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dpo-410m-eval-files/EleutherAI-pythia-410m-0shot-shelloutput.txt
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1 |
+
bootstrapping for stddev: perplexity
|
2 |
+
{
|
3 |
+
"results": {
|
4 |
+
"arc_challenge": {
|
5 |
+
"acc,none": 0.21416382252559726,
|
6 |
+
"acc_stderr,none": 0.011988383205966515,
|
7 |
+
"acc_norm,none": 0.2431740614334471,
|
8 |
+
"acc_norm_stderr,none": 0.012536554144587084
|
9 |
+
},
|
10 |
+
"arc_easy": {
|
11 |
+
"acc,none": 0.5189393939393939,
|
12 |
+
"acc_stderr,none": 0.01025242049689449,
|
13 |
+
"acc_norm,none": 0.45707070707070707,
|
14 |
+
"acc_norm_stderr,none": 0.010221897564256049
|
15 |
+
},
|
16 |
+
"boolq": {
|
17 |
+
"acc,none": 0.6058103975535168,
|
18 |
+
"acc_stderr,none": 0.008546995661233639
|
19 |
+
},
|
20 |
+
"hellaswag": {
|
21 |
+
"acc,none": 0.33718382792272455,
|
22 |
+
"acc_stderr,none": 0.004717820714968757,
|
23 |
+
"acc_norm,none": 0.4060944035052778,
|
24 |
+
"acc_norm_stderr,none": 0.004900988997414242
|
25 |
+
},
|
26 |
+
"lambada_openai": {
|
27 |
+
"perplexity,none": 10.780459714601333,
|
28 |
+
"perplexity_stderr,none": 0.32049412467424027,
|
29 |
+
"acc,none": 0.5163982146322531,
|
30 |
+
"acc_stderr,none": 0.006962230326368326
|
31 |
+
},
|
32 |
+
"openbookqa": {
|
33 |
+
"acc,none": 0.182,
|
34 |
+
"acc_stderr,none": 0.01727277329773045,
|
35 |
+
"acc_norm,none": 0.294,
|
36 |
+
"acc_norm_stderr,none": 0.020395095484936624
|
37 |
+
},
|
38 |
+
"piqa": {
|
39 |
+
"acc,none": 0.6670293797606094,
|
40 |
+
"acc_stderr,none": 0.010995648822619082,
|
41 |
+
"acc_norm,none": 0.6719260065288357,
|
42 |
+
"acc_norm_stderr,none": 0.010954487135124227
|
43 |
+
},
|
44 |
+
"sciq": {
|
45 |
+
"acc,none": 0.815,
|
46 |
+
"acc_stderr,none": 0.012285191326386667,
|
47 |
+
"acc_norm,none": 0.725,
|
48 |
+
"acc_norm_stderr,none": 0.014127086556490528
|
49 |
+
},
|
50 |
+
"wikitext": {
|
51 |
+
"word_perplexity,none": 34.50450469911897,
|
52 |
+
"byte_perplexity,none": 1.7927778872125213,
|
53 |
+
"bits_per_byte,none": 0.842196759334895
|
54 |
+
},
|
55 |
+
"winogrande": {
|
56 |
+
"acc,none": 0.5335438042620363,
|
57 |
+
"acc_stderr,none": 0.014020826677598103
|
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 0x7fae1b130040>",
|
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 0x7fae1b102ef0>",
|
365 |
+
"doc_to_target": "<function doc_to_target at 0x7fae1b103370>",
|
366 |
+
"doc_to_choice": "<function doc_to_choice at 0x7fae1b1035b0>",
|
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=EleutherAI/pythia-410m",
|
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=EleutherAI/pythia-410m), limit: None, num_fewshot: 0, batch_size: 16
|
409 |
+
| Task |Version|Filter| Metric | Value | |Stderr|
|
410 |
+
|--------------|-------|------|---------------|------:|---|-----:|
|
411 |
+
|arc_challenge |Yaml |none |acc | 0.2142|± |0.0120|
|
412 |
+
| | |none |acc_norm | 0.2432|± |0.0125|
|
413 |
+
|arc_easy |Yaml |none |acc | 0.5189|± |0.0103|
|
414 |
+
| | |none |acc_norm | 0.4571|± |0.0102|
|
415 |
+
