Muennighoff
commited on
Commit
•
f4d13b5
1
Parent(s):
bfd53df
Add evaluation
Browse files
README.md
CHANGED
@@ -155,6 +155,1601 @@ widget:
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A: Let's think step by step.
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example_title: Mathematical reasoning
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group: English
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|
158 |
---
|
159 |
|
160 |
<img src="https://s3.amazonaws.com/moonup/production/uploads/1657124309515-5f17f0a0925b9863e28ad517.png" alt="BigScience Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
|
@@ -545,6 +2140,157 @@ Model may:
|
|
545 |
<details>
|
546 |
<summary>Click to expand</summary>
|
547 |
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|
548 |
## Metrics
|
549 |
*This section describes the different ways performance is calculated and why.*
|
550 |
|
@@ -675,4 +2421,4 @@ Initial prompting experiments using interim checkpoints: https://huggingface.co/
|
|
675 |
# Model Card Authors
|
676 |
*Ordered roughly chronologically and by amount of time spent.*
|
677 |
|
678 |
-
Margaret Mitchell, Giada Pistilli, Yacine Jernite, Ezinwanne Ozoani, Marissa Gerchick, Nazneen Rajani, Sasha Luccioni, Irene Solaiman, Maraim Masoud, Somaieh Nikpoor, Carlos Muñoz Ferrandis, Stas Bekman, Christopher Akiki, Danish Contractor, David Lansky, Angelina McMillan-Major, Tristan Thrush, Suzana Ilić, Gérard Dupont, Shayne Longpre, Manan Dey, Stella Biderman, Douwe Kiela, Emi Baylor, Teven Le Scao, Aaron Gokaslan, Julien Launay
|
|
|
155 |
A: Let's think step by step.
|
156 |
example_title: Mathematical reasoning
|
157 |
group: English
|
158 |
+
model-index:
|
159 |
+
- name: bloom
|
160 |
+
results:
|
161 |
+
- task:
|
162 |
+
type: text-generation
|
163 |
+
name: text generation
|
164 |
+
dataset:
|
165 |
+
name: arc_challenge
|
166 |
+
type: arc_challenge
|
167 |
+
metrics:
|
168 |
+
- name: acc
|
169 |
+
type: acc
|
170 |
+
value: 0.4112627986348123
|
171 |
+
verified: false
|
172 |
+
- task:
|
173 |
+
type: text-generation
|
174 |
+
name: text generation
|
175 |
+
dataset:
|
176 |
+
name: arc_easy
|
177 |
+
type: arc_easy
|
178 |
+
metrics:
|
179 |
+
- name: acc
|
180 |
+
type: acc
|
181 |
+
value: 0.726010101010101
|
182 |
+
verified: false
|
183 |
+
- task:
|
184 |
+
type: text-generation
|
185 |
+
name: text generation
|
186 |
+
dataset:
|
187 |
+
name: axb
|
188 |
+
type: axb
|
189 |
+
metrics:
|
190 |
+
- name: acc
|
191 |
+
type: acc
|
192 |
+
value: 0.5751811594202898
|
193 |
+
verified: false
|
194 |
+
- task:
|
195 |
+
type: text-generation
|
196 |
+
name: text generation
|
197 |
+
dataset:
|
198 |
+
name: axg
|
199 |
+
type: axg
|
200 |
+
metrics:
|
201 |
+
- name: acc
|
202 |
+
type: acc
|
203 |
+
value: 0.5252808988764045
|
204 |
+
verified: false
|
205 |
+
- task:
|
206 |
+
type: text-generation
|
207 |
+
name: text generation
|
208 |
+
dataset:
|
209 |
+
name: boolq
|
210 |
+
type: boolq
|
211 |
+
metrics:
|
212 |
+
- name: acc
|
213 |
+
type: acc
|
214 |
+
value: 0.6345565749235474
|
215 |
+
verified: false
|
216 |
+
- task:
|
217 |
+
type: text-generation
|
218 |
+
name: text generation
|
219 |
+
dataset:
|
220 |
+
name: cb
|
221 |
+
type: cb
|
222 |
+
metrics:
|
223 |
+
- name: acc
|
224 |
+
type: acc
|
225 |
+
value: 0.3392857142857143
|
226 |
+
verified: false
|
227 |
+
- task:
|
228 |
+
type: text-generation
|
229 |
+
name: text generation
|
230 |
+
dataset:
|
231 |
+
name: cola
|
232 |
+
type: cola
|
233 |
+
metrics:
|
234 |
+
- name: acc
|
235 |
+
type: acc
|
236 |
+
value: 0.39022051773729627
|
237 |
+
verified: false
|
238 |
+
- task:
|
239 |
+
type: text-generation
|
240 |
+
name: text generation
|
241 |
+
dataset:
|
242 |
+
name: copa
|
243 |
+
type: copa
|
244 |
+
metrics:
|
245 |
+
- name: acc
|
246 |
+
type: acc
|
247 |
+
value: 0.56
|
248 |
+
verified: false
|
249 |
+
- task:
|
250 |
+
type: text-generation
|
251 |
+
name: text generation
|
252 |
+
dataset:
|
253 |
+
name: crows_pairs_english
|
254 |
+
type: crows_pairs_english
|
255 |
+
metrics:
|
256 |
+
- name: acc
|
257 |
+
type: acc
|
258 |
+
value: 0.5
|
259 |
+
verified: false
|
260 |
+
- task:
|
261 |
+
type: text-generation
|
262 |
+
name: text generation
|
263 |
+
dataset:
|
264 |
+
name: crows_pairs_french
|
265 |
+
type: crows_pairs_french
|
266 |
+
metrics:
|
267 |
+
- name: acc
|
268 |
+
type: acc
|
269 |
+
value: 0.505664877757901
|
270 |
+
verified: false
|
271 |
+
- task:
|
272 |
+
type: text-generation
|
273 |
+
name: text generation
|
274 |
+
dataset:
|
275 |
+
name: diabla
|
276 |
+
type: diabla
|
277 |
+
metrics:
|
278 |
+
- name: acc
|
279 |
+
type: acc
|
280 |
+
value: 0.2947981906750174
|
281 |
+
verified: false
|
282 |
+
- task:
|
283 |
+
type: text-generation
|
284 |
+
name: text generation
|
285 |
+
dataset:
|
286 |
+
name: gsarti/flores_101_afr
|
287 |
+
