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dpo-160m-eval-files/dpo-pythia-160m-0shot-shelloutput.txt
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1 |
+
bootstrapping for stddev: perplexity
|
2 |
+
{
|
3 |
+
"results": {
|
4 |
+
"arc_challenge": {
|
5 |
+
"acc,none": 0.19283276450511946,
|
6 |
+
"acc_stderr,none": 0.01152905546566333,
|
7 |
+
"acc_norm,none": 0.24488054607508533,
|
8 |
+
"acc_norm_stderr,none": 0.012566273985131358
|
9 |
+
},
|
10 |
+
"arc_easy": {
|
11 |
+
"acc,none": 0.4671717171717172,
|
12 |
+
"acc_stderr,none": 0.010237645778853858,
|
13 |
+
"acc_norm,none": 0.4132996632996633,
|
14 |
+
"acc_norm_stderr,none": 0.010104361780747516
|
15 |
+
},
|
16 |
+
"boolq": {
|
17 |
+
"acc,none": 0.6149847094801223,
|
18 |
+
"acc_stderr,none": 0.00851066875102728
|
19 |
+
},
|
20 |
+
"hellaswag": {
|
21 |
+
"acc,none": 0.28958374825731925,
|
22 |
+
"acc_stderr,none": 0.004526422125860652,
|
23 |
+
"acc_norm,none": 0.3016331408086039,
|
24 |
+
"acc_norm_stderr,none": 0.004580288728196038
|
25 |
+
},
|
26 |
+
"lambada_openai": {
|
27 |
+
"perplexity,none": 40.49750927655119,
|
28 |
+
"perplexity_stderr,none": 1.9470980651595484,
|
29 |
+
"acc,none": 0.35066951290510384,
|
30 |
+
"acc_stderr,none": 0.006648045374603881
|
31 |
+
},
|
32 |
+
"openbookqa": {
|
33 |
+
"acc,none": 0.172,
|
34 |
+
"acc_stderr,none": 0.01689386887634748,
|
35 |
+
"acc_norm,none": 0.28,
|
36 |
+
"acc_norm_stderr,none": 0.020099950647503237
|
37 |
+
},
|
38 |
+
"piqa": {
|
39 |
+
"acc,none": 0.6332970620239391,
|
40 |
+
"acc_stderr,none": 0.011243625019038255,
|
41 |
+
"acc_norm,none": 0.6262241566920566,
|
42 |
+
"acc_norm_stderr,none": 0.011287972563201014
|
43 |
+
},
|
44 |
+
"sciq": {
|
45 |
+
"acc,none": 0.753,
|
46 |
+
"acc_stderr,none": 0.013644675781314128,
|
47 |
+
"acc_norm,none": 0.67,
|
48 |
+
"acc_norm_stderr,none": 0.014876872027456732
|
49 |
+
},
|
50 |
+
"wikitext": {
|
51 |
+
"word_perplexity,none": 75.24993841350984,
|
52 |
+
"byte_perplexity,none": 2.0386909133746456,
|
53 |
+
"bits_per_byte,none": 1.0276430644458452
|
54 |
+
},
|
55 |
+
"winogrande": {
|
56 |
+
"acc,none": 0.5138121546961326,
|
57 |
+
"acc_stderr,none": 0.014047122916440419
|
58 |
+
}
|
59 |
+
},
|
60 |
+
"configs": {
|
61 |
+
"arc_challenge": {
|
62 |
+
"task": "arc_challenge",
|
63 |
+
"group": [
|
64 |
+
"ai2_arc",
|
65 |
+
"multiple_choice"
|
66 |
+
],
|
67 |
+
"dataset_path": "ai2_arc",
|
68 |
+
"dataset_name": "ARC-Challenge",
|
69 |
+
"training_split": "train",
|
70 |
+
"validation_split": "validation",
|
71 |
+
"test_split": "test",
|
72 |
+
"doc_to_text": "Question: {{question}}\nAnswer:",
|
73 |
+
"doc_to_target": "{{choices.label.index(answerKey)}}",
|
74 |
+
"doc_to_choice": "{{choices.text}}",
|
75 |
+
"description": "",
|
76 |
+
"target_delimiter": " ",
|
77 |
+
"fewshot_delimiter": "\n\n",
|
78 |
+
"num_fewshot": 0,
|
79 |
+
"metric_list": [
|
80 |
+
{
|
81 |
+
"metric": "acc",
|
82 |
+
"aggregation": "mean",
|
83 |
+
"higher_is_better": true
|
84 |
+
},
|
85 |
+
{
|
86 |
+
"metric": "acc_norm",
|
87 |
+
"aggregation": "mean",
|
88 |
+
"higher_is_better": true
|
89 |
+
}
|
90 |
+
],
|
91 |
+
"output_type": "multiple_choice",
|
92 |
+
"repeats": 1,
|
93 |
+
"should_decontaminate": true,
|
94 |
+
"doc_to_decontamination_query": "Question: {{question}}\nAnswer:"
|
95 |
+
},
|
96 |
+
"arc_easy": {
|
97 |
+
"task": "arc_easy",
|
98 |
+
"group": [
|
99 |
+
"ai2_arc",
|
100 |
+
"multiple_choice"
|
101 |
+
],
|
102 |
+
"dataset_path": "ai2_arc",
|
103 |
+
"dataset_name": "ARC-Easy",
|
104 |
+
"training_split": "train",
|
105 |
+
"validation_split": "validation",