|boolq |Yaml |none |acc | 0.6058|± |0.0085|
|
416 |
+
|hellaswag |Yaml |none |acc | 0.3372|± |0.0047|
|
417 |
+
| | |none |acc_norm | 0.4061|± |0.0049|
|
418 |
+
|lambada_openai|Yaml |none |perplexity |10.7805|± |0.3205|
|
419 |
+
| | |none |acc | 0.5164|± |0.0070|
|
420 |
+
|openbookqa |Yaml |none |acc | 0.1820|± |0.0173|
|
421 |
+
| | |none |acc_norm | 0.2940|± |0.0204|
|
422 |
+
|piqa |Yaml |none |acc | 0.6670|± |0.0110|
|
423 |
+
| | |none |acc_norm | 0.6719|± |0.0110|
|
424 |
+
|sciq |Yaml |none |acc | 0.8150|± |0.0123|
|
425 |
+
| | |none |acc_norm | 0.7250|± |0.0141|
|
426 |
+
|wikitext |Yaml |none |word_perplexity|34.5045| | |
|
427 |
+
| | |none |byte_perplexity| 1.7928| | |
|
428 |
+
| | |none |bits_per_byte | 0.8422| | |
|
429 |
+
|winogrande |Yaml |none |acc | 0.5335|± |0.0140|
|
430 |
+
|
dpo-410m-eval-files/EleutherAI-pythia-410m-5shot-shelloutput.txt
ADDED
@@ -0,0 +1,440 @@
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|
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|
1 |
+
Downloading and preparing dataset super_glue/boolq to /home/laura/.cache/huggingface/datasets/super_glue/boolq/1.0.3/bb9675f958ebfee0d5d6dc5476fafe38c79123727a7258d515c450873dbdbbed...
|
2 |
+
Dataset super_glue downloaded and prepared to /home/laura/.cache/huggingface/datasets/super_glue/boolq/1.0.3/bb9675f958ebfee0d5d6dc5476fafe38c79123727a7258d515c450873dbdbbed. Subsequent calls will reuse this data.
|
3 |
+
Downloading and preparing dataset openbookqa/main to /home/laura/.cache/huggingface/datasets/openbookqa/main/1.0.1/f338ccacfbc86fb8c2de3aa1c06d2ce686933de3bca284dba97d32592c52b33f...
|
4 |
+
Dataset openbookqa downloaded and prepared to /home/laura/.cache/huggingface/datasets/openbookqa/main/1.0.1/f338ccacfbc86fb8c2de3aa1c06d2ce686933de3bca284dba97d32592c52b33f. Subsequent calls will reuse this data.
|
5 |
+
Downloading and preparing dataset piqa/plain_text to /home/laura/.cache/huggingface/datasets/piqa/plain_text/1.1.0/6c611c1a9bf220943c4174e117d3b660859665baf1d43156230116185312d011...
|
6 |
+
Dataset piqa downloaded and prepared to /home/laura/.cache/huggingface/datasets/piqa/plain_text/1.1.0/6c611c1a9bf220943c4174e117d3b660859665baf1d43156230116185312d011. Subsequent calls will reuse this data.
|
7 |
+
Downloading and preparing dataset sciq/default to /home/laura/.cache/huggingface/datasets/sciq/default/0.1.0/50e5c6e3795b55463819d399ec417bfd4c3c621105e00295ddb5f3633d708493...
|
8 |
+
Dataset sciq downloaded and prepared to /home/laura/.cache/huggingface/datasets/sciq/default/0.1.0/50e5c6e3795b55463819d399ec417bfd4c3c621105e00295ddb5f3633d708493. Subsequent calls will reuse this data.
|
9 |
+
Downloading and preparing dataset winogrande/winogrande_xl to /home/laura/.cache/huggingface/datasets/winogrande/winogrande_xl/1.1.0/a826c3d3506aefe0e9e9390dcb53271070536586bab95849876b2c1743df56e2...
|
10 |
+
Dataset winogrande downloaded and prepared to /home/laura/.cache/huggingface/datasets/winogrande/winogrande_xl/1.1.0/a826c3d3506aefe0e9e9390dcb53271070536586bab95849876b2c1743df56e2. Subsequent calls will reuse this data.
