Initial commit
Browse files- .gitattributes +1 -0
- README.md +2833 -0
- benchmark_results.txt +227 -0
- benchmark_translations.zip +0 -0
- config.json +41 -0
- generation_config.json +16 -0
- model.safetensors +3 -0
- pytorch_model.bin +3 -0
- source.spm +3 -0
- special_tokens_map.json +1 -0
- target.spm +3 -0
- tokenizer_config.json +1 -0
- vocab.json +0 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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+
*.spm filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
@@ -0,0 +1,2833 @@
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|
1 |
+
---
|
2 |
+
library_name: transformers
|
3 |
+
language:
|
4 |
+
- af
|
5 |
+
- ang
|
6 |
+
- bar
|
7 |
+
- bi
|
8 |
+
- bzj
|
9 |
+
- de
|
10 |
+
- djk
|
11 |
+
- drt
|
12 |
+
- en
|
13 |
+
- enm
|
14 |
+
- es
|
15 |
+
- fr
|
16 |
+
- frr
|
17 |
+
- fy
|
18 |
+
- gos
|
19 |
+
- gsw
|
20 |
+
- hrx
|
21 |
+
- hwc
|
22 |
+
- icr
|
23 |
+
- jam
|
24 |
+
- kri
|
25 |
+
- ksh
|
26 |
+
- lb
|
27 |
+
- li
|
28 |
+
- nds
|
29 |
+
- nl
|
30 |
+
- ofs
|
31 |
+
- pcm
|
32 |
+
- pdc
|
33 |
+
- pfl
|
34 |
+
- pih
|
35 |
+
- pis
|
36 |
+
- pt
|
37 |
+
- rop
|
38 |
+
- sco
|
39 |
+
- srm
|
40 |
+
- srn
|
41 |
+
- stq
|
42 |
+
- swg
|
43 |
+
- tcs
|
44 |
+
- tpi
|
45 |
+
- vls
|
46 |
+
- wae
|
47 |
+
- yi
|
48 |
+
- zea
|
49 |
+
|
50 |
+
tags:
|
51 |
+
- translation
|
52 |
+
- opus-mt-tc-bible
|
53 |
+
|
54 |
+
license: apache-2.0
|
55 |
+
model-index:
|
56 |
+
- name: opus-mt-tc-bible-big-deu_eng_fra_por_spa-gmw
|
57 |
+
results:
|
58 |
+
- task:
|
59 |
+
name: Translation deu-afr
|
60 |
+
type: translation
|
61 |
+
args: deu-afr
|
62 |
+
dataset:
|
63 |
+
name: flores200-devtest
|
64 |
+
type: flores200-devtest
|
65 |
+
args: deu-afr
|
66 |
+
metrics:
|
67 |
+
- name: BLEU
|
68 |
+
type: bleu
|
69 |
+
value: 26.2
|
70 |
+
- name: chr-F
|
71 |
+
type: chrf
|
72 |
+
value: 0.57725
|
73 |
+
- task:
|
74 |
+
name: Translation deu-eng
|
75 |
+
type: translation
|
76 |
+
args: deu-eng
|
77 |
+
dataset:
|
78 |
+
name: flores200-devtest
|
79 |
+
type: flores200-devtest
|
80 |
+
args: deu-eng
|
81 |
+
metrics:
|
82 |
+
- name: BLEU
|
83 |
+
type: bleu
|
84 |
+
value: 41.5
|
85 |
+
- name: chr-F
|
86 |
+
type: chrf
|
87 |
+
value: 0.67043
|
88 |
+
- task:
|
89 |
+
name: Translation deu-ltz
|
90 |
+
type: translation
|
91 |
+
args: deu-ltz
|
92 |
+
dataset:
|
93 |
+
name: flores200-devtest
|
94 |
+
type: flores200-devtest
|
95 |
+
args: deu-ltz
|
96 |
+
metrics:
|
97 |
+
- name: BLEU
|
98 |
+
type: bleu
|
99 |
+
value: 21.6
|
100 |
+
- name: chr-F
|
101 |
+
type: chrf
|
102 |
+
value: 0.54626
|
103 |
+
- task:
|
104 |
+
name: Translation deu-nld
|
105 |
+
type: translation
|
106 |
+
args: deu-nld
|
107 |
+
dataset:
|
108 |
+
name: flores200-devtest
|
109 |
+
type: flores200-devtest
|
110 |
+
args: deu-nld
|
111 |
+
metrics:
|
112 |
+
- name: BLEU
|
113 |
+
type: bleu
|
114 |
+
value: 24.0
|
115 |
+
- name: chr-F
|
116 |
+
type: chrf
|
117 |
+
value: 0.55679
|
118 |
+
- task:
|
119 |
+
name: Translation deu-tpi
|
120 |
+
type: translation
|
121 |
+
args: deu-tpi
|
122 |
+
dataset:
|
123 |
+
name: flores200-devtest
|
124 |
+
type: flores200-devtest
|
125 |
+
args: deu-tpi
|
126 |
+
metrics:
|
127 |
+
- name: BLEU
|
128 |
+
type: bleu
|
129 |
+
value: 13.5
|
130 |
+
- name: chr-F
|
131 |
+
type: chrf
|
132 |
+
value: 0.39146
|
133 |
+
- task:
|
134 |
+
name: Translation eng-afr
|
135 |
+
type: translation
|
136 |
+
args: eng-afr
|
137 |
+
dataset:
|
138 |
+
name: flores200-devtest
|
139 |
+
type: flores200-devtest
|
140 |
+
args: eng-afr
|
141 |
+
metrics:
|
142 |
+
- name: BLEU
|
143 |
+
type: bleu
|
144 |
+
value: 40.2
|
145 |
+
- name: chr-F
|
146 |
+
type: chrf
|
147 |
+
value: 0.68115
|
148 |
+
- task:
|
149 |
+
name: Translation eng-deu
|
150 |
+
type: translation
|
151 |
+
args: eng-deu
|
152 |
+
dataset:
|
153 |
+
name: flores200-devtest
|
154 |
+
type: flores200-devtest
|
155 |
+
args: eng-deu
|
156 |
+
metrics:
|
157 |
+
- name: BLEU
|
158 |
+
type: bleu
|
159 |
+
value: 37.4
|
160 |
+
- name: chr-F
|
161 |
+
type: chrf
|
162 |
+
value: 0.64561
|
163 |
+
- task:
|
164 |
+
name: Translation eng-ltz
|
165 |
+
type: translation
|
166 |
+
args: eng-ltz
|
167 |
+
dataset:
|
168 |
+
name: flores200-devtest
|
169 |
+
type: flores200-devtest
|
170 |
+
args: eng-ltz
|
171 |
+
metrics:
|
172 |
+
- name: BLEU
|
173 |
+
type: bleu
|
174 |
+
value: 22.0
|
175 |
+
- name: chr-F
|
176 |
+
type: chrf
|
177 |
+
value: 0.54932
|
178 |
+
- task:
|
179 |
+
name: Translation eng-nld
|
180 |
+
type: translation
|
181 |
+
args: eng-nld
|
182 |
+
dataset:
|
183 |
+
name: flores200-devtest
|
184 |
+
type: flores200-devtest
|
185 |
+
args: eng-nld
|
186 |
+
metrics:
|
187 |
+
- name: BLEU
|
188 |
+
type: bleu
|
189 |
+
value: 26.8
|
190 |
+
- name: chr-F
|
191 |
+
type: chrf
|
192 |
+
value: 0.58124
|
193 |
+
- task:
|
194 |
+
name: Translation eng-tpi
|
195 |
+
type: translation
|
196 |
+
args: eng-tpi
|
197 |
+
dataset:
|
198 |
+
name: flores200-devtest
|
199 |
+
type: flores200-devtest
|
200 |
+
args: eng-tpi
|
201 |
+
metrics:
|
202 |
+
- name: BLEU
|
203 |
+
type: bleu
|
204 |
+
value: 15.9
|
205 |
+
- name: chr-F
|
206 |
+
type: chrf
|
207 |
+
value: 0.40338
|
208 |
+
- task:
|
209 |
+
name: Translation fra-afr
|
210 |
+
type: translation
|
211 |
+
args: fra-afr
|
212 |
+
dataset:
|
213 |
+
name: flores200-devtest
|
214 |
+
type: flores200-devtest
|
215 |
+
args: fra-afr
|
216 |
+
metrics:
|
217 |
+
- name: BLEU
|
218 |
+
type: bleu
|
219 |
+
value: 26.4
|
220 |
+
- name: chr-F
|
221 |
+
type: chrf
|
222 |
+
value: 0.57320
|
223 |
+
- task:
|
224 |
+
name: Translation fra-deu
|
225 |
+
type: translation
|
226 |
+
args: fra-deu
|
227 |
+
dataset:
|
228 |
+
name: flores200-devtest
|
229 |
+
type: flores200-devtest
|
230 |
+
args: fra-deu
|
231 |
+
metrics:
|
232 |
+
- name: BLEU
|
233 |
+
type: bleu
|
234 |
+
value: 29.5
|
235 |
+
- name: chr-F
|
236 |
+
type: chrf
|
237 |
+
value: 0.58974
|
238 |
+
- task:
|
239 |
+
name: Translation fra-eng
|
240 |
+
type: translation