type: gsarti/flores_101_afr
|
288 |
+
metrics:
|
289 |
+
- name: byte_perplexity
|
290 |
+
type: byte_perplexity
|
291 |
+
value: 4.25431550058444
|
292 |
+
verified: false
|
293 |
+
- task:
|
294 |
+
type: text-generation
|
295 |
+
name: text generation
|
296 |
+
dataset:
|
297 |
+
name: gsarti/flores_101_amh
|
298 |
+
type: gsarti/flores_101_amh
|
299 |
+
metrics:
|
300 |
+
- name: byte_perplexity
|
301 |
+
type: byte_perplexity
|
302 |
+
value: 3.716877477347089
|
303 |
+
verified: false
|
304 |
+
- task:
|
305 |
+
type: text-generation
|
306 |
+
name: text generation
|
307 |
+
dataset:
|
308 |
+
name: gsarti/flores_101_ara
|
309 |
+
type: gsarti/flores_101_ara
|
310 |
+
metrics:
|
311 |
+
- name: byte_perplexity
|
312 |
+
type: byte_perplexity
|
313 |
+
value: 1.7049030137120964
|
314 |
+
verified: false
|
315 |
+
- task:
|
316 |
+
type: text-generation
|
317 |
+
name: text generation
|
318 |
+
dataset:
|
319 |
+
name: gsarti/flores_101_asm
|
320 |
+
type: gsarti/flores_101_asm
|
321 |
+
metrics:
|
322 |
+
- name: byte_perplexity
|
323 |
+
type: byte_perplexity
|
324 |
+
value: 6.576581380404954
|
325 |
+
verified: false
|
326 |
+
- task:
|
327 |
+
type: text-generation
|
328 |
+
name: text generation
|
329 |
+
dataset:
|
330 |
+
name: gsarti/flores_101_ast
|
331 |
+
type: gsarti/flores_101_ast
|
332 |
+
metrics:
|
333 |
+
- name: byte_perplexity
|
334 |
+
type: byte_perplexity
|
335 |
+
value: 2.8562364775797944
|
336 |
+
verified: false
|
337 |
+
- task:
|
338 |
+
type: text-generation
|
339 |
+
name: text generation
|
340 |
+
dataset:
|
341 |
+
name: gsarti/flores_101_azj
|
342 |
+
type: gsarti/flores_101_azj
|
343 |
+
metrics:
|
344 |
+
- name: byte_perplexity
|
345 |
+
type: byte_perplexity
|
346 |
+
value: 4.80721528624391
|
347 |
+
verified: false
|
348 |
+
- task:
|
349 |
+
type: text-generation
|
350 |
+
name: text generation
|
351 |
+
dataset:
|
352 |
+
name: gsarti/flores_101_bel
|
353 |
+
type: gsarti/flores_101_bel
|
354 |
+
metrics:
|
355 |
+
- name: byte_perplexity
|
356 |
+
type: byte_perplexity
|
357 |
+
value: 2.7312177406635065
|
358 |
+
verified: false
|
359 |
+
- task:
|
360 |
+
type: text-generation
|
361 |
+
name: text generation
|
362 |
+
dataset:
|
363 |
+
name: gsarti/flores_101_ben
|
364 |
+
type: gsarti/flores_101_ben
|
365 |
+
metrics:
|
366 |
+
- name: byte_perplexity
|
367 |
+
type: byte_perplexity
|
368 |
+
value: 5.993409478990023
|
369 |
+
verified: false
|
370 |
+
- task:
|
371 |
+
type: text-generation
|
372 |
+
name: text generation
|
373 |
+
dataset:
|
374 |
+
name: gsarti/flores_101_bos
|
375 |
+
type: gsarti/flores_101_bos
|
376 |
+
metrics:
|
377 |
+
- name: byte_perplexity
|
378 |
+
type: byte_perplexity
|
379 |
+
value: 3.5936169095529493
|
380 |
+
verified: false
|
381 |
+
- task:
|
382 |
+
type: text-generation
|
383 |
+
name: text generation
|
384 |
+
dataset:
|
385 |
+
name: gsarti/flores_101_bul
|
386 |
+
type: gsarti/flores_101_bul
|
387 |
+
metrics:
|
388 |
+
- name: byte_perplexity
|
389 |
+
type: byte_perplexity
|
390 |
+
value: 2.159035321398085
|
391 |
+
verified: false
|
392 |
+
- task:
|
393 |
+
type: text-generation
|
394 |
+
name: text generation
|
395 |
+
dataset:
|
396 |
+
name: gsarti/flores_101_cat
|
397 |
+
type: gsarti/flores_101_cat
|
398 |
+
metrics:
|
399 |
+
- name: byte_perplexity
|
400 |
+
type: byte_perplexity
|
401 |
+
value: 2.167873680006659
|
402 |
+
verified: false
|
403 |
+
- task:
|
404 |
+
type: text-generation
|
405 |
+
name: text generation
|
406 |
+
dataset:
|
407 |
+
name: gsarti/flores_101_ceb
|
408 |
+
type: gsarti/flores_101_ceb
|
409 |
+
metrics:
|
410 |
+
- name: byte_perplexity
|
411 |
+
type: byte_perplexity
|
412 |
+
value: 5.286975089885673
|
413 |
+
verified: false
|
414 |
+
- task:
|
415 |
+
type: text-generation
|
416 |
+
name: text generation
|
417 |
+
dataset:
|
418 |
+
name: gsarti/flores_101_ces
|
419 |
+
type: gsarti/flores_101_ces
|
420 |
+
metrics:
|
421 |
+
- name: byte_perplexity
|
422 |
+
type: byte_perplexity
|
423 |
+
value: 3.4516208322236017
|
424 |
+
verified: false
|
425 |
+
- task:
|
426 |
+
type: text-generation
|
427 |
+
name: text generation
|
428 |
+
dataset:
|
429 |
+
name: gsarti/flores_101_ckb
|
430 |
+
type: gsarti/flores_101_ckb
|
431 |
+
metrics:
|
432 |
+
- name: byte_perplexity
|
433 |
+
type: byte_perplexity
|
434 |
+
value: 3.7051034724765612
|
435 |
+
verified: false
|
436 |
+
- task:
|
437 |
+
type: text-generation
|
438 |
+
name: text generation
|
439 |
+
dataset:
|
440 |
+
name: gsarti/flores_101_cym
|
441 |
+
type: gsarti/flores_101_cym
|
442 |
+
metrics:
|
443 |
+
- name: byte_perplexity
|
444 |
+
type: byte_perplexity
|
445 |
+
value: 7.0889312398688125
|
446 |
+
verified: false
|
447 |
+
- task:
|
448 |
+
type: text-generation
|
449 |
+
name: text generation
|
450 |
+
dataset:
|
451 |
+
name: gsarti/flores_101_dan
|
452 |
+
type: gsarti/flores_101_dan
|
453 |
+
metrics:
|
454 |
+
- name: byte_perplexity
|
455 |
+
type: byte_perplexity
|
456 |
+
value: 3.4300748208111838
|
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dataset:
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name: gsarti/flores_101_uzb
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name: text generation
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dataset:
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name: gsarti/flores_101_vie
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type: text-generation
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name: text generation
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dataset:
|
1342 |
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name: gsarti/flores_101_wol
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type: gsarti/flores_101_wol
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name: text generation
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dataset:
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dataset:
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name: text generation
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dataset:
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dataset:
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name: text generation
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dataset:
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type: text-generation
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name: text generation
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dataset:
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name: headqa
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type: headqa
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type: text-generation
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name: text generation
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dataset:
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name: hellaswag
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type: hellaswag
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name: text generation
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dataset:
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name: lambada_mt_de
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type: text-generation
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name: text generation
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dataset:
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name: lambada_mt_en
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type: text-generation
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name: text generation
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dataset:
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name: lambada_mt_es
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type: lambada_mt_es
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type: text-generation
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name: text generation
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dataset:
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name: lambada_mt_it
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name: text generation
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dataset:
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name: logiqa
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type: logiqa
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dataset:
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name: mathqa
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type: mathqa
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type: text-generation
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name: text generation
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dataset:
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name: mc_taco
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type: mc_taco
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type: text-generation
|
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name: text generation
|
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dataset:
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name: mnli
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type: mnli
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metrics:
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type: text-generation
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name: text generation
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dataset:
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name: mnli_mismatched
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type: mnli_mismatched
|
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metrics:
|
