none": 0.
|
| 83 |
-
"acc_norm,none": 0.
|
| 84 |
-
"acc_norm_stderr,none": 0.
|
| 85 |
"alias": " - cmmlu_chinese_history"
|
| 86 |
},
|
| 87 |
"cmmlu_chinese_literature": {
|
| 88 |
-
"acc,none": 0.
|
| 89 |
-
"acc_stderr,none": 0.
|
| 90 |
-
"acc_norm,none": 0.
|
| 91 |
-
"acc_norm_stderr,none": 0.
|
| 92 |
"alias": " - cmmlu_chinese_literature"
|
| 93 |
},
|
| 94 |
"cmmlu_chinese_teacher_qualification": {
|
| 95 |
-
"acc,none": 0.
|
| 96 |
-
"acc_stderr,none": 0.
|
| 97 |
-
"acc_norm,none": 0.
|
| 98 |
-
"acc_norm_stderr,none": 0.
|
| 99 |
"alias": " - cmmlu_chinese_teacher_qualification"
|
| 100 |
},
|
| 101 |
"cmmlu_clinical_knowledge": {
|
| 102 |
-
"acc,none": 0.
|
| 103 |
-
"acc_stderr,none": 0.
|
| 104 |
-
"acc_norm,none": 0.
|
| 105 |
-
"acc_norm_stderr,none": 0.
|
| 106 |
"alias": " - cmmlu_clinical_knowledge"
|
| 107 |
},
|
| 108 |
"cmmlu_college_actuarial_science": {
|
| 109 |
-
"acc,none": 0.
|
| 110 |
-
"acc_stderr,none": 0.
|
| 111 |
-
"acc_norm,none": 0.
|
| 112 |
-
"acc_norm_stderr,none": 0.
|
| 113 |
"alias": " - cmmlu_college_actuarial_science"
|
| 114 |
},
|
| 115 |
"cmmlu_college_education": {
|
| 116 |
-
"acc,none": 0.
|
| 117 |
-
"acc_stderr,none": 0.
|
| 118 |
-
"acc_norm,none": 0.
|
| 119 |
-
"acc_norm_stderr,none": 0.
|
| 120 |
"alias": " - cmmlu_college_education"
|
| 121 |
},
|
| 122 |
"cmmlu_college_engineering_hydrology": {
|
| 123 |
-
"acc,none": 0.
|
| 124 |
-
"acc_stderr,none": 0.
|
| 125 |
-
"acc_norm,none": 0.
|
| 126 |
-
"acc_norm_stderr,none": 0.
|
| 127 |
"alias": " - cmmlu_college_engineering_hydrology"
|
| 128 |
},
|
| 129 |
"cmmlu_college_law": {
|
| 130 |
-
"acc,none": 0.
|
| 131 |
-
"acc_stderr,none": 0.
|
| 132 |
-
"acc_norm,none": 0.
|
| 133 |
-
"acc_norm_stderr,none": 0.
|
| 134 |
"alias": " - cmmlu_college_law"
|
| 135 |
},
|
| 136 |
"cmmlu_college_mathematics": {
|
| 137 |
-
"acc,none": 0.
|
| 138 |
-
"acc_stderr,none": 0.
|
| 139 |
-
"acc_norm,none": 0.
|
| 140 |
-
"acc_norm_stderr,none": 0.
|
| 141 |
"alias": " - cmmlu_college_mathematics"
|
| 142 |
},
|
| 143 |
"cmmlu_college_medical_statistics": {
|
| 144 |
-
"acc,none": 0.
|
| 145 |
-
"acc_stderr,none": 0.
|
| 146 |
-
"acc_norm,none": 0.
|
| 147 |
-
"acc_norm_stderr,none": 0.
|
| 148 |
"alias": " - cmmlu_college_medical_statistics"
|
| 149 |
},
|
| 150 |
"cmmlu_college_medicine": {
|
| 151 |
-
"acc,none": 0.
|
| 152 |
-
"acc_stderr,none": 0.
|
| 153 |
-
"acc_norm,none": 0.
|
| 154 |
-
"acc_norm_stderr,none": 0.
|
| 155 |
"alias": " - cmmlu_college_medicine"
|
| 156 |
},
|
| 157 |
"cmmlu_computer_science": {
|
| 158 |
-
"acc,none": 0.