|
11 |
+
bootstrapping for stddev: perplexity
|
12 |
+
{
|
13 |
+
"results": {
|
14 |
+
"arc_challenge": {
|
15 |
+
"acc,none": 0.21843003412969283,
|
16 |
+
"acc_stderr,none": 0.012074291605700959,
|
17 |
+
"acc_norm,none": 0.2645051194539249,
|
18 |
+
"acc_norm_stderr,none": 0.012889272949313368
|
19 |
+
},
|
20 |
+
"arc_easy": {
|
21 |
+
"acc,none": 0.54503367003367,
|
22 |
+
"acc_stderr,none": 0.010218084454602589,
|
23 |
+
"acc_norm,none": 0.5370370370370371,
|
24 |
+
"acc_norm_stderr,none": 0.010231597249131058
|
25 |
+
},
|
26 |
+
"boolq": {
|
27 |
+
"acc,none": 0.4871559633027523,
|
28 |
+
"acc_stderr,none": 0.008742169169427067
|
29 |
+
},
|
30 |
+
"hellaswag": {
|
31 |
+
"acc,none": 0.33827922724556864,
|
32 |
+
"acc_stderr,none": 0.004721571443354456,
|
33 |
+
"acc_norm,none": 0.40818562039434375,
|
34 |
+
"acc_norm_stderr,none": 0.004904933500255884
|
35 |
+
},
|
36 |
+
"lambada_openai": {
|
37 |
+
"perplexity,none": 14.485555582236119,
|
38 |
+
"perplexity_stderr,none": 0.4358013409476018,
|
39 |
+
"acc,none": 0.4422666407917718,
|
40 |
+
"acc_stderr,none": 0.006919384666875831
|
41 |
+
},
|
42 |
+
"openbookqa": {
|
43 |
+
"acc,none": 0.188,
|
44 |
+
"acc_stderr,none": 0.01749067888034625,
|
45 |
+
"acc_norm,none": 0.28,
|
46 |
+
"acc_norm_stderr,none": 0.020099950647503237
|
47 |
+
},
|
48 |
+
"piqa": {
|
49 |
+
"acc,none": 0.6806311207834603,
|
50 |
+
"acc_stderr,none": 0.010877964076613737,
|
51 |
+
"acc_norm,none": 0.6692056583242655,
|
52 |
+
"acc_norm_stderr,none": 0.010977520584714429
|
53 |
+
},
|
54 |
+
"sciq": {
|
55 |
+
"acc,none": 0.892,
|
56 |
+
"acc_stderr,none": 0.009820001651345682,
|
57 |
+
"acc_norm,none": 0.887,
|
58 |
+
"acc_norm_stderr,none": 0.01001655286669685
|
59 |
+
},
|
60 |
+
"wikitext": {
|
61 |
+
"word_perplexity,none": 34.50450469911897,
|
62 |
+
"byte_perplexity,none": 1.7927778872125213,
|
63 |
+
"bits_per_byte,none": 0.842196759334895
|
64 |
+
},
|
65 |
+
"winogrande": {
|
66 |
+
"acc,none": 0.5335438042620363,
|
67 |
+
"acc_stderr,none": 0.014020826677598103
|
68 |
+
}
|
69 |
+
},
|
70 |
+
"configs": {
|
71 |
+
"arc_challenge": {
|
72 |
+
"task": "arc_challenge",
|
73 |
+
"group": [
|
74 |
+
"ai2_arc",
|
75 |
+
"multiple_choice"
|
76 |
+
],
|
77 |
+
"dataset_path": "ai2_arc",
|
78 |
+
"dataset_name": "ARC-Challenge",
|
79 |
+
"training_split": "train",
|
80 |
+
"validation_split": "validation",
|
81 |
+
"test_split": "test",
|
82 |
+
"doc_to_text": "Question: {{question}}\nAnswer:",
|
83 |
+
"doc_to_target": "{{choices.label.index(answerKey)}}",
|
84 |
+
"doc_to_choice": "{{choices.text}}",
|
85 |
+
"description": "",
|
86 |
+
"target_delimiter": " ",
|
87 |
+
"fewshot_delimiter": "\n\n",
|
88 |
+
"num_fewshot": 5,
|
89 |
+
"metric_list": [
|
90 |
+
{
|
91 |
+
"metric": "acc",
|
92 |
+
"aggregation": "mean",
|
93 |
+
"higher_is_better": true
|
94 |
+
},
|