|
106 |
+
"test_split": "test",
|
107 |
+
"doc_to_text": "Question: {{question}}\nAnswer:",
|
108 |
+
"doc_to_target": "{{choices.label.index(answerKey)}}",
|
109 |
+
"doc_to_choice": "{{choices.text}}",
|
110 |
+
"description": "",
|
111 |
+
"target_delimiter": " ",
|
112 |
+
"fewshot_delimiter": "\n\n",
|
113 |
+
"num_fewshot": 0,
|
114 |
+
"metric_list": [
|
115 |
+
{
|
116 |
+
"metric": "acc",
|
117 |
+
"aggregation": "mean",
|
118 |
+
"higher_is_better": true
|
119 |
+
},
|
120 |
+
{
|
121 |
+
"metric": "acc_norm",
|
122 |
+
"aggregation": "mean",
|
123 |
+
"higher_is_better": true
|
124 |
+
}
|
125 |
+
],
|
126 |
+
"output_type": "multiple_choice",
|
127 |
+
"repeats": 1,
|
128 |
+
"should_decontaminate": true,
|
129 |
+
"doc_to_decontamination_query": "Question: {{question}}\nAnswer:"
|
130 |
+
},
|
131 |
+
"boolq": {
|
132 |
+
"task": "boolq",
|
133 |
+
"group": [
|
134 |
+
"super-glue-lm-eval-v1"
|
135 |
+
],
|
136 |
+
"dataset_path": "super_glue",
|
137 |
+
"dataset_name": "boolq",
|
138 |
+
"training_split": "train",
|
139 |
+
"validation_split": "validation",
|
140 |
+
"doc_to_text": "{{passage}}\nQuestion: {{question}}?\nAnswer:",
|
141 |
+
"doc_to_target": "label",
|
142 |
+
"doc_to_choice": [
|
143 |
+
"no",
|
144 |
+
"yes"
|
145 |
+
],
|
146 |
+
"description": "",
|
147 |
+
"target_delimiter": " ",
|
148 |
+
"fewshot_delimiter": "\n\n",
|
149 |
+
"num_fewshot": 0,
|
150 |
+
"metric_list": [
|
151 |
+
{
|
152 |
+
"metric": "acc"
|
153 |
+
}
|
154 |
+
],
|
155 |
+
"output_type": "multiple_choice",
|
156 |
+
"repeats": 1,
|
157 |
+
"should_decontaminate": true,
|
158 |
+
"doc_to_decontamination_query": "passage"
|
159 |
+
},
|
160 |
+
"hellaswag": {
|
161 |
+
"task": "hellaswag",
|
162 |
+
"group": [
|
163 |
+
"multiple_choice"
|
164 |
+
],
|
165 |
+
"dataset_path": "hellaswag",
|
166 |
+
"training_split": "train",
|
167 |
+
"validation_split": "validation",
|
168 |
+
"doc_to_text": "{% set text = activity_label ~ ': ' ~ ctx_a ~ ' ' ~ ctx_b.capitalize() %}{{text|trim|replace(' [title]', '. ')|regex_replace('\\[.*?\\]', '')|replace(' ', ' ')}}",
|
169 |
+
"doc_to_target": "{{label}}",
|
170 |
+
"doc_to_choice": "{{endings|map('trim')|map('replace', ' [title]', '. ')|map('regex_replace', '\\[.*?\\]', '')|map('replace', ' ', ' ')|list}}",
|
171 |
+
"description": "",
|
172 |
+
"target_delimiter": " ",
|
173 |
+
"fewshot_delimiter": "\n\n",
|
174 |
+
"num_fewshot": 0,
|
175 |
+
"metric_list": [
|
176 |
+
{
|
177 |
+
"metric": "acc",
|
178 |
+
"aggregation": "mean",
|
179 |
+
"higher_is_better": true
|
180 |
+
},
|
181 |
+
{
|
182 |
+
"metric": "acc_norm",
|
183 |
+
"aggregation": "mean",
|
184 |
+
"higher_is_better": true
|
185 |
+
}
|
186 |
+
],
|
187 |
+
"output_type": "multiple_choice",
|
188 |
+
"repeats": 1,
|
189 |
+
"should_decontaminate": false
|
190 |
+
},
|
191 |
+
"lambada_openai": {
|
192 |
+
"task": "lambada_openai",
|
193 |
+
"group": [
|
194 |
+
"lambada",
|
195 |
+
"loglikelihood",
|
196 |
+
"perplexity"
|
197 |
+
],
|
198 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
199 |
+
"dataset_name": "default",
|
200 |
+
"test_split": "test",
|
201 |
+
"template_aliases": "",
|
202 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
203 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
204 |
+
"description": "",
|
205 |
+
"target_delimiter": " ",
|
206 |
+
"fewshot_delimiter": "\n\n",
|
207 |
+
"num_fewshot": 0,
|
208 |
+
"metric_list": [
|
209 |
+
{
|
210 |
+
"metric": "perplexity",
|
211 |
+
"aggregation": "perplexity",
|
212 |
+
"higher_is_better": false
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"metric": "acc",