|
| 159 |
-
"acc_stderr,none": 0.
|
| 160 |
-
"acc_norm,none": 0.
|
| 161 |
-
"acc_norm_stderr,none": 0.
|
| 162 |
"alias": " - cmmlu_computer_science"
|
| 163 |
},
|
| 164 |
"cmmlu_computer_security": {
|
|
@@ -169,45 +169,45 @@
|
|
| 169 |
"alias": " - cmmlu_computer_security"
|
| 170 |
},
|
| 171 |
"cmmlu_conceptual_physics": {
|
| 172 |
-
"acc,none": 0.
|
| 173 |
-
"acc_stderr,none": 0.
|
| 174 |
-
"acc_norm,none": 0.
|
| 175 |
-
"acc_norm_stderr,none": 0.
|
| 176 |
"alias": " - cmmlu_conceptual_physics"
|
| 177 |
},
|
| 178 |
"cmmlu_construction_project_management": {
|
| 179 |
-
"acc,none": 0.
|
| 180 |
-
"acc_stderr,none": 0.
|
| 181 |
-
"acc_norm,none": 0.
|
| 182 |
-
"acc_norm_stderr,none": 0.
|
| 183 |
"alias": " - cmmlu_construction_project_management"
|
| 184 |
},
|
| 185 |
"cmmlu_economics": {
|
| 186 |
-
"acc,none": 0.
|
| 187 |
-
"acc_stderr,none": 0.
|
| 188 |
-
"acc_norm,none": 0.
|
| 189 |
-
"acc_norm_stderr,none": 0.
|
| 190 |
"alias": " - cmmlu_economics"
|
| 191 |
},
|
| 192 |
"cmmlu_education": {
|
| 193 |
-
"acc,none": 0.
|
| 194 |
-
"acc_stderr,none": 0.
|
| 195 |
-
"acc_norm,none": 0.
|
| 196 |
-
"acc_norm_stderr,none": 0.
|
| 197 |
"alias": " - cmmlu_education"
|
| 198 |
},
|
| 199 |
"cmmlu_electrical_engineering": {
|
| 200 |
-
"acc,none": 0.
|
| 201 |
-
"acc_stderr,none": 0.
|
| 202 |
-
"acc_norm,none": 0.
|
| 203 |
-
"acc_norm_stderr,none": 0.
|
| 204 |
"alias": " - cmmlu_electrical_engineering"
|
| 205 |
},
|
| 206 |
"cmmlu_elementary_chinese": {
|
| 207 |
-
"acc,none": 0.
|
| 208 |
-
"acc_stderr,none": 0.
|
| 209 |
-
"acc_norm,none": 0.
|
| 210 |
-
"acc_norm_stderr,none": 0.
|
| 211 |
"alias": " - cmmlu_elementary_chinese"
|
| 212 |
},
|
| 213 |
"cmmlu_elementary_commonsense": {
|
|
@@ -218,10 +218,10 @@
|
|
| 218 |
"alias": " - cmmlu_elementary_commonsense"
|
| 219 |
},
|
| 220 |
"cmmlu_elementary_information_and_technology": {
|
| 221 |
-
"acc,none": 0.
|
| 222 |
-
"acc_stderr,none": 0.
|
| 223 |
-
"acc_norm,none": 0.
|
| 224 |
-
"acc_norm_stderr,none": 0.
|
| 225 |
"alias": " - cmmlu_elementary_information_and_technology"
|
| 226 |
},
|
| 227 |
"cmmlu_elementary_mathematics": {
|
|
@@ -232,66 +232,66 @@
|
|
| 232 |
"alias": " - cmmlu_elementary_mathematics"
|
| 233 |
},
|
| 234 |
"cmmlu_ethnology": {
|
| 235 |
-
"acc,none": 0.
|
| 236 |
-
"acc_stderr,none": 0.
|
| 237 |
-
"acc_norm,none": 0.
|
| 238 |
-
"acc_norm_stderr,none": 0.
|
| 239 |
"alias": " - cmmlu_ethnology"
|
| 240 |
},
|
| 241 |
"cmmlu_food_science": {
|
| 242 |
-
"acc,none": 0.