95 |
+
{
|
96 |
+
"metric": "acc_norm",
|
97 |
+
"aggregation": "mean",
|
98 |
+
"higher_is_better": true
|
99 |
+
}
|
100 |
+
],
|
101 |
+
"output_type": "multiple_choice",
|
102 |
+
"repeats": 1,
|
103 |
+
"should_decontaminate": true,
|
104 |
+
"doc_to_decontamination_query": "Question: {{question}}\nAnswer:"
|
105 |
+
},
|
106 |
+
"arc_easy": {
|
107 |
+
"task": "arc_easy",
|
108 |
+
"group": [
|
109 |
+
"ai2_arc",
|
110 |
+
"multiple_choice"
|
111 |
+
],
|
112 |
+
"dataset_path": "ai2_arc",
|
113 |
+
"dataset_name": "ARC-Easy",
|
114 |
+
"training_split": "train",
|
115 |
+
"validation_split": "validation",
|
116 |
+
"test_split": "test",
|
117 |
+
"doc_to_text": "Question: {{question}}\nAnswer:",
|
118 |
+
"doc_to_target": "{{choices.label.index(answerKey)}}",
|
119 |
+
"doc_to_choice": "{{choices.text}}",
|
120 |
+
"description": "",
|
121 |
+
"target_delimiter": " ",
|
122 |
+
"fewshot_delimiter": "\n\n",
|
123 |
+
"num_fewshot": 5,
|
124 |
+
"metric_list": [
|
125 |
+
{
|
126 |
+
"metric": "acc",
|
127 |
+
"aggregation": "mean",
|
128 |
+
"higher_is_better": true
|
129 |
+
},
|
130 |
+
{
|
131 |
+
"metric": "acc_norm",
|
132 |
+
"aggregation": "mean",
|
133 |
+
"higher_is_better": true
|
134 |
+
}
|
135 |
+
],
|
136 |
+
"output_type": "multiple_choice",
|
137 |
+
"repeats": 1,
|
138 |
+
"should_decontaminate": true,
|
139 |
+
"doc_to_decontamination_query": "Question: {{question}}\nAnswer:"
|
140 |
+
},
|
141 |
+
"boolq": {
|
142 |
+
"task": "boolq",
|
143 |
+
"group": [
|
144 |
+
"super-glue-lm-eval-v1"
|
145 |
+
],
|
146 |
+
"dataset_path": "super_glue",
|
147 |
+
"dataset_name": "boolq",
|
148 |
+
"training_split": "train",
|
149 |
+
"validation_split": "validation",
|
150 |
+
"doc_to_text": "{{passage}}\nQuestion: {{question}}?\nAnswer:",
|
151 |
+
"doc_to_target": "label",
|
152 |
+
"doc_to_choice": [
|
153 |
+
"no",
|
154 |
+
"yes"
|
155 |
+
],
|
156 |
+
"description": "",
|
157 |
+
"target_delimiter": " ",
|
158 |
+
"fewshot_delimiter": "\n\n",
|
159 |
+
"num_fewshot": 5,
|
160 |
+
"metric_list": [
|
161 |
+
{
|
162 |
+
"metric": "acc"
|
163 |
+
}
|
164 |
+
],
|
165 |
+
"output_type": "multiple_choice",
|
166 |
+
"repeats": 1,
|
167 |
+
"should_decontaminate": true,
|
168 |
+
"doc_to_decontamination_query": "passage"
|
169 |
+
},
|
170 |
+
"hellaswag": {
|
171 |
+
"task": "hellaswag",
|
172 |
+
"group": [
|
173 |
+
"multiple_choice"
|
174 |
+
],
|
175 |
+
"dataset_path": "hellaswag",
|
176 |
+
"training_split": "train",
|
177 |
+
"validation_split": "validation",
|
178 |
+
"doc_to_text": "{% set text = activity_label ~ ': ' ~ ctx_a ~ ' ' ~ ctx_b.capitalize() %}{{text|trim|replace(' [title]', '. ')|regex_replace('\\[.*?\\]', '')|replace(' ', ' ')}}",
|
179 |
+
"doc_to_target": "{{label}}",
|
180 |
+
"doc_to_choice": "{{endings|map('trim')|map('replace', ' [title]', '. ')|map('regex_replace', '\\[.*?\\]', '')|map('replace', ' ', ' ')|list}}",