|
241 |
+
args: fra-eng
|
242 |
+
dataset:
|
243 |
+
name: flores200-devtest
|
244 |
+
type: flores200-devtest
|
245 |
+
args: fra-eng
|
246 |
+
metrics:
|
247 |
+
- name: BLEU
|
248 |
+
type: bleu
|
249 |
+
value: 43.7
|
250 |
+
- name: chr-F
|
251 |
+
type: chrf
|
252 |
+
value: 0.68106
|
253 |
+
- task:
|
254 |
+
name: Translation fra-ltz
|
255 |
+
type: translation
|
256 |
+
args: fra-ltz
|
257 |
+
dataset:
|
258 |
+
name: flores200-devtest
|
259 |
+
type: flores200-devtest
|
260 |
+
args: fra-ltz
|
261 |
+
metrics:
|
262 |
+
- name: BLEU
|
263 |
+
type: bleu
|
264 |
+
value: 17.8
|
265 |
+
- name: chr-F
|
266 |
+
type: chrf
|
267 |
+
value: 0.49618
|
268 |
+
- task:
|
269 |
+
name: Translation fra-nld
|
270 |
+
type: translation
|
271 |
+
args: fra-nld
|
272 |
+
dataset:
|
273 |
+
name: flores200-devtest
|
274 |
+
type: flores200-devtest
|
275 |
+
args: fra-nld
|
276 |
+
metrics:
|
277 |
+
- name: BLEU
|
278 |
+
type: bleu
|
279 |
+
value: 22.5
|
280 |
+
- name: chr-F
|
281 |
+
type: chrf
|
282 |
+
value: 0.54623
|
283 |
+
- task:
|
284 |
+
name: Translation fra-tpi
|
285 |
+
type: translation
|
286 |
+
args: fra-tpi
|
287 |
+
dataset:
|
288 |
+
name: flores200-devtest
|
289 |
+
type: flores200-devtest
|
290 |
+
args: fra-tpi
|
291 |
+
metrics:
|
292 |
+
- name: BLEU
|
293 |
+
type: bleu
|
294 |
+
value: 13.7
|
295 |
+
- name: chr-F
|
296 |
+
type: chrf
|
297 |
+
value: 0.39334
|
298 |
+
- task:
|
299 |
+
name: Translation por-afr
|
300 |
+
type: translation
|
301 |
+
args: por-afr
|
302 |
+
dataset:
|
303 |
+
name: flores200-devtest
|
304 |
+
type: flores200-devtest
|
305 |
+
args: por-afr
|
306 |
+
metrics:
|
307 |
+
- name: BLEU
|
308 |
+
type: bleu
|
309 |
+
value: 27.6
|
310 |
+
- name: chr-F
|
311 |
+
type: chrf
|
312 |
+
value: 0.58408
|
313 |
+
- task:
|
314 |
+
name: Translation por-deu
|
315 |
+
type: translation
|
316 |
+
args: por-deu
|
317 |
+
dataset:
|
318 |
+
name: flores200-devtest
|
319 |
+
type: flores200-devtest
|
320 |
+
args: por-deu
|
321 |
+
metrics:
|
322 |
+
- name: BLEU
|
323 |
+
type: bleu
|
324 |
+
value: 30.4
|
325 |
+
- name: chr-F
|
326 |
+
type: chrf
|
327 |
+
value: 0.59121
|
328 |
+
- task:
|
329 |
+
name: Translation por-eng
|
330 |
+
type: translation
|
331 |
+
args: por-eng
|
332 |
+
dataset:
|
333 |
+
name: flores200-devtest
|
334 |
+
type: flores200-devtest
|
335 |
+
args: por-eng
|
336 |
+
metrics:
|
337 |
+
- name: BLEU
|
338 |
+
type: bleu
|
339 |
+
value: 48.3
|
340 |
+
- name: chr-F
|
341 |
+
type: chrf
|
342 |
+
value: 0.71418
|
343 |
+
- task:
|
344 |
+
name: Translation por-ltz
|
345 |
+
type: translation
|
346 |
+
args: por-ltz
|
347 |
+
dataset:
|
348 |
+
name: flores200-devtest
|
349 |
+
type: flores200-devtest
|
350 |
+
args: por-ltz
|
351 |
+
metrics:
|
352 |
+
- name: BLEU
|
353 |
+
type: bleu
|
354 |
+
value: 12.3
|
355 |
+
- name: chr-F
|
356 |
+
type: chrf
|
357 |
+
value: 0.39073
|
358 |
+
- task:
|
359 |
+
name: Translation por-nld
|
360 |
+
type: translation
|
361 |
+
args: por-nld
|
362 |
+
dataset:
|
363 |
+
name: flores200-devtest
|
364 |
+
type: flores200-devtest
|
365 |
+
args: por-nld
|
366 |
+
metrics:
|
367 |
+
- name: BLEU
|
368 |
+
type: bleu
|
369 |
+
value: 22.9
|
370 |
+
- name: chr-F
|
371 |
+
type: chrf
|
372 |
+
value: 0.54828
|
373 |
+
- task:
|
374 |
+
name: Translation por-tpi
|
375 |
+
type: translation
|
376 |
+
args: por-tpi
|
377 |
+
dataset:
|
378 |
+
name: flores200-devtest
|
379 |
+
type: flores200-devtest
|
380 |
+
args: por-tpi
|
381 |
+
metrics:
|
382 |
+
- name: BLEU
|
383 |
+
type: bleu
|
384 |
+
value: 13.7
|
385 |
+
- name: chr-F
|
386 |
+
type: chrf
|
387 |
+
value: 0.38929
|
388 |
+
- task:
|
389 |
+
name: Translation spa-afr
|
390 |
+
type: translation
|
391 |
+
args: spa-afr
|
392 |
+
dataset:
|
393 |
+
name: flores200-devtest
|
394 |
+
type: flores200-devtest
|
395 |
+
args: spa-afr
|
396 |
+
metrics:
|
397 |
+
- name: BLEU
|
398 |
+
type: bleu
|
399 |
+
value: 17.8
|
400 |
+
- name: chr-F
|
401 |
+
type: chrf
|
402 |
+
value: 0.51514
|
403 |
+
- task:
|
404 |
+
name: Translation spa-deu
|
405 |
+
type: translation
|
406 |
+
args: spa-deu
|
407 |
+
dataset:
|
408 |
+
name: flores200-devtest
|
409 |
+
type: flores200-devtest
|
410 |
+
args: spa-deu
|
411 |
+
metrics:
|
412 |
+
- name: BLEU
|
413 |
+
type: bleu
|
414 |
+
value: 21.4
|
415 |
+
- name: chr-F
|
416 |
+
type: chrf
|
417 |
+
value: 0.53603
|
418 |
+
- task:
|
419 |
+
name: Translation spa-eng
|
420 |
+
type: translation
|
421 |
+
args: spa-eng
|
422 |
+
dataset:
|
423 |
+
name: flores200-devtest
|
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425 |
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426 |
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427 |
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428 |
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429 |
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430 |
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431 |
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432 |
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434 |
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435 |
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436 |
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437 |
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438 |
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439 |
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440 |
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441 |
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442 |
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443 |
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445 |
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446 |
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447 |
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448 |
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449 |
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450 |
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451 |