|
| 243 |
-
"acc_stderr,none": 0.
|
| 244 |
-
"acc_norm,none": 0.
|
| 245 |
-
"acc_norm_stderr,none": 0.
|
| 246 |
"alias": " - cmmlu_food_science"
|
| 247 |
},
|
| 248 |
"cmmlu_genetics": {
|
| 249 |
-
"acc,none": 0.
|
| 250 |
-
"acc_stderr,none": 0.
|
| 251 |
-
"acc_norm,none": 0.
|
| 252 |
-
"acc_norm_stderr,none": 0.
|
| 253 |
"alias": " - cmmlu_genetics"
|
| 254 |
},
|
| 255 |
"cmmlu_global_facts": {
|
| 256 |
-
"acc,none": 0.
|
| 257 |
-
"acc_stderr,none": 0.
|
| 258 |
-
"acc_norm,none": 0.
|
| 259 |
-
"acc_norm_stderr,none": 0.
|
| 260 |
"alias": " - cmmlu_global_facts"
|
| 261 |
},
|
| 262 |
"cmmlu_high_school_biology": {
|
| 263 |
-
"acc,none": 0.
|
| 264 |
-
"acc_stderr,none": 0.
|
| 265 |
-
"acc_norm,none": 0.
|
| 266 |
-
"acc_norm_stderr,none": 0.
|
| 267 |
"alias": " - cmmlu_high_school_biology"
|
| 268 |
},
|
| 269 |
"cmmlu_high_school_chemistry": {
|
| 270 |
-
"acc,none": 0.
|
| 271 |
-
"acc_stderr,none": 0.
|
| 272 |
-
"acc_norm,none": 0.
|
| 273 |
-
"acc_norm_stderr,none": 0.
|
| 274 |
"alias": " - cmmlu_high_school_chemistry"
|
| 275 |
},
|
| 276 |
"cmmlu_high_school_geography": {
|
| 277 |
-
"acc,none": 0.
|
| 278 |
-
"acc_stderr,none": 0.
|
| 279 |
-
"acc_norm,none": 0.
|
| 280 |
-
"acc_norm_stderr,none": 0.
|
| 281 |
"alias": " - cmmlu_high_school_geography"
|
| 282 |
},
|
| 283 |
"cmmlu_high_school_mathematics": {
|
| 284 |
-
"acc,none": 0.
|
| 285 |
-
"acc_stderr,none": 0.
|
| 286 |
-
"acc_norm,none": 0.
|
| 287 |
-
"acc_norm_stderr,none": 0.
|
| 288 |
"alias": " - cmmlu_high_school_mathematics"
|
| 289 |
},
|
| 290 |
"cmmlu_high_school_physics": {
|
| 291 |
-
"acc,none": 0.
|
| 292 |
-
"acc_stderr,none": 0.
|
| 293 |
-
"acc_norm,none": 0.
|
| 294 |
-
"acc_norm_stderr,none": 0.
|
| 295 |
"alias": " - cmmlu_high_school_physics"
|
| 296 |
},
|
| 297 |
"cmmlu_high_school_politics": {
|
|
@@ -302,129 +302,129 @@
|
|
| 302 |
"alias": " - cmmlu_high_school_politics"
|
| 303 |
},
|
| 304 |
"cmmlu_human_sexuality": {
|
| 305 |
-
"acc,none": 0.
|
| 306 |
-
"acc_stderr,none": 0.
|
| 307 |
-
"acc_norm,none": 0.
|
| 308 |
-
"acc_norm_stderr,none": 0.
|
| 309 |
"alias": " - cmmlu_human_sexuality"
|
| 310 |
},
|
| 311 |
"cmmlu_international_law": {
|
| 312 |
-
"acc,none": 0.
|
| 313 |
-
"acc_stderr,none": 0.
|
| 314 |
-
"acc_norm,none": 0.
|
| 315 |
-
"acc_norm_stderr,none": 0.
|
| 316 |
"alias": " - cmmlu_international_law"
|
| 317 |
},
|
| 318 |
"cmmlu_journalism": {
|
| 319 |
-
"acc,none": 0.
|
| 320 |
-
"acc_stderr,none": 0.