|
181 |
+
"description": "",
|
182 |
+
"target_delimiter": " ",
|
183 |
+
"fewshot_delimiter": "\n\n",
|
184 |
+
"num_fewshot": 5,
|
185 |
+
"metric_list": [
|
186 |
+
{
|
187 |
+
"metric": "acc",
|
188 |
+
"aggregation": "mean",
|
189 |
+
"higher_is_better": true
|
190 |
+
},
|
191 |
+
{
|
192 |
+
"metric": "acc_norm",
|
193 |
+
"aggregation": "mean",
|
194 |
+
"higher_is_better": true
|
195 |
+
}
|
196 |
+
],
|
197 |
+
"output_type": "multiple_choice",
|
198 |
+
"repeats": 1,
|
199 |
+
"should_decontaminate": false
|
200 |
+
},
|
201 |
+
"lambada_openai": {
|
202 |
+
"task": "lambada_openai",
|
203 |
+
"group": [
|
204 |
+
"lambada",
|
205 |
+
"loglikelihood",
|
206 |
+
"perplexity"
|
207 |
+
],
|
208 |
+
"dataset_path": "EleutherAI/lambada_openai",
|
209 |
+
"dataset_name": "default",
|
210 |
+
"test_split": "test",
|
211 |
+
"template_aliases": "",
|
212 |
+
"doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
|
213 |
+
"doc_to_target": "{{' '+text.split(' ')[-1]}}",
|
214 |
+
"description": "",
|
215 |
+
"target_delimiter": " ",
|
216 |
+
"fewshot_delimiter": "\n\n",
|
217 |
+
"num_fewshot": 5,
|
218 |
+
"metric_list": [
|
219 |
+
{
|
220 |
+
"metric": "perplexity",
|
221 |
+
"aggregation": "perplexity",
|
222 |
+
"higher_is_better": false
|
223 |
+
},
|
224 |
+
{
|
225 |
+
"metric": "acc",
|
226 |
+
"aggregation": "mean",
|
227 |
+
"higher_is_better": true
|
228 |
+
}
|
229 |
+
],
|
230 |
+
"output_type": "loglikelihood",
|
231 |
+
"repeats": 1,
|
232 |
+
"should_decontaminate": true,
|
233 |
+
"doc_to_decontamination_query": "{{text}}"
|
234 |
+
},
|
235 |
+
"openbookqa": {
|
236 |
+
"task": "openbookqa",
|
237 |
+
"group": [
|
238 |
+
"multiple_choice"
|
239 |
+
],
|
240 |
+
"dataset_path": "openbookqa",
|
241 |
+
"dataset_name": "main",
|
242 |
+
"training_split": "train",
|
243 |
+
"validation_split": "validation",
|
244 |
+
"test_split": "test",
|
245 |
+
"doc_to_text": "question_stem",
|
246 |
+
"doc_to_target": "{{choices.label.index(answerKey.lstrip())}}",
|
247 |
+
"doc_to_choice": "{{choices.text}}",
|
248 |
+
"description": "",
|
249 |
+
"target_delimiter": " ",
|
250 |
+
"fewshot_delimiter": "\n\n",
|
251 |
+
"num_fewshot": 5,
|
252 |
+
"metric_list": [
|
253 |
+
{
|
254 |
+
"metric": "acc",
|
255 |
+
"aggregation": "mean",
|
256 |
+
"higher_is_better": true
|
257 |
+
},
|
258 |
+
{
|
259 |
+
"metric": "acc_norm",
|
260 |
+
"aggregation": "mean",
|
261 |
+
"higher_is_better": true
|
262 |
+
}
|
263 |
+
],
|
264 |
+
"output_type": "multiple_choice",
|
265 |
+
"repeats": 1,
|
266 |
+
"should_decontaminate": true,
|
267 |
+
"doc_to_decontamination_query": "question_stem"
|
268 |
+
},
|
269 |
+
"piqa": {
|
270 |
+
"task": "piqa",
|
271 |
+
"group": [
|
272 |
+
"multiple_choice"
|
273 |
+
],
|
274 |
+
"dataset_path": "piqa",
|
275 |
+