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452 |
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dataset:
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453 |
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454 |
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455 |
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456 |
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457 |
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458 |
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459 |
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460 |
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461 |
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462 |
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463 |
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464 |
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465 |
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466 |
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args: deu-afr
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467 |
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dataset:
|
468 |
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469 |
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470 |
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471 |
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metrics:
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472 |
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473 |
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474 |
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475 |
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476 |
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477 |
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478 |
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479 |
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481 |
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482 |
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483 |
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484 |
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485 |
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486 |
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487 |
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488 |
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489 |
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490 |
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492 |
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493 |
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494 |
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496 |
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497 |
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498 |
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500 |
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501 |
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502 |
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503 |
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504 |
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505 |
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506 |
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507 |
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508 |
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509 |
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510 |
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511 |
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512 |
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513 |
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514 |
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515 |
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516 |
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517 |
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518 |
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519 |
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520 |
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521 |
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522 |
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523 |
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524 |
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525 |
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526 |
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527 |
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dataset:
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528 |
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529 |
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530 |
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531 |
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532 |
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533 |
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534 |
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535 |
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536 |
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537 |
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538 |
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539 |
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540 |
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541 |
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542 |
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543 |
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544 |
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545 |
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546 |
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547 |
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548 |
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549 |
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550 |
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551 |
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552 |
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553 |