|
216 |
+
"aggregation": "mean",
|
217 |
+
"higher_is_better": true
|
218 |
+
}
|
219 |
+
],
|
220 |
+
"output_type": "loglikelihood",
|
221 |
+
"repeats": 1,
|
222 |
+
"should_decontaminate": true,
|
223 |
+
"doc_to_decontamination_query": "{{text}}"
|
224 |
+
},
|
225 |
+
"openbookqa": {
|
226 |
+
"task": "openbookqa",
|
227 |
+
"group": [
|
228 |
+
"multiple_choice"
|
229 |
+
],
|
230 |
+
"dataset_path": "openbookqa",
|
231 |
+
"dataset_name": "main",
|
232 |
+
"training_split": "train",
|
233 |
+
"validation_split": "validation",
|
234 |
+
"test_split": "test",
|
235 |
+
"doc_to_text": "question_stem",
|
236 |
+
"doc_to_target": "{{choices.label.index(answerKey.lstrip())}}",
|
237 |
+
"doc_to_choice": "{{choices.text}}",
|
238 |
+
"description": "",
|
239 |
+
"target_delimiter": " ",
|
240 |
+
"fewshot_delimiter": "\n\n",
|
241 |
+
"num_fewshot": 0,
|
242 |
+
"metric_list": [
|
243 |
+
{
|
244 |
+
"metric": "acc",
|
245 |
+
"aggregation": "mean",
|
246 |
+
"higher_is_better": true
|
247 |
+
},
|
248 |
+
{
|
249 |
+
"metric": "acc_norm",
|
250 |
+
"aggregation": "mean",
|
251 |
+
"higher_is_better": true
|
252 |
+
}
|
253 |
+
],
|
254 |
+
"output_type": "multiple_choice",
|
255 |
+
"repeats": 1,
|
256 |
+
"should_decontaminate": true,
|
257 |
+
"doc_to_decontamination_query": "question_stem"
|
258 |
+
},
|
259 |
+
"piqa": {
|
260 |
+
"task": "piqa",
|
261 |
+
"group": [
|
262 |
+
"multiple_choice"
|
263 |
+
],
|
264 |
+
"dataset_path": "piqa",
|
265 |
+
"training_split": "train",
|
266 |
+
"validation_split": "validation",
|
267 |
+
"doc_to_text": "Question: {{goal}}\nAnswer:",
|
268 |
+
"doc_to_target": "label",
|
269 |
+
"doc_to_choice": "{{[sol1, sol2]}}",
|
270 |
+
"description": "",
|
271 |
+
"target_delimiter": " ",
|
272 |
+
"fewshot_delimiter": "\n\n",
|
273 |
+
"num_fewshot": 0,
|
274 |
+
"metric_list": [
|
275 |
+
{
|
276 |
+
"metric": "acc",
|
277 |
+
"aggregation": "mean",
|
278 |
+
"higher_is_better": true
|
279 |
+
},
|
280 |
+
{
|
281 |
+
"metric": "acc_norm",
|
282 |
+
"aggregation": "mean",
|
283 |
+
"higher_is_better": true
|
284 |
+
}
|
285 |
+
],
|
286 |
+
"output_type": "multiple_choice",
|
287 |
+
"repeats": 1,
|
288 |
+
"should_decontaminate": true,
|
289 |
+
"doc_to_decontamination_query": "goal"
|
290 |
+
},
|
291 |
+
"sciq": {
|
292 |
+
"task": "sciq",
|
293 |
+
"group": [
|
294 |
+
"multiple_choice"
|
295 |
+
],
|
296 |
+
"dataset_path": "sciq",
|
297 |
+
"training_split": "train",
|
298 |
+
"validation_split": "validation",
|
299 |
+
"test_split": "test",
|
300 |
+
"doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
|
301 |
+
"doc_to_target": 3,
|
302 |
+
"doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
|
303 |
+
"description": "",
|
304 |
+
"target_delimiter": " ",
|
305 |
+
"fewshot_delimiter": "\n\n",
|
306 |
+
"num_fewshot": 0,
|
307 |
+
"metric_list": [
|
308 |
+
{
|
309 |
+
"metric": "acc",
|
310 |
+
"aggregation": "mean",
|
311 |
+
"higher_is_better": true
|
312 |
+
},
|
313 |
+
{
|
314 |
+
"metric": "acc_norm",
|
315 |
+
"aggregation": "mean",
|
316 |
+
"higher_is_better": true
|
317 |
+
}
|
318 |
+
],
|
319 |
+
"output_type": "multiple_choice",
|
320 |
+
"repeats": 1,
|
321 |
+
"should_decontaminate": true,
|
322 |
+
"doc_to_decontamination_query": "{{support}} {{question}}"
|
323 |
+
},
|
324 |
+
"wikitext": {
|
325 |
+
"task": "wikitext",
|
326 |
+
"group": [
|
327 |
+
"perplexity",
|
328 |
+
"loglikelihood_rolling"
|
329 |
+
],
|
330 |
+
"dataset_path": "EleutherAI/wikitext_document_level",
|
331 |
+
"dataset_name": "wikitext-2-raw-v1",
|
332 |
+
"training_split": "train",
|
333 |
+