"training_split": "train",
|
276 |
+
"validation_split": "validation",
|
277 |
+
"doc_to_text": "Question: {{goal}}\nAnswer:",
|
278 |
+
"doc_to_target": "label",
|
279 |
+
"doc_to_choice": "{{[sol1, sol2]}}",
|
280 |
+
"description": "",
|
281 |
+
"target_delimiter": " ",
|
282 |
+
"fewshot_delimiter": "\n\n",
|
283 |
+
"num_fewshot": 5,
|
284 |
+
"metric_list": [
|
285 |
+
{
|
286 |
+
"metric": "acc",
|
287 |
+
"aggregation": "mean",
|
288 |
+
"higher_is_better": true
|
289 |
+
},
|
290 |
+
{
|
291 |
+
"metric": "acc_norm",
|
292 |
+
"aggregation": "mean",
|
293 |
+
"higher_is_better": true
|
294 |
+
}
|
295 |
+
],
|
296 |
+
"output_type": "multiple_choice",
|
297 |
+
"repeats": 1,
|
298 |
+
"should_decontaminate": true,
|
299 |
+
"doc_to_decontamination_query": "goal"
|
300 |
+
},
|
301 |
+
"sciq": {
|
302 |
+
"task": "sciq",
|
303 |
+
"group": [
|
304 |
+
"multiple_choice"
|
305 |
+
],
|
306 |
+
"dataset_path": "sciq",
|
307 |
+
"training_split": "train",
|
308 |
+
"validation_split": "validation",
|
309 |
+
"test_split": "test",
|
310 |
+
"doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
|
311 |
+
"doc_to_target": 3,
|
312 |
+
"doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
|
313 |
+
"description": "",
|
314 |
+
"target_delimiter": " ",
|
315 |
+
"fewshot_delimiter": "\n\n",
|
316 |
+
"num_fewshot": 5,
|
317 |
+
"metric_list": [
|
318 |
+
{
|
319 |
+
"metric": "acc",
|
320 |
+
"aggregation": "mean",
|
321 |
+
"higher_is_better": true
|
322 |
+
},
|
323 |
+
{
|
324 |
+
"metric": "acc_norm",
|
325 |
+
"aggregation": "mean",
|
326 |
+
"higher_is_better": true
|
327 |
+
}
|
328 |
+
],
|
329 |
+
"output_type": "multiple_choice",
|
330 |
+
"repeats": 1,
|
331 |
+
"should_decontaminate": true,
|
332 |
+
"doc_to_decontamination_query": "{{support}} {{question}}"
|
333 |
+
},
|
334 |
+
"wikitext": {
|
335 |
+
"task": "wikitext",
|
336 |
+
"group": [
|
337 |
+
"perplexity",
|
338 |
+
"loglikelihood_rolling"
|
339 |
+
],
|
340 |
+
"dataset_path": "EleutherAI/wikitext_document_level",
|
341 |
+
"dataset_name": "wikitext-2-raw-v1",
|
342 |
+
"training_split": "train",
|
343 |
+
"validation_split": "validation",
|
344 |
+
"test_split": "test",
|
345 |
+
"template_aliases": "",
|
346 |
+
"doc_to_text": "",
|
347 |
+
"doc_to_target": "<function wikitext_detokenizer at 0x7efb86530040>",
|
348 |
+
"description": "",
|
349 |
+
"target_delimiter": " ",
|
350 |
+
"fewshot_delimiter": "\n\n",
|
351 |
+
"num_fewshot": 5,
|
352 |
+
"metric_list": [
|
353 |
+
{
|
354 |
+
"metric": "word_perplexity"
|
355 |
+
},
|
356 |
+
{
|
357 |
+
"metric": "byte_perplexity"
|
358 |
+
},
|
359 |
+
{
|
360 |
+
"metric": "bits_per_byte"
|
361 |
+
}
|
362 |
+
],
|
363 |
+
"output_type": "loglikelihood_rolling",
|
364 |
+
"repeats": 1,
|
365 |
+
"should_decontaminate": true,
|
366 |
+
"doc_to_decontamination_query": "{{page}}"