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- task:
|
554 |
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555 |
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556 |
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args: fra-ltz
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557 |
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dataset:
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558 |
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559 |
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560 |
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561 |
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562 |
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563 |
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564 |
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565 |
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566 |
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567 |
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568 |
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569 |
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570 |
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571 |
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572 |
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573 |
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574 |
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575 |
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576 |
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577 |
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578 |
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579 |
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580 |
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581 |
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582 |
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583 |
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584 |
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585 |
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586 |
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587 |
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588 |
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589 |
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590 |
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591 |
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592 |
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593 |
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594 |
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595 |
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596 |
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597 |
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598 |
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599 |
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600 |
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601 |
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602 |
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603 |
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604 |
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605 |
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606 |
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607 |
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608 |
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609 |
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610 |
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611 |
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612 |
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613 |
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614 |
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615 |
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616 |
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617 |
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618 |
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619 |
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620 |
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621 |
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622 |
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623 |
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624 |
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625 |
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626 |
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627 |
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628 |
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629 |
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630 |
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631 |
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632 |
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633 |
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634 |
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635 |
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636 |
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637 |
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638 |
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639 |
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640 |
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641 |
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642 |
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643 |
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644 |
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645 |
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646 |
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647 |
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648 |
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649 |
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650 |
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651 |
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652 |
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653 |