|
| 321 |
-
"acc_norm,none": 0.
|
| 322 |
-
"acc_norm_stderr,none": 0.
|
| 323 |
"alias": " - cmmlu_journalism"
|
| 324 |
},
|
| 325 |
"cmmlu_jurisprudence": {
|
| 326 |
-
"acc,none": 0.
|
| 327 |
-
"acc_stderr,none": 0.
|
| 328 |
-
"acc_norm,none": 0.
|
| 329 |
-
"acc_norm_stderr,none": 0.
|
| 330 |
"alias": " - cmmlu_jurisprudence"
|
| 331 |
},
|
| 332 |
"cmmlu_legal_and_moral_basis": {
|
| 333 |
-
"acc,none": 0.
|
| 334 |
-
"acc_stderr,none": 0.
|
| 335 |
-
"acc_norm,none": 0.
|
| 336 |
-
"acc_norm_stderr,none": 0.
|
| 337 |
"alias": " - cmmlu_legal_and_moral_basis"
|
| 338 |
},
|
| 339 |
"cmmlu_logical": {
|
| 340 |
-
"acc,none": 0.
|
| 341 |
-
"acc_stderr,none": 0.
|
| 342 |
-
"acc_norm,none": 0.
|
| 343 |
-
"acc_norm_stderr,none": 0.
|
| 344 |
"alias": " - cmmlu_logical"
|
| 345 |
},
|
| 346 |
"cmmlu_machine_learning": {
|
| 347 |
-
"acc,none": 0.
|
| 348 |
-
"acc_stderr,none": 0.
|
| 349 |
-
"acc_norm,none": 0.
|
| 350 |
-
"acc_norm_stderr,none": 0.
|
| 351 |
"alias": " - cmmlu_machine_learning"
|
| 352 |
},
|
| 353 |
"cmmlu_management": {
|
| 354 |
-
"acc,none": 0.
|
| 355 |
-
"acc_stderr,none": 0.
|
| 356 |
-
"acc_norm,none": 0.
|
| 357 |
-
"acc_norm_stderr,none": 0.
|
| 358 |
"alias": " - cmmlu_management"
|
| 359 |
},
|
| 360 |
"cmmlu_marketing": {
|
| 361 |
-
"acc,none": 0.
|
| 362 |
-
"acc_stderr,none": 0.
|
| 363 |
-
"acc_norm,none": 0.
|
| 364 |
-
"acc_norm_stderr,none": 0.
|
| 365 |
"alias": " - cmmlu_marketing"
|
| 366 |
},
|
| 367 |
"cmmlu_marxist_theory": {
|
| 368 |
-
"acc,none": 0.
|
| 369 |
-
"acc_stderr,none": 0.
|
| 370 |
-
"acc_norm,none": 0.
|
| 371 |
-
"acc_norm_stderr,none": 0.
|
| 372 |
"alias": " - cmmlu_marxist_theory"
|
| 373 |
},
|
| 374 |
"cmmlu_modern_chinese": {
|
| 375 |
-
"acc,none": 0.
|
| 376 |
-
"acc_stderr,none": 0.
|
| 377 |
-
"acc_norm,none": 0.
|
| 378 |
-
"acc_norm_stderr,none": 0.
|
| 379 |
"alias": " - cmmlu_modern_chinese"
|
| 380 |
},
|
| 381 |
"cmmlu_nutrition": {
|
| 382 |
-
"acc,none": 0.
|
| 383 |
-
"acc_stderr,none": 0.
|
| 384 |
-
"acc_norm,none": 0.
|
| 385 |
-
"acc_norm_stderr,none": 0.
|
| 386 |
"alias": " - cmmlu_nutrition"
|
| 387 |
},
|
| 388 |
"cmmlu_philosophy": {
|
| 389 |
-
"acc,none": 0.
|
| 390 |
-
"acc_stderr,none": 0.
|
| 391 |
-
"acc_norm,none": 0.
|
| 392 |
-
"acc_norm_stderr,none": 0.
|
| 393 |
"alias": " - cmmlu_philosophy"
|
| 394 |
},
|
| 395 |
"cmmlu_professional_accounting": {
|
| 396 |
-
"acc,none": 0.
|
| 397 |
-
"acc_stderr,none": 0.