"validation_split": "validation",
|
334 |
+
"test_split": "test",
|
335 |
+
"template_aliases": "",
|
336 |
+
"doc_to_text": "",
|
337 |
+
"doc_to_target": "<function wikitext_detokenizer at 0x7fd1a1c44040>",
|
338 |
+
"description": "",
|
339 |
+
"target_delimiter": " ",
|
340 |
+
"fewshot_delimiter": "\n\n",
|
341 |
+
"num_fewshot": 0,
|
342 |
+
"metric_list": [
|
343 |
+
{
|
344 |
+
"metric": "word_perplexity"
|
345 |
+
},
|
346 |
+
{
|
347 |
+
"metric": "byte_perplexity"
|
348 |
+
},
|
349 |
+
{
|
350 |
+
"metric": "bits_per_byte"
|
351 |
+
}
|
352 |
+
],
|
353 |
+
"output_type": "loglikelihood_rolling",
|
354 |
+
"repeats": 1,
|
355 |
+
"should_decontaminate": true,
|
356 |
+
"doc_to_decontamination_query": "{{page}}"
|
357 |
+
},
|
358 |
+
"winogrande": {
|
359 |
+
"task": "winogrande",
|
360 |
+
"dataset_path": "winogrande",
|
361 |
+
"dataset_name": "winogrande_xl",
|
362 |
+
"training_split": "train",
|
363 |
+
"validation_split": "validation",
|
364 |
+
"doc_to_text": "<function doc_to_text at 0x7fd1a1c16ef0>",
|
365 |
+
"doc_to_target": "<function doc_to_target at 0x7fd1a1c17370>",
|
366 |
+
"doc_to_choice": "<function doc_to_choice at 0x7fd1a1c175b0>",
|
367 |
+
"description": "",
|
368 |
+
"target_delimiter": " ",
|
369 |
+
"fewshot_delimiter": "\n\n",
|
370 |
+
"num_fewshot": 0,
|
371 |
+
"metric_list": [
|
372 |
+
{
|
373 |
+
"metric": "acc",
|
374 |
+
"aggregation": "mean",
|
375 |
+
"higher_is_better": true
|
376 |
+
}
|
377 |
+
],
|
378 |
+
"output_type": "multiple_choice",
|
379 |
+
"repeats": 1,
|
380 |
+
"should_decontaminate": false
|
381 |
+
}
|
382 |
+
},
|
383 |
+
"versions": {
|
384 |
+
"arc_challenge": "Yaml",
|
385 |
+
"arc_easy": "Yaml",
|
386 |
+
"boolq": "Yaml",
|
387 |
+
"hellaswag": "Yaml",
|
388 |
+
"lambada_openai": "Yaml",
|
389 |
+
"openbookqa": "Yaml",
|
390 |
+
"piqa": "Yaml",
|
391 |
+
"sciq": "Yaml",
|
392 |
+
"wikitext": "Yaml",
|
393 |
+
"winogrande": "Yaml"
|
394 |
+
},
|
395 |
+
"config": {
|
396 |
+
"model": "hf",
|
397 |
+
"model_args": "pretrained=lomahony/eleuther-pythia160m-hh-dpo",
|
398 |
+
"num_fewshot": 0,
|
399 |
+
"batch_size": 16,
|
400 |
+
"batch_sizes": [],
|
401 |
+
"device": "cuda:0",
|
402 |
+
"use_cache": null,
|
403 |
+
"limit": null,
|
404 |
+
"bootstrap_iters": 100000
|
405 |
+
},
|
406 |
+
"git_hash": "4e44f0a"
|
407 |
+
}
|
408 |
+
hf (pretrained=lomahony/eleuther-pythia160m-hh-dpo), limit: None, num_fewshot: 0, batch_size: 16
|
409 |
+
| Task |Version|Filter| Metric | Value | |Stderr|
|
410 |
+
|--------------|-------|------|---------------|------:|---|-----:|
|
411 |
+
|arc_challenge |Yaml |none |acc | 0.1928|± |0.0115|
|
412 |
+
| | |none |acc_norm | 0.2449|± |0.0126|
|
413 |
+
|arc_easy |Yaml |none |acc | 0.4672|± |0.0102|
|
414 |
+
| | |none |acc_norm | 0.4133|± |0.0101|
|
415 |
+
|boolq |Yaml |none |acc | 0.6150|± |0.0085|
|
416 |
+
|hellaswag |Yaml |none |acc | 0.2896|± |0.0045|
|
417 |
+
| | |none |acc_norm | 0.3016|± |0.0046|
|
418 |
+
|lambada_openai|Yaml |none |perplexity |40.4975|± |1.9471|
|
419 |
+
| | |none |acc | 0.3507|± |0.0066|
|
420 |
+
|openbookqa |Yaml |none |acc | 0.1720|± |0.0169|
|
421 |
+
| | |none |acc_norm | 0.2800|± |0.0201|
|
422 |
+
|piqa |Yaml |none |acc | 0.6333|± |0.0112|
|
423 |
+
| | |none |acc_norm | 0.6262|± |0.0113|
|
424 |
+
|sciq |Yaml |none |acc | 0.7530|± |0.0136|
|
425 |
+
| | |none |acc_norm | 0.6700|± |0.0149|
|
426 |
+
|wikitext |Yaml |none |word_perplexity|75.2499| | |
|
427 |
+
| | |none |byte_perplexity| 2.0387| | |
|
428 |
+
| | |none |bits_per_byte | 1.0276| | |
|
429 |
+
|winogrande |Yaml |none |acc | 0.5138|± |0.0140|
|
430 |
+
|