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654 |
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655 |
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656 |
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657 |
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658 |
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659 |
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660 |
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661 |
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662 |
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663 |
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664 |
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665 |
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666 |
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667 |
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668 |
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669 |
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670 |
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671 |
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672 |
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673 |
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674 |
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675 |
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676 |
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677 |
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678 |
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679 |
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680 |
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681 |
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682 |
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683 |
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684 |
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685 |
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686 |
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687 |
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688 |
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689 |
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690 |
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691 |
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692 |
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693 |
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696 |
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700 |
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701 |
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702 |
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703 |
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704 |
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705 |
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706 |
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707 |
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708 |
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712 |
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713 |
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715 |
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716 |
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717 |
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718 |
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719 |
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720 |
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721 |
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722 |
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723 |
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725 |
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727 |
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728 |
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729 |
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730 |
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731 |
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732 |
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733 |
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734 |
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735 |
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736 |
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737 |
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738 |
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740 |
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742 |
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745 |
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747 |
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748 |
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749 |
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750 |
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751 |
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752 |
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753 |
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755 |
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756 |
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758 |
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760 |
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761 |
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762 |
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763 |
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764 |
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765 |
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767 |
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768 |
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771 |
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773 |
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775 |
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776 |
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778 |
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779 |
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780 |
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781 |