|
| 398 |
-
"acc_norm,none": 0.
|
| 399 |
-
"acc_norm_stderr,none": 0.
|
| 400 |
"alias": " - cmmlu_professional_accounting"
|
| 401 |
},
|
| 402 |
"cmmlu_professional_law": {
|
| 403 |
-
"acc,none": 0.
|
| 404 |
-
"acc_stderr,none": 0.
|
| 405 |
-
"acc_norm,none": 0.
|
| 406 |
-
"acc_norm_stderr,none": 0.
|
| 407 |
"alias": " - cmmlu_professional_law"
|
| 408 |
},
|
| 409 |
"cmmlu_professional_medicine": {
|
| 410 |
-
"acc,none": 0.
|
| 411 |
-
"acc_stderr,none": 0.
|
| 412 |
-
"acc_norm,none": 0.
|
| 413 |
-
"acc_norm_stderr,none": 0.
|
| 414 |
"alias": " - cmmlu_professional_medicine"
|
| 415 |
},
|
| 416 |
"cmmlu_professional_psychology": {
|
| 417 |
-
"acc,none": 0.
|
| 418 |
-
"acc_stderr,none": 0.
|
| 419 |
-
"acc_norm,none": 0.
|
| 420 |
-
"acc_norm_stderr,none": 0.
|
| 421 |
"alias": " - cmmlu_professional_psychology"
|
| 422 |
},
|
| 423 |
"cmmlu_public_relations": {
|
| 424 |
-
"acc,none": 0.
|
| 425 |
-
"acc_stderr,none": 0.
|
| 426 |
-
"acc_norm,none": 0.
|
| 427 |
-
"acc_norm_stderr,none": 0.
|
| 428 |
"alias": " - cmmlu_public_relations"
|
| 429 |
},
|
| 430 |
"cmmlu_security_study": {
|
|
@@ -435,31 +435,31 @@
|
|
| 435 |
"alias": " - cmmlu_security_study"
|
| 436 |
},
|
| 437 |
"cmmlu_sociology": {
|
| 438 |
-
"acc,none": 0.
|
| 439 |
-
"acc_stderr,none": 0.
|
| 440 |
-
"acc_norm,none": 0.
|
| 441 |
-
"acc_norm_stderr,none": 0.
|
| 442 |
"alias": " - cmmlu_sociology"
|
| 443 |
},
|
| 444 |
"cmmlu_sports_science": {
|
| 445 |
-
"acc,none": 0.
|
| 446 |
-
"acc_stderr,none": 0.
|
| 447 |
-
"acc_norm,none": 0.
|
| 448 |
-
"acc_norm_stderr,none": 0.
|
| 449 |
"alias": " - cmmlu_sports_science"
|
| 450 |
},
|
| 451 |
"cmmlu_traditional_chinese_medicine": {
|
| 452 |
"acc,none": 0.23243243243243245,
|
| 453 |
-
"acc_stderr,none": 0.
|
| 454 |
"acc_norm,none": 0.23243243243243245,
|
| 455 |
-
"acc_norm_stderr,none": 0.
|
| 456 |
"alias": " - cmmlu_traditional_chinese_medicine"
|
| 457 |
},
|
| 458 |
"cmmlu_virology": {
|
| 459 |
-
"acc,none": 0.
|
| 460 |
-
"acc_stderr,none": 0.
|
| 461 |
-
"acc_norm,none": 0.
|
| 462 |
-
"acc_norm_stderr,none": 0.
|
| 463 |
"alias": " - cmmlu_virology"
|
| 464 |
},
|
| 465 |
"cmmlu_world_history": {
|
|
@@ -479,10 +479,10 @@
|
|
| 479 |
},
|
| 480 |
"groups": {
|
| 481 |
"cmmlu": {
|
| 482 |
-
"acc,none": 0.
|
| 483 |
-
"acc_stderr,none": 0.
|
| 484 |
-
"acc_norm,none": 0.
|
| 485 |
-
"acc_norm_stderr,none": 0.