dpo-160m-eval-files/dpo-pythia-160m-5shot-shelloutput.txt
ADDED
@@ -0,0 +1,430 @@
|
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|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
bootstrapping for stddev: perplexity
|
2 |
+
{
|
3 |
+
"results": {
|
4 |
+
"arc_challenge": {
|
5 |
+
"acc,none": 0.20563139931740615,
|
6 |
+
"acc_stderr,none": 0.011810745260742547,
|
7 |
+
"acc_norm,none": 0.24744027303754265,
|
8 |
+
"acc_norm_stderr,none": 0.01261035266329267
|
9 |
+
},
|
10 |
+
"arc_easy": {
|
11 |
+
"acc,none": 0.46380471380471383,
|
12 |
+
"acc_stderr,none": 0.01023286555034674,
|
13 |
+
"acc_norm,none": 0.4385521885521885,
|
14 |
+
"acc_norm_stderr,none": 0.010182010275471116
|
15 |
+
},
|
16 |
+
"boolq": {
|
17 |
+
"acc,none": 0.6055045871559633,
|
18 |
+
"acc_stderr,none": 0.008548152025770934
|
19 |
+
},
|
20 |
+
"hellaswag": {
|
21 |
+
"acc,none": 0.2885879306910974,
|
22 |
+
"acc_stderr,none": 0.004521798577922137,
|
23 |
+
"acc_norm,none": 0.3088030272854013,
|
24 |
+
"acc_norm_stderr,none": 0.004610554974411229
|
25 |
+
},
|
26 |
+
"lambada_openai": {
|
27 |
+
"perplexity,none": 68.78788187981594,
|
28 |
+
"perplexity_stderr,none": 3.3418985414978897,
|
29 |
+
"acc,none": 0.2815835435668543,
|
30 |
+
"acc_stderr,none": 0.006266194106395877
|
31 |
+
},
|
32 |
+
"openbookqa": {
|
33 |
+
"acc,none": 0.158,
|
34 |
+
"acc_stderr,none": 0.01632804980457984,
|
35 |
+
"acc_norm,none": 0.254,
|
36 |
+
"acc_norm_stderr,none": 0.019486596801643368
|
37 |
+
},
|
38 |
+
"piqa": {
|
39 |
+
"acc,none": 0.6284004352557128,
|
40 |
+
"acc_stderr,none": 0.011274603006724757,
|
41 |
+
"acc_norm,none": 0.6332970620239391,
|
42 |
+
"acc_norm_stderr,none": 0.01124362501903826
|
43 |
+
},
|
44 |
+
"sciq": {
|
45 |
+
"acc,none": 0.76,
|
46 |
+
"acc_stderr,none": 0.013512312258920836,
|
47 |
+
"acc_norm,none": 0.737,
|
48 |
+
"acc_norm_stderr,none": 0.013929286594259724
|
49 |
+
},
|
50 |
+
"wikitext": {
|
51 |
+
"word_perplexity,none": 75.24993841350984,
|
52 |
+
"byte_perplexity,none": 2.0386909133746456,
|
53 |
+
"bits_per_byte,none": 1.0276430644458452
|
54 |
+
},
|
55 |
+
"winogrande": {
|
56 |
+
"acc,none": 0.5138121546961326,
|
57 |
+
"acc_stderr,none": 0.014047122916440419
|
58 |
+
}
|
59 |
+
},
|
60 |
+
"configs": {
|
61 |
+
"arc_challenge": {
|
62 |
+
"task": "arc_challenge",
|
63 |
+
"group": [
|
64 |
+
"ai2_arc",
|
65 |
+
"multiple_choice"
|
66 |
+
],
|
67 |
+
"dataset_path": "ai2_arc",
|
68 |
+
"dataset_name": "ARC-Challenge",
|
69 |
+
"training_split": "train",
|
70 |
+
"validation_split": "validation",
|
71 |
+
"test_split": "test",
|
72 |
+
"doc_to_text": "Question: {{question}}\nAnswer:",
|
73 |
+
"doc_to_target": "{{choices.label.index(answerKey)}}",
|
74 |
+
"doc_to_choice": "{{choices.text}}",
|
75 |
+
"description": "",
|
76 |
+
"target_delimiter": " ",
|
77 |
+
"fewshot_delimiter": "\n\n",
|
78 |
+
"num_fewshot": 5,
|
79 |
+
"metric_list": [
|
80 |
+
{
|
81 |
+
"metric": "acc",
|
82 |
+
"aggregation": "mean",
|
83 |
+
"higher_is_better": true
|
84 |
+
},
|
85 |
+
{
|
86 |
+
"metric": "acc_norm",
|
87 |
+
"aggregation": "mean",
|
88 |
+
"higher_is_better": true
|
89 |
+
}
|
90 |
+
],
|
91 |
+
"output_type": "multiple_choice",
|
92 |
+
"repeats": 1,
|
93 |
+
"should_decontaminate": true,
|
94 |
+
"doc_to_decontamination_query": "Question: {{question}}\nAnswer:"
|
95 |
+
},
|
96 |
+
"arc_easy": {
|
97 |
+
"task": "arc_easy",
|
98 |
+
"group": [
|
99 |
+
"ai2_arc",
|
100 |
+
"multiple_choice"
|
101 |
+
],
|
102 |
+
"dataset_path": "ai2_arc",
|
103 |
+
"dataset_name": "ARC-Easy",
|
104 |
+
"training_split": "train",
|
105 |
+
"validation_split": "validation",