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782 |
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783 |
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787 |
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790 |
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793 |
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794 |
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795 |
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796 |
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797 |
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798 |
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800 |
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801 |
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803 |
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805 |
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806 |
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807 |
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808 |
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809 |
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810 |
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811 |
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812 |
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813 |
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815 |
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820 |
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821 |
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822 |
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823 |
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824 |
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828 |
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835 |
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838 |
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839 |
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842 |
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850 |
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853 |
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854 |
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857 |
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865 |
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869 |
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892 |
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894 |
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895 |
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896 |
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898 |
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|
899 |
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900 |
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|
901 |
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args: fra-eng
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902 |
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dataset:
|
903 |
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904 |
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args: fra-eng
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906 |
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907 |
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908 |
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909 |
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910 |
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911 |
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912 |
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|
914 |
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915 |
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|
916 |
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args: fra-eng
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917 |
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|
918 |
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920 |
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args: fra-eng
|
921 |
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929 |
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930 |
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932 |
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933 |
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951 |
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963 |
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978 |
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1000 |
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1001 |
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1002 |
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1004 |
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1008 |
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1011 |
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1019 |
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1022 |
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1023 |
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1024 |
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1034 |
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1038 |
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1045 |
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1052 |
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1053 |
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1057 |
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1072 |
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1080 |
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1100 |
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1101 |
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1102 |
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1109 |
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|
1113 |
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1115 |
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1116 |
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metrics:
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1117 |