|
| 486 |
"alias": "cmmlu"
|
| 487 |
}
|
| 488 |
},
|
|
@@ -3311,13 +3311,15 @@
|
|
| 3311 |
"config": {
|
| 3312 |
"model": "hf",
|
| 3313 |
"model_args": "pretrained=allenai/OLMo-7B,dtype=bfloat16,trust_remote_code=True",
|
| 3314 |
-
"batch_size": "
|
| 3315 |
-
"batch_sizes": [
|
|
|
|
|
|
|
| 3316 |
"device": null,
|
| 3317 |
"use_cache": null,
|
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"limit": null,
|
| 3319 |
"bootstrap_iters": 100000,
|
| 3320 |
"gen_kwargs": null
|
| 3321 |
},
|
| 3322 |
-
"git_hash": "
|
| 3323 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"results": {
|
| 3 |
"cmmlu": {
|
| 4 |
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"acc,none": 0.2485753755828009,
|
| 5 |
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"acc_stderr,none": 0.042815306797706565,
|
| 6 |
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|
| 7 |
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|
| 8 |
"alias": "cmmlu"
|
| 9 |
},
|
| 10 |
"cmmlu_agronomy": {
|
| 11 |
+
"acc,none": 0.1952662721893491,
|
| 12 |
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"acc_stderr,none": 0.030583351673923103,
|
| 13 |
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|
| 14 |
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"acc_norm_stderr,none": 0.030583351673923103,
|
| 15 |
"alias": " - cmmlu_agronomy"
|
| 16 |
},
|
| 17 |
"cmmlu_anatomy": {
|
| 18 |
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"acc,none": 0.22297297297297297,
|
| 19 |
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|
| 20 |
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|
| 21 |
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"acc_norm_stderr,none": 0.03433092518104002,
|
| 22 |
"alias": " - cmmlu_anatomy"
|
| 23 |
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|
| 24 |
"cmmlu_ancient_chinese": {
|
| 25 |
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"acc,none": 0.24390243902439024,
|
| 26 |
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"acc_stderr,none": 0.033635910482728223,
|
| 27 |
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"acc_norm,none": 0.24390243902439024,
|
| 28 |
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"acc_norm_stderr,none": 0.033635910482728223,
|
| 29 |
"alias": " - cmmlu_ancient_chinese"
|
| 30 |
},
|
| 31 |
"cmmlu_arts": {
|
| 32 |
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"acc,none": 0.29375,
|
| 33 |
+
"acc_stderr,none": 0.03612181848191273,
|
| 34 |
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"acc_norm,none": 0.29375,
|
| 35 |
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"acc_norm_stderr,none": 0.03612181848191273,
|
| 36 |
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|
| 37 |
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|
| 38 |
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|
|
|
|
| 43 |
"alias": " - cmmlu_astronomy"
|
| 44 |
},
|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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"acc,none": 0.21875,
|
| 54 |
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|
| 55 |
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|
| 56 |
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"acc_norm_stderr,none": 0.032784644885244255,
|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
"alias": " - cmmlu_chinese_food_culture"
|
| 72 |
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|
| 73 |
"cmmlu_chinese_foreign_policy": {
|
| 74 |
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|
| 75 |
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| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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| 90 |
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| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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| 97 |
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| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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| 104 |
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| 105 |
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| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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| 111 |
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| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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| 117 |
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| 118 |
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| 119 |
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| 120 |
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|
| 121 |
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| 122 |
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|
| 123 |
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| 124 |
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| 125 |
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| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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| 131 |
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| 132 |
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| 133 |
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|
| 134 |
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|
| 135 |
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|
| 136 |
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|
| 137 |
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| 138 |
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| 139 |
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| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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| 145 |
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| 146 |
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| 147 |
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|
| 148 |
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|
| 149 |
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|
| 150 |
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|
| 151 |
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| 152 |
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| 153 |
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| 154 |
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| 155 |
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|
| 156 |
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|
| 157 |
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|
| 158 |
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| 163 |
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|
|
| 169 |
"alias": " - cmmlu_computer_security"
|
| 170 |
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| 177 |
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| 184 |
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| 198 |
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| 205 |
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| 207 |
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| 211 |
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|
| 212 |
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|
| 213 |
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|
|
|
| 218 |
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|
| 219 |
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| 220 |
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| 225 |
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| 226 |
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| 227 |
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|
|
| 232 |
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| 233 |
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| 234 |
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| 254 |
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