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type: acc
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value: 0.3545565500406835
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type: text-generation
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name: text generation
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1528 |
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dataset:
|
1529 |
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name: mrpc
|
1530 |
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type: mrpc
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1531 |
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metrics:
|
1532 |
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type: acc
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value: 0.3872549019607843
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type: text-generation
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name: text generation
|
1539 |
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dataset:
|
1540 |
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name: multirc
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type: multirc
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metrics:
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|
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name: text generation
|
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dataset:
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1551 |
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name: openbookqa
|
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type: openbookqa
|
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metrics:
|
1554 |
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type: acc
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value: 0.312
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type: text-generation
|
1560 |
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name: text generation
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dataset:
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name: piqa
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type: piqa
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metrics:
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value: 0.7812840043525572
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name: text generation
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dataset:
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name: prost
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type: prost
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value: 0.2977156276686593
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type: text-generation
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name: text generation
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dataset:
|
1584 |
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name: pubmedqa
|
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type: pubmedqa
|
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metrics:
|
1587 |
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type: acc
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value: 0.741
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type: text-generation
|
1593 |
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name: text generation
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1594 |
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dataset:
|
1595 |
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name: qnli
|
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type: qnli
|
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metrics:
|
1598 |
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type: acc
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value: 0.5172981878088962
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- task:
|
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type: text-generation
|
1604 |
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name: text generation
|
1605 |
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dataset:
|
1606 |
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name: qqp
|
1607 |
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type: qqp
|
1608 |
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metrics:
|
1609 |
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type: acc
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value: 0.5883007667573584
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type: text-generation
|
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name: text generation
|
1616 |
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dataset:
|
1617 |
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name: race
|
1618 |
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type: race