|
106 |
+
"test_split": "test",
|
107 |
+
"doc_to_text": "Question: {{question}}\nAnswer:",
|
108 |
+
"doc_to_target": "{{choices.label.index(answerKey)}}",
|
109 |
+
"doc_to_choice": "{{choices.text}}",
|
110 |
+
"description": "",
|
111 |
+
"target_delimiter": " ",
|
112 |
+
"fewshot_delimiter": "\n\n",
|
113 |
+
"num_fewshot": 5,
|
114 |
+
"metric_list": [
|
115 |
+
{
|
116 |
+
"metric": "acc",
|
117 |
+
"aggregation": "mean",
|
118 |
+
"higher_is_better": true
|
119 |
+
},
|
120 |
+
{
|
121 |
+
"metric": "acc_norm",
|
122 |
+
"aggregation": "mean",
|
123 |
+
"higher_is_better": true
|
124 |
+
}
|
125 |
+
],
|
126 |
+
"output_type": "multiple_choice",
|
127 |
+
"repeats": 1,
|
128 |
+
"should_decontaminate": true,
|
129 |
+
"doc_to_decontamination_query": "Question: {{question}}\nAnswer:"
|
130 |
+
},
|
131 |
+
"boolq": {
|
132 |
+
"task": "boolq",
|
133 |
+
"group": [
|
134 |
+
"super-glue-lm-eval-v1"
|
135 |
+
],
|
136 |
+
"dataset_path": "super_glue",
|
137 |
+
"dataset_name": "boolq",
|
138 |
+
"training_split": "train",
|
139 |
+
"validation_split": "validation",
|
140 |
+
"doc_to_text": "{{passage}}\nQuestion: {{question}}?\nAnswer:",
|
141 |
+
"doc_to_target": "label",
|
142 |
+
"doc_to_choice": [
|
143 |
+
"no",
|
144 |
+
"yes"
|
145 |
+
],
|
146 |
+
"description": "",
|
147 |
+
"target_delimiter": " ",
|
148 |
+
"fewshot_delimiter": "\n\n",
|
149 |
+
"num_fewshot": 5,
|
150 |
+
"metric_list": [
|
151 |
+
{
|
152 |
+
"metric": "acc"
|
153 |
+
}
|
154 |
+
],
|
155 |
+
"output_type": "multiple_choice",
|
156 |
+
"repeats": 1,
|
157 |
+
"should_decontaminate": true,
|
158 |
+
"doc_to_decontamination_query": "passage"
|
159 |
+
},
|
160 |
+
"hellaswag": {
|
161 |
+
"task": "hellaswag",
|
162 |
+
"group": [
|
163 |
+
"multiple_choice"
|
164 |
+
],
|
165 |
+
"dataset_path": "hellaswag",
|
166 |
+
"training_split": "train",
|
167 |
+
"validation_split": "validation",
|
168 |
+
"doc_to_text": "{% set text = activity_label ~ ': ' ~ ctx_a ~ ' ' ~ ctx_b.capitalize() %}{{text|trim|replace(' [title]', '. ')|regex_replace('\\[.*?\\]', '')|replace(' ', ' ')}}",
|
169 |
+
"doc_to_target": "{{label}}",
|
170 |
+
"doc_to_choice": "{{endings|map('trim')|map('replace', ' [title]', '. ')|map('regex_replace', '\\[.*?\\]', '')|map('replace', ' ', ' ')|list}}",
|
171 |
+
"description": "",
|
172 |
+
"target_delimiter": " ",
|
173 |
+
"fewshot_delimiter": "\n\n",
|
174 |
+
"num_fewshot": 5,
|
175 |
+
"metric_list": [
|
176 |
+
{
|
177 |
+
"metric": "acc",
|
178 |
+
"aggregation": "mean",
|
179 |
+
"higher_is_better": true
|
180 |
+
},
|
181 |
+
{
|
182 |
+
"metric": "acc_norm",
|
183 |
+
"aggregation": "mean",
|
184 |
+
"higher_is_better": true
|
185 |
+
}
|
186 |
+
],
|
187 |
+
"output_type": "multiple_choice",
|
188 |
+
"repeats": 1,
|
189 |
+
"should_decontaminate": false
|
190 |
+
},
|
191 |
+
"lambada_openai": {
|
192 |
+
"task": "lambada_openai",
|
193 |
+
"group": [
|
194 |
+
"lambada",
|
195 |
+
"loglikelihood",
|
196 |
+
"perplexity"
|
197 |
+
],
|
198 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
199 |
+
"dataset_name": "default",
|
200 |
+
"test_split": "test",
|
201 |
+
"template_aliases": "",
|
202 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
203 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
204 |
+
"description": "",
|
205 |
+
"target_delimiter": " ",
|
206 |
+
"fewshot_delimiter": "\n\n",
|
207 |
+
"num_fewshot": 5,
|
208 |
+
"metric_list": [
|
209 |
+
{
|
210 |
+
"metric": "perplexity",
|
211 |
+
"aggregation": "perplexity",
|
212 |
+
"higher_is_better": false
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"metric": "acc",