|
367 |
+
},
|
368 |
+
"winogrande": {
|
369 |
+
"task": "winogrande",
|
370 |
+
"dataset_path": "winogrande",
|
371 |
+
"dataset_name": "winogrande_xl",
|
372 |
+
"training_split": "train",
|
373 |
+
"validation_split": "validation",
|
374 |
+
"doc_to_text": "<function doc_to_text at 0x7efb86502ef0>",
|
375 |
+
"doc_to_target": "<function doc_to_target at 0x7efb86503370>",
|
376 |
+
"doc_to_choice": "<function doc_to_choice at 0x7efb865035b0>",
|
377 |
+
"description": "",
|
378 |
+
"target_delimiter": " ",
|
379 |
+
"fewshot_delimiter": "\n\n",
|
380 |
+
"num_fewshot": 5,
|
381 |
+
"metric_list": [
|
382 |
+
{
|
383 |
+
"metric": "acc",
|
384 |
+
"aggregation": "mean",
|
385 |
+
"higher_is_better": true
|
386 |
+
}
|
387 |
+
],
|
388 |
+
"output_type": "multiple_choice",
|
389 |
+
"repeats": 1,
|
390 |
+
"should_decontaminate": false
|
391 |
+
}
|
392 |
+
},
|
393 |
+
"versions": {
|
394 |
+
"arc_challenge": "Yaml",
|
395 |
+
"arc_easy": "Yaml",
|
396 |
+
"boolq": "Yaml",
|
397 |
+
"hellaswag": "Yaml",
|
398 |
+
"lambada_openai": "Yaml",
|
399 |
+
"openbookqa": "Yaml",
|
400 |
+
"piqa": "Yaml",
|
401 |
+
"sciq": "Yaml",
|
402 |
+
"wikitext": "Yaml",
|
403 |
+
"winogrande": "Yaml"
|
404 |
+
},
|
405 |
+
"config": {
|
406 |
+
"model": "hf",
|
407 |
+
"model_args": "pretrained=EleutherAI/pythia-410m",
|
408 |
+
"num_fewshot": 5,
|
409 |
+
"batch_size": 16,
|
410 |
+
"batch_sizes": [],
|
411 |
+
"device": "cuda:0",
|
412 |
+
"use_cache": null,
|
413 |
+
"limit": null,
|
414 |
+
"bootstrap_iters": 100000
|
415 |
+
},
|
416 |
+
"git_hash": "4e44f0a"
|
417 |
+
}
|
418 |
+
hf (pretrained=EleutherAI/pythia-410m), limit: None, num_fewshot: 5, batch_size: 16
|
419 |
+
| Task |Version|Filter| Metric | Value | |Stderr|
|
420 |
+
|--------------|-------|------|---------------|------:|---|-----:|
|
421 |
+
|arc_challenge |Yaml |none |acc | 0.2184|± |0.0121|
|
422 |
+
| | |none |acc_norm | 0.2645|± |0.0129|
|
423 |
+
|arc_easy |Yaml |none |acc | 0.5450|± |0.0102|
|
424 |
+
| | |none |acc_norm | 0.5370|± |0.0102|
|
425 |
+
|boolq |Yaml |none |acc | 0.4872|± |0.0087|
|
426 |
+
|hellaswag |Yaml |none |acc | 0.3383|± |0.0047|
|
427 |
+
| | |none |acc_norm | 0.4082|± |0.0049|
|
428 |
+
|lambada_openai|Yaml |none |perplexity |14.4856|± |0.4358|
|
429 |
+
| | |none |acc | 0.4423|± |0.0069|
|
430 |
+
|openbookqa |Yaml |none |acc | 0.1880|± |0.0175|
|
431 |
+
| | |none |acc_norm | 0.2800|± |0.0201|
|
432 |
+
|piqa |Yaml |none |acc | 0.6806|± |0.0109|
|
433 |
+
| | |none |acc_norm | 0.6692|± |0.0110|
|
434 |
+
|sciq |Yaml |none |acc | 0.8920|± |0.0098|
|
435 |
+
| | |none |acc_norm | 0.8870|± |0.0100|
|
436 |
+
|wikitext |Yaml |none |word_perplexity|34.5045| | |
|
437 |
+
| | |none |byte_perplexity| 1.7928| | |
|
438 |
+
| | |none |bits_per_byte | 0.8422| | |
|
439 |
+
|winogrande |Yaml |none |acc | 0.5335|± |0.0140|
|
440 |
+
|