|
1619 |
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metrics:
|
1620 |
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type: acc
|
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value: 0.39043062200956935
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|
1625 |
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type: text-generation
|
1626 |
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name: text generation
|
1627 |
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dataset:
|
1628 |
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name: rte
|
1629 |
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type: rte
|
1630 |
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metrics:
|
1631 |
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type: acc
|
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value: 0.5198555956678701
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type: text-generation
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name: text generation
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dataset:
|
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name: sciq
|
1640 |
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type: sciq
|
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metrics:
|
1642 |
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type: acc
|
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value: 0.936
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|
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type: text-generation
|
1648 |
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name: text generation
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1649 |
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dataset:
|
1650 |
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name: sst
|
1651 |
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type: sst
|
1652 |
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metrics:
|
1653 |
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type: acc
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1655 |
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value: 0.6043577981651376
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|
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type: text-generation
|
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name: text generation
|
1660 |
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dataset:
|
1661 |
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name: triviaqa
|
1662 |
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type: triviaqa
|
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metrics:
|
1664 |
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value: 0.18332891363917617
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|
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name: text generation
|
1671 |
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dataset:
|
1672 |
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name: tydiqa_primary
|
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type: tydiqa_primary
|
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metrics:
|
1675 |
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|
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name: text generation
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dataset:
|
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name: webqs
|
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type: webqs
|
1685 |
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metrics:
|
1686 |
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|
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name: text generation
|
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dataset:
|
1694 |
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name: wic
|
1695 |
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type: wic
|
1696 |
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metrics:
|
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type: text-generation
|
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name: text generation
|
1704 |
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dataset:
|
1705 |
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name: winogrande
|
1706 |
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type: winogrande
|
1707 |
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metrics:
|
1708 |
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type: acc
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value: 0.7095501183898973
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|
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type: text-generation
|
1714 |
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name: text generation
|
1715 |