|
216 |
+
"aggregation": "mean",
|
217 |
+
"higher_is_better": true
|
218 |
+
}
|
219 |
+
],
|
220 |
+
"output_type": "loglikelihood",
|
221 |
+
"repeats": 1,
|
222 |
+
"should_decontaminate": true,
|
223 |
+
"doc_to_decontamination_query": "{{text}}"
|
224 |
+
},
|
225 |
+
"openbookqa": {
|
226 |
+
"task": "openbookqa",
|
227 |
+
"group": [
|
228 |
+
"multiple_choice"
|
229 |
+
],
|
230 |
+
"dataset_path": "openbookqa",
|
231 |
+
"dataset_name": "main",
|
232 |
+
"training_split": "train",
|
233 |
+
"validation_split": "validation",
|
234 |
+
"test_split": "test",
|
235 |
+
"doc_to_text": "question_stem",
|
236 |
+
"doc_to_target": "{{choices.label.index(answerKey.lstrip())}}",
|
237 |
+
"doc_to_choice": "{{choices.text}}",
|
238 |
+
"description": "",
|
239 |
+
"target_delimiter": " ",
|
240 |
+
"fewshot_delimiter": "\n\n",
|
241 |
+
"num_fewshot": 5,
|
242 |
+
"metric_list": [
|
243 |
+
{
|
244 |
+
"metric": "acc",
|
245 |
+
"aggregation": "mean",
|
246 |
+
"higher_is_better": true
|
247 |
+
},
|
248 |
+
{
|
249 |
+
"metric": "acc_norm",
|
250 |
+
"aggregation": "mean",
|
251 |
+
"higher_is_better": true
|
252 |
+
}
|
253 |
+
],
|
254 |
+
"output_type": "multiple_choice",
|
255 |
+
"repeats": 1,
|
256 |
+
"should_decontaminate": true,
|
257 |
+
"doc_to_decontamination_query": "question_stem"
|
258 |
+
},
|
259 |
+
"piqa": {
|
260 |
+
"task": "piqa",
|
261 |
+
"group": [
|
262 |
+
"multiple_choice"
|
263 |
+
],
|
264 |
+
"dataset_path": "piqa",
|
265 |
+
"training_split": "train",
|
266 |
+
"validation_split": "validation",
|
267 |
+
"doc_to_text": "Question: {{goal}}\nAnswer:",
|
268 |
+
"doc_to_target": "label",
|
269 |
+
"doc_to_choice": "{{[sol1, sol2]}}",
|
270 |
+
"description": "",
|
271 |
+
"target_delimiter": " ",
|
272 |
+
"fewshot_delimiter": "\n\n",
|
273 |
+
"num_fewshot": 5,
|
274 |
+
"metric_list": [
|
275 |
+
{
|
276 |
+
"metric": "acc",
|
277 |
+
"aggregation": "mean",
|
278 |
+
"higher_is_better": true
|
279 |
+
},
|
280 |
+
{
|
281 |
+
"metric": "acc_norm",
|
282 |
+
"aggregation": "mean",
|
283 |
+
"higher_is_better": true
|
284 |
+
}
|
285 |
+
],
|
286 |
+
"output_type": "multiple_choice",
|
287 |
+
"repeats": 1,
|
288 |
+
"should_decontaminate": true,
|
289 |
+
"doc_to_decontamination_query": "goal"
|
290 |
+
},
|
291 |
+
"sciq": {
|
292 |
+
"task": "sciq",
|
293 |
+
"group": [
|
294 |
+
"multiple_choice"
|
295 |
+
],
|
296 |
+
"dataset_path": "sciq",
|
297 |
+
"training_split": "train",
|
298 |
+
"validation_split": "validation",
|
299 |
+
"test_split": "test",
|
300 |
+
"doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
|
301 |
+
"doc_to_target": 3,
|
302 |
+
"doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
|
303 |
+
"description": "",
|
304 |
+
"target_delimiter": " ",
|
305 |
+
"fewshot_delimiter": "\n\n",
|
306 |
+
"num_fewshot": 5,
|
307 |
+
"metric_list": [
|
308 |
+
{
|
309 |
+
"metric": "acc",
|
310 |
+
"aggregation": "mean",
|
311 |
+
"higher_is_better": true
|
312 |
+
},
|
313 |
+
{
|
314 |
+
"metric": "acc_norm",
|
315 |
+
"aggregation": "mean",
|
316 |
+
"higher_is_better": true
|
317 |
+
}
|
318 |
+
],
|
319 |
+
"output_type": "multiple_choice",
|
320 |
+
"repeats": 1,
|
321 |
+
"should_decontaminate": true,
|
322 |
+
"doc_to_decontamination_query": "{{support}} {{question}}"
|
323 |
+
},
|
324 |
+
"wikitext": {
|
325 |
+
"task": "wikitext",
|
326 |
+
"group": [
|
327 |
+
"perplexity",
|
328 |
+
"loglikelihood_rolling"
|
329 |
+
],
|
330 |
+
"dataset_path": "EleutherAI/wikitext_document_level",
|
331 |
+
"dataset_name": "wikitext-2-raw-v1",
|
332 |
+
"training_split": "train",
|
333 |