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dataset:
|
1716 |
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name: wnli
|
1717 |
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type: wnli
|
1718 |
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metrics:
|
1719 |
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|
1720 |
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type: acc
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1721 |
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value: 0.5704225352112676
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1722 |
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|
1723 |
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- task:
|
1724 |
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type: text-generation
|
1725 |
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name: text generation
|
1726 |
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dataset:
|
1727 |
+
name: wsc
|
1728 |
+
type: wsc
|
1729 |
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metrics:
|
1730 |
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type: acc
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1732 |
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value: 0.5192307692307693
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- task:
|
1735 |
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type: text-generation
|
1736 |
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name: text generation
|
1737 |
+
dataset:
|
1738 |
+
name: humaneval
|
1739 |
+
type: humaneval
|
1740 |
+
metrics:
|
1741 |
+
- name: pass@1
|
1742 |
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type: pass@1
|
1743 |
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value: 0.15524390243902436
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1744 |
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verified: false
|
1745 |
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|
1746 |
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type: pass@10
|
1747 |
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value: 0.3220367632383857
|
1748 |
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verified: false
|
1749 |
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|
1750 |
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type: pass@100
|
1751 |
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value: 0.5545431515723145
|
1752 |
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verified: false
|
1753 |
---
|
1754 |
|
1755 |
<img src="https://s3.amazonaws.com/moonup/production/uploads/1657124309515-5f17f0a0925b9863e28ad517.png" alt="BigScience Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
|
|
|
2140 |
<details>
|
2141 |
<summary>Click to expand</summary>
|
2142 |
|
2143 |
+
See this repository for JSON files: https://github.com/bigscience-workshop/evaluation-results
|
2144 |
+
|
2145 |
+
| Task | Language | Metric | BLOOM-176B | OPT-175B* |
|
2146 |
+
|:--------|:-----------------|:------------------------|-------------:|------------:|
|
2147 |
+
| arc_challenge | eng | acc ↑ | 0.411 | 0.412 |
|
2148 |
+
| arc_easy | eng | acc ↑ | 0.726 | 0.751 |
|
2149 |
+
| axb (Median of 10 prompts) | eng | acc ↑ | 0.575 | 0.532 |
|
2150 |
+
| axg (Median of 10 prompts) | eng | acc ↑ | 0.525 | 0.548 |
|
2151 |
+
| boolq (Median of 11 prompts) | eng | acc ↑ | 0.635 | 0.622 |
|
2152 |
+
| cb (Median of 15 prompts) | eng | acc ↑ | 0.339 | 0.411 |
|
2153 |
+
| cola (Median of 5 prompts) | eng | acc ↑ | 0.39 | 0.444 |
|
2154 |
+
| copa (Median of 9 prompts) | eng | acc ↑ | 0.56 | 0.55 |
|
2155 |
+
| crows_pairs_english (Median of 6 prompts) | eng | acc ↑ | 0.5 | 0.502 |
|
2156 |
+
| crows_pairs_french (Median of 7 prompts) | eng | acc ↑ | 0.506 | 0.499 |
|
2157 |
+
| diabla (Median of 2 prompts) | eng | acc ↑ | 0.295 | 0.289 |
|
2158 |
+
| gsarti/flores_101_afr | afr | byte_perplexity ↓ | 4.254 | 3.381 |
|
2159 |
+
| gsarti/flores_101_amh | amh | byte_perplexity ↓ | 3.717 | 3.87 |
|
2160 |
+
| gsarti/flores_101_ara | ara | byte_perplexity ↓ | 1.705 | 2.42 |
|
2161 |
+
| gsarti/flores_101_asm | asm | byte_perplexity ↓ | 6.577 | 3.028 |
|
2162 |
+
| gsarti/flores_101_ast | ast | byte_perplexity ↓ | 2.856 | 4.737 |
|
2163 |
+
| gsarti/flores_101_azj | azj | byte_perplexity ↓ | 4.807 | 4.767 |
|
2164 |
+
| gsarti/flores_101_bel | bel | byte_perplexity ↓ | 2.731 | 2.557 |
|
2165 |
+
| gsarti/flores_101_ben | ben | byte_perplexity ↓ | 5.993 | 2.243 |
|
2166 |
+
| gsarti/flores_101_bos | bos | byte_perplexity ↓ | 3.594 | 2.668 |
|
2167 |
+
| gsarti/flores_101_bul | bul | byte_perplexity ↓ | 2.159 | 2.099 |
|
2168 |
+
| gsarti/flores_101_cat | cat | byte_perplexity ↓ | 2.168 | 2.837 |
|
2169 |
+
| gsarti/flores_101_ceb | ceb | byte_perplexity ↓ | 5.287 | 3.636 |
|
2170 |
+
| gsarti/flores_101_ces | ces | byte_perplexity ↓ | 3.452 | 2.749 |
|
2171 |
+
| gsarti/flores_101_ckb | ckb | byte_perplexity ↓ | 3.705 | 4.688 |
|
2172 |
+
| gsarti/flores_101_cym | cym | byte_perplexity ↓ | 7.089 | 5.075 |
|
2173 |
+
| gsarti/flores_101_dan | dan | byte_perplexity ↓ | 3.43 | 2.492 |
|
2174 |
+
| gsarti/flores_101_deu | deu | byte_perplexity ↓ | 2.338 | 2.099 |
|
2175 |
+
| gsarti/flores_101_ell | ell | byte_perplexity ↓ | 1.96 | 1.811 |
|
2176 |
+
| gsarti/flores_101_eng | eng | byte_perplexity ↓ | 1.882 | 1.9 |
|
2177 |
+
| gsarti/flores_101_est | est | byte_perplexity ↓ | 5.774 | 3.533 |
|
2178 |
+
| gsarti/flores_101_fas | fas | byte_perplexity ↓ | 2.431 | 2.444 |
|
2179 |
+
| gsarti/flores_101_fin | fin | byte_perplexity ↓ | 4.304 | 2.601 |
|
2180 |
+
| gsarti/flores_101_fra | fra | byte_perplexity ↓ | 1.937 | 1.984 |
|
2181 |
+
| gsarti/flores_101_ful | ful | byte_perplexity ↓ | 9.74 | 11.84 |
|
2182 |
+
| gsarti/flores_101_gle | gle | byte_perplexity ↓ | 6.035 | 3.914 |
|
2183 |
+
| gsarti/flores_101_glg | glg | byte_perplexity ↓ | 2.365 | 3.015 |
|
2184 |
+
| gsarti/flores_101_guj | guj | byte_perplexity ↓ | 5.707 | 2.438 |
|
2185 |
+
| gsarti/flores_101_hau | hau | byte_perplexity ↓ | 8.855 | 5.283 |
|
2186 |
+
| gsarti/flores_101_heb | heb | byte_perplexity ↓ | 2.921 | 2.903 |
|
2187 |
+
| gsarti/flores_101_hin | hin | byte_perplexity ↓ | 5.452 | 1.86 |
|
2188 |
+
| gsarti/flores_101_hrv | hrv | byte_perplexity ↓ | 3.706 | 2.715 |
|
2189 |
+
| gsarti/flores_101_hun | hun | byte_perplexity ↓ | 4.059 | 2.865 |
|
2190 |
+
| gsarti/flores_101_hye | hye | byte_perplexity ↓ | 3.127 | 3.411 |
|
2191 |
+
| gsarti/flores_101_ibo | ibo | byte_perplexity ↓ | 3.95 | 8.008 |
|
2192 |
+
| gsarti/flores_101_ind | ind | byte_perplexity ↓ | 1.976 | 2.632 |
|
2193 |
+
| gsarti/flores_101_isl | isl | byte_perplexity ↓ | 5.501 | 4.701 |
|
2194 |
+
| gsarti/flores_101_ita | ita | byte_perplexity ↓ | 2.314 | 2.104 |
|
2195 |
+
| gsarti/flores_101_jav | jav | byte_perplexity ↓ | 4.942 | 8.16 |
|
2196 |
+
| gsarti/flores_101_jpn | jpn | byte_perplexity ↓ | 2.259 | 2.198 |
|
2197 |
+
| gsarti/flores_101_kam | kam | byte_perplexity ↓ | 9.743 | 10.981 |
|
2198 |
+
| gsarti/flores_101_kan | kan | byte_perplexity ↓ | 6.234 | 2.373 |
|
2199 |
+
| gsarti/flores_101_kat | kat | byte_perplexity ↓ | 2.051 | 2.466 |
|
2200 |
+
| gsarti/flores_101_kaz | kaz | byte_perplexity ↓ | 3.039 | 4.376 |
|
2201 |
+
| gsarti/flores_101_kea | kea | byte_perplexity ↓ | 7.147 | 9.632 |
|
2202 |
+
| gsarti/flores_101_khm | khm | byte_perplexity ↓ | 3.367 | 2.646 |
|
2203 |
+
| gsarti/flores_101_kir | kir | byte_perplexity ↓ | 3.241 | 4.522 |
|
2204 |
+
| gsarti/flores_101_kor | kor | byte_perplexity ↓ | 2.902 | 3.376 |
|
2205 |
+
| gsarti/flores_101_lao | lao | byte_perplexity ↓ | 2.331 | 3.106 |
|
2206 |
+
| gsarti/flores_101_lav | lav | byte_perplexity ↓ | 5.224 | 4.811 |
|
2207 |
+
| gsarti/flores_101_lin | lin | byte_perplexity ↓ | 4.847 | 8.871 |
|
2208 |
+
| gsarti/flores_101_lit | lit | byte_perplexity ↓ | 4.543 | 5.183 |
|
2209 |
+
| gsarti/flores_101_ltz | ltz | byte_perplexity ↓ | 5.591 | 7.158 |
|
2210 |
+
| gsarti/flores_101_lug | lug | byte_perplexity ↓ | 5.43 | 7.399 |
|
2211 |
+
| gsarti/flores_101_luo | luo | byte_perplexity ↓ | 12.031 | 11.951 |
|
2212 |
+
| gsarti/flores_101_mal | mal | byte_perplexity ↓ | 4.794 | 2.054 |
|
2213 |
+
| gsarti/flores_101_mar | mar | byte_perplexity ↓ | 6.857 | 2.274 |
|
2214 |
+
| gsarti/flores_101_mkd | mkd | byte_perplexity ↓ | 2.335 | 2.538 |
|
2215 |
+
| gsarti/flores_101_mlt | mlt | byte_perplexity ↓ | 9.041 | 5.996 |
|
2216 |
+
| gsarti/flores_101_mon | mon | byte_perplexity ↓ | 3.095 | 4.519 |
|
2217 |
+
| gsarti/flores_101_mri | mri | byte_perplexity ↓ | 5.266 | 4.438 |
|
2218 |
+
| gsarti/flores_101_msa | msa | byte_perplexity ↓ | 2.222 | 2.935 |
|
2219 |
+
| gsarti/flores_101_mya | mya | byte_perplexity ↓ | 2.523 | 2.413 |
|
2220 |
+
| gsarti/flores_101_nld | nld | byte_perplexity ↓ | 2.799 | 2.293 |
|
2221 |
+
| gsarti/flores_101_nob | nob | byte_perplexity ↓ | 3.629 | 2.593 |
|
2222 |
+
| gsarti/flores_101_npi | npi | byte_perplexity ↓ | 6.666 | 2.499 |
|
2223 |
+
| gsarti/flores_101_nso | nso | byte_perplexity ↓ | 5.015 | 8.485 |
|
2224 |
+
| gsarti/flores_101_nya | nya | byte_perplexity ↓ | 4.938 | 7.548 |
|
2225 |
+
| gsarti/flores_101_oci | oci | byte_perplexity ↓ | 3.607 | 4.936 |
|
2226 |
+
| gsarti/flores_101_orm | orm | byte_perplexity ↓ | 11.316 | 7.145 |
|
2227 |
+
| gsarti/flores_101_ory | ory | byte_perplexity ↓ | 5.982 | 2.668 |
|
2228 |
+
| gsarti/flores_101_pan | pan | byte_perplexity ↓ | 4.772 | 2.782 |
|
2229 |
+
| gsarti/flores_101_pol | pol | byte_perplexity ↓ | 3.012 | 2.432 |
|
2230 |
+
| gsarti/flores_101_por | por | byte_perplexity ↓ | 1.841 | 2.178 |
|
2231 |
+
| gsarti/flores_101_pus | pus | byte_perplexity ↓ | 4.624 | 4.785 |
|
2232 |
+