+
"validation_split": "validation",
|
334 |
+
"test_split": "test",
|
335 |
+
"template_aliases": "",
|
336 |
+
"doc_to_text": "",
|
337 |
+
"doc_to_target": "<function wikitext_detokenizer at 0x7ff6ce1e4040>",
|
338 |
+
"description": "",
|
339 |
+
"target_delimiter": " ",
|
340 |
+
"fewshot_delimiter": "\n\n",
|
341 |
+
"num_fewshot": 5,
|
342 |
+
"metric_list": [
|
343 |
+
{
|
344 |
+
"metric": "word_perplexity"
|
345 |
+
},
|
346 |
+
{
|
347 |
+
"metric": "byte_perplexity"
|
348 |
+
},
|
349 |
+
{
|
350 |
+
"metric": "bits_per_byte"
|
351 |
+
}
|
352 |
+
],
|
353 |
+
"output_type": "loglikelihood_rolling",
|
354 |
+
"repeats": 1,
|
355 |
+
"should_decontaminate": true,
|
356 |
+
"doc_to_decontamination_query": "{{page}}"
|
357 |
+
},
|
358 |
+
"winogrande": {
|
359 |
+
"task": "winogrande",
|
360 |
+
"dataset_path": "winogrande",
|
361 |
+
"dataset_name": "winogrande_xl",
|
362 |
+
"training_split": "train",
|
363 |
+
"validation_split": "validation",
|
364 |
+
"doc_to_text": "<function doc_to_text at 0x7ff6ce1b6ef0>",
|
365 |
+
"doc_to_target": "<function doc_to_target at 0x7ff6ce1b7370>",
|
366 |
+
"doc_to_choice": "<function doc_to_choice at 0x7ff6ce1b75b0>",
|
367 |
+
"description": "",
|
368 |
+
"target_delimiter": " ",
|
369 |
+
"fewshot_delimiter": "\n\n",
|
370 |
+
"num_fewshot": 5,
|
371 |
+
"metric_list": [
|
372 |
+
{
|
373 |
+
"metric": "acc",
|
374 |
+
"aggregation": "mean",
|
375 |
+
"higher_is_better": true
|
376 |
+
}
|
377 |
+
],
|
378 |
+
"output_type": "multiple_choice",
|
379 |
+
"repeats": 1,
|
380 |
+
"should_decontaminate": false
|
381 |
+
}
|
382 |
+
},
|
383 |
+
"versions": {
|
384 |
+
"arc_challenge": "Yaml",
|
385 |
+
"arc_easy": "Yaml",
|
386 |
+
"boolq": "Yaml",
|
387 |
+
"hellaswag": "Yaml",
|
388 |
+
"lambada_openai": "Yaml",
|
389 |
+
"openbookqa": "Yaml",
|
390 |
+
"piqa": "Yaml",
|
391 |
+
"sciq": "Yaml",
|
392 |
+
"wikitext": "Yaml",
|
393 |
+
"winogrande": "Yaml"
|
394 |
+
},
|
395 |
+
"config": {
|
396 |
+
"model": "hf",
|
397 |
+
"model_args": "pretrained=lomahony/eleuther-pythia160m-hh-dpo",
|
398 |
+
"num_fewshot": 5,
|
399 |
+
"batch_size": 16,
|
400 |
+
"batch_sizes": [],
|
401 |
+
"device": "cuda:0",
|
402 |
+
"use_cache": null,
|
403 |
+
"limit": null,
|
404 |
+
"bootstrap_iters": 100000
|
405 |
+
},
|
406 |
+
"git_hash": "4e44f0a"
|
407 |
+
}
|
408 |
+
hf (pretrained=lomahony/eleuther-pythia160m-hh-dpo), limit: None, num_fewshot: 5, batch_size: 16
|
409 |
+
| Task |Version|Filter| Metric | Value | |Stderr|
|
410 |
+
|--------------|-------|------|---------------|------:|---|-----:|
|
411 |
+
|arc_challenge |Yaml |none |acc | 0.2056|± |0.0118|
|
412 |
+
| | |none |acc_norm | 0.2474|± |0.0126|
|
413 |
+
|arc_easy |Yaml |none |acc | 0.4638|± |0.0102|
|
414 |
+
| | |none |acc_norm | 0.4386|± |0.0102|
|
415 |
+
|boolq |Yaml |none |acc | 0.6055|± |0.0085|
|
416 |
+
|hellaswag |Yaml |none |acc | 0.2886|± |0.0045|
|
417 |
+
| | |none |acc_norm | 0.3088|± |0.0046|
|
418 |
+
|lambada_openai|Yaml |none |perplexity |68.7879|± |3.3419|
|
419 |
+
| | |none |acc | 0.2816|± |0.0063|
|
420 |
+
|openbookqa |Yaml |none |acc | 0.1580|± |0.0163|
|
421 |
+
| | |none |acc_norm | 0.2540|± |0.0195|
|
422 |
+
|piqa |Yaml |none |acc | 0.6284|± |0.0113|
|
423 |
+
| | |none |acc_norm | 0.6333|± |0.0112|
|
424 |
+
|sciq |Yaml |none |acc | 0.7600|± |0.0135|
|
425 |
+
| | |none |acc_norm | 0.7370|± |0.0139|
|
426 |
+
|wikitext |Yaml |none |word_perplexity|75.2499| | |
|
427 |
+
| | |none |byte_perplexity| 2.0387| | |
|
428 |
+
| | |none |bits_per_byte | 1.0276| | |
|
429 |
+
|winogrande |Yaml |none |acc | 0.5138|± |0.0140|
|
430 |
+
|