| gsarti/flores_101_ron | ron | byte_perplexity ↓ | 3.05 | 2.197 |
|
2233 |
+
| gsarti/flores_101_rus | rus | byte_perplexity ↓ | 1.708 | 1.689 |
|
2234 |
+
| gsarti/flores_101_slk | slk | byte_perplexity ↓ | 4.038 | 3.419 |
|
2235 |
+
| gsarti/flores_101_slv | slv | byte_perplexity ↓ | 4.141 | 3.582 |
|
2236 |
+
| gsarti/flores_101_sna | sna | byte_perplexity ↓ | 4.711 | 5.588 |
|
2237 |
+
| gsarti/flores_101_snd | snd | byte_perplexity ↓ | 4.206 | 5.667 |
|
2238 |
+
| gsarti/flores_101_som | som | byte_perplexity ↓ | 9.154 | 4.788 |
|
2239 |
+
| gsarti/flores_101_spa | spa | byte_perplexity ↓ | 1.796 | 2.098 |
|
2240 |
+
| gsarti/flores_101_srp | srp | byte_perplexity ↓ | 2.241 | 2.688 |
|
2241 |
+
| gsarti/flores_101_swe | swe | byte_perplexity ↓ | 3.345 | 2.468 |
|
2242 |
+
| gsarti/flores_101_swh | swh | byte_perplexity ↓ | 2.684 | 4.473 |
|
2243 |
+
| gsarti/flores_101_tam | tam | byte_perplexity ↓ | 5.165 | 2.024 |
|
2244 |
+
| gsarti/flores_101_tel | tel | byte_perplexity ↓ | 6.81 | 2.407 |
|
2245 |
+
| gsarti/flores_101_tgk | tgk | byte_perplexity ↓ | 3.785 | 4.899 |
|
2246 |
+
| gsarti/flores_101_tgl | tgl | byte_perplexity ↓ | 3.75 | 2.738 |
|
2247 |
+
| gsarti/flores_101_tha | tha | byte_perplexity ↓ | 2.104 | 2.035 |
|
2248 |
+
| gsarti/flores_101_tur | tur | byte_perplexity ↓ | 3.318 | 2.622 |
|
2249 |
+
| gsarti/flores_101_ukr | ukr | byte_perplexity ↓ | 2.089 | 1.93 |
|
2250 |
+
| gsarti/flores_101_umb | umb | byte_perplexity ↓ | 11.766 | 11.64 |
|
2251 |
+
| gsarti/flores_101_urd | urd | byte_perplexity ↓ | 1.779 | 2.982 |
|
2252 |
+
| gsarti/flores_101_uzb | uzb | byte_perplexity ↓ | 8.5 | 13.209 |
|
2253 |
+
| gsarti/flores_101_vie | vie | byte_perplexity ↓ | 1.659 | 2.229 |
|
2254 |
+
| gsarti/flores_101_wol | wol | byte_perplexity ↓ | 6.142 | 13.945 |
|
2255 |
+
| gsarti/flores_101_xho | xho | byte_perplexity ↓ | 4.69 | 8.42 |
|
2256 |
+
| gsarti/flores_101_yor | yor | byte_perplexity ↓ | 4.361 | 7.636 |
|
2257 |
+
| gsarti/flores_101_zho_simpl | zho_simpl | byte_perplexity ↓ | 2.118 | 5.113 |
|
2258 |
+
| gsarti/flores_101_zho_trad | zho_trad | byte_perplexity ↓ | 2.274 | 5.67 |
|
2259 |
+
| gsarti/flores_101_zul | zul | byte_perplexity ↓ | 6.017 | 7.341 |
|
2260 |
+
| headqa | esp | acc ↑ | 0.346 | 0.244 |
|
2261 |
+
| hellaswag | eng | acc ↑ | 0.535 | 0.592 |
|
2262 |
+
| lambada_mt_de | deu | acc ↑ | 0.329 | 0.358 |
|
2263 |
+
| lambada_mt_en | eng | acc ↑ | 0.672 | 0.747 |
|
2264 |
+
| lambada_mt_es | esp | acc ↑ | 0.476 | 0.397 |
|
2265 |
+
| lambada_mt_it | ita | acc ↑ | 0.406 | 0.409 |
|
2266 |
+
| logiqa | eng | acc ↑ | 0.235 | 0.244 |
|
2267 |
+
| mathqa | eng | acc ↑ | 0.277 | 0.268 |
|
2268 |
+
| mc_taco | eng | em ↑ | 0.131 | 0.124 |
|
2269 |
+
| mnli (Median of 15 prompts) | eng | acc ↑ | 0.355 | 0.36 |
|
2270 |
+
| mnli_mismatched (Median of 15 prompts) | eng | acc ↑ | 0.355 | 0.36 |
|
2271 |
+
| mrpc | eng | acc ↑ | 0.387 | 0.446 |
|
2272 |
+
| multirc (Median of 11 prompts) | eng | acc ↑ | 0.571 | 0.599 |
|
2273 |
+
| openbookqa | eng | acc ↑ | 0.312 | 0.322 |
|
2274 |
+
| piqa | eng | acc ↑ | 0.781 | 0.791 |
|
2275 |
+
| prost | eng | acc ↑ | 0.298 | 0.299 |
|
2276 |
+
| pubmedqa | eng | acc ↑ | 0.741 | 0.709 |
|
2277 |
+
| qnli | eng | acc ↑ | 0.517 | 0.554 |
|
2278 |
+
| qqp (Median of 7 prompts) | eng | acc ↑ | 0.588 | 0.395 |
|
2279 |
+
| race | eng | acc ↑ | 0.39 | 0.402 |
|
2280 |
+
| rte (Median of 6 prompts) | eng | acc ↑ | 0.52 | 0.495 |
|
2281 |
+
| sciq | eng | acc ↑ | 0.936 | 0.948 |
|
2282 |
+
| sst (Median of 6 prompts) | eng | acc ↑ | 0.604 | 0.647 |
|
2283 |
+
| triviaqa | eng | acc ↑ | 0.183 | 0.342 |
|
2284 |
+
| tydiqa_primary (Median of 16 prompts) | eng | acc ↑ | 0.281 | 0.148 |
|
2285 |
+
| webqs | eng | acc ↑ | 0.062 | 0.159 |
|
2286 |
+
| wic (Median of 11 prompts) | eng | acc ↑ | 0.506 | 0.498 |
|
2287 |
+
| winogrande | eng | acc ↑ | 0.71 | 0.736 |
|
2288 |
+
| wnli (Median of 6 prompts) | eng | acc ↑ | 0.57 | 0.563 |
|
2289 |
+
| wsc (Median of 11 prompts) | eng | acc ↑ | 0.519 | 0.413 |
|
2290 |
+
| humaneval | python | pass@1 | 0.155 | 0.0 |
|
2291 |
+
| humaneval | python | pass@10 | 0.322 | 0.0 |
|
2292 |
+
| humaneval | python | pass@100 | 0.555 | 0.003 |
|
2293 |
+
|
2294 |
## Metrics
|
2295 |
*This section describes the different ways performance is calculated and why.*
|
2296 |
|
|
|
2421 |
# Model Card Authors
|
2422 |
*Ordered roughly chronologically and by amount of time spent.*
|
2423 |
|
2424 |
+
Margaret Mitchell, Giada Pistilli, Yacine Jernite, Ezinwanne Ozoani, Marissa Gerchick, Nazneen Rajani, Sasha Luccioni, Irene Solaiman, Maraim Masoud, Somaieh Nikpoor, Carlos Muñoz Ferrandis, Stas Bekman, Christopher Akiki, Danish Contractor, David Lansky, Angelina McMillan-Major, Tristan Thrush, Suzana Ilić, Gérard Dupont, Shayne Longpre, Manan Dey, Stella Biderman, Douwe Kiela, Emi Baylor, Teven Le Scao, Aaron Gokaslan, Julien Launay, Niklas Muennighoff
|