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1120 |
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1124 |
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|
1128 |
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1130 |
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1133 |
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1139 |
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1147 |
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1150 |
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1158 |
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1177 |
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1184 |
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1188 |
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1198 |
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1199 |
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1202 |
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1203 |
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1206 |
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1207 |
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1208 |
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1214 |
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1220 |
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1221 |
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1223 |
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1237 |
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1243 |
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1244 |
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1247 |
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dataset:
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1248 |
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1250 |
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1251 |
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1252 |
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1255 |
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1259 |
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1263 |
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1265 |
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1267 |
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1270 |
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|
1278 |
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1304 |
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1308 |
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1334 |
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1338 |
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1683 |
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1694 |
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1754 |
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1769 |
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1783 |
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1784 |
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1795 |
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1799 |
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1802 |
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dataset:
|
1803 |
+
name: newstest2009
|
1804 |
+
type: wmt-2009-news
|
1805 |
+
args: fra-deu
|
1806 |
+
metrics:
|
1807 |
+
- name: BLEU
|
1808 |
+
type: bleu
|
1809 |
+
value: 22.9
|
1810 |
+
- name: chr-F
|
1811 |
+
type: chrf
|
1812 |
+
value: 0.52995
|
1813 |
+
- task:
|
1814 |
+
name: Translation fra-eng
|
1815 |
+
type: translation
|
1816 |
+
args: fra-eng
|
1817 |
+
dataset:
|
1818 |
+
name: newstest2009
|
1819 |
+
type: wmt-2009-news
|
1820 |
+
args: fra-eng
|
1821 |
+
metrics:
|
1822 |
+
- name: BLEU
|
1823 |
+
type: bleu
|
1824 |
+
value: 30.0
|
1825 |
+
- name: chr-F
|
1826 |
+
type: chrf
|
1827 |
+
value: 0.56663
|
1828 |
+
- task:
|
1829 |
+
name: Translation spa-deu
|
1830 |
+
type: translation
|
1831 |
+
args: spa-deu
|
1832 |
+
dataset:
|
1833 |
+
name: newstest2009
|
1834 |
+
type: wmt-2009-news
|
1835 |
+
args: spa-deu
|
1836 |
+
metrics:
|
1837 |
+
- name: BLEU
|
1838 |
+
type: bleu
|
1839 |
+
value: 22.1
|
1840 |
+
- name: chr-F
|
1841 |
+
type: chrf
|
1842 |
+
value: 0.52586
|
1843 |
+
- task:
|
1844 |
+
name: Translation spa-eng
|
1845 |
+
type: translation
|
1846 |
+
args: spa-eng
|
1847 |
+
dataset:
|
1848 |
+
name: newstest2009
|
1849 |
+
type: wmt-2009-news
|
1850 |
+
args: spa-eng
|
1851 |
+
metrics:
|
1852 |
+
- name: BLEU
|
1853 |
+
type: bleu
|
1854 |
+
value: 29.9
|
1855 |
+
- name: chr-F
|
1856 |
+
type: chrf
|
1857 |
+
value: 0.56756
|
1858 |
+
- task:
|
1859 |
+
name: Translation deu-eng
|
1860 |
+
type: translation
|
1861 |
+
args: deu-eng
|
1862 |
+
dataset:
|
1863 |
+
name: newstest2010
|
1864 |
+
type: wmt-2010-news
|
1865 |
+
args: deu-eng
|
1866 |
+
metrics:
|
1867 |
+
- name: BLEU
|
1868 |
+
type: bleu
|
1869 |
+
value: 30.4
|
1870 |
+
- name: chr-F
|
1871 |
+
type: chrf
|
1872 |
+
value: 0.58365
|
1873 |
+
- task:
|
1874 |
+
name: Translation eng-deu
|
1875 |
+
type: translation
|
1876 |
+
args: eng-deu
|
1877 |
+
dataset:
|
1878 |
+
name: newstest2010
|
1879 |
+
type: wmt-2010-news
|
1880 |
+
args: eng-deu
|
1881 |
+
metrics:
|
1882 |
+
- name: BLEU
|
1883 |
+
type: bleu
|
1884 |
+
value: 25.7
|
1885 |
+
- name: chr-F
|
1886 |
+
type: chrf
|
1887 |
+
value: 0.54917
|
1888 |
+
- task:
|
1889 |
+
name: Translation fra-deu
|
1890 |
+
type: translation
|
1891 |
+
args: fra-deu
|
1892 |
+
dataset:
|
1893 |
+
name: newstest2010
|
1894 |
+
type: wmt-2010-news
|
1895 |
+
args: fra-deu
|
1896 |
+
metrics:
|
1897 |
+
- name: BLEU
|
1898 |
+
type: bleu
|
1899 |
+
value: 24.3
|
1900 |
+
- name: chr-F
|
1901 |
+
type: chrf
|
1902 |
+
value: 0.53904
|
1903 |
+
- task:
|
1904 |
+
name: Translation fra-eng
|
1905 |
+
type: translation
|
1906 |
+
args: fra-eng
|
1907 |
+
dataset:
|
1908 |
+
name: newstest2010
|
1909 |
+
type: wmt-2010-news
|
1910 |
+
args: fra-eng
|
1911 |
+
metrics:
|
1912 |
+
- name: BLEU
|
1913 |
+
type: bleu
|
1914 |
+
value: 32.4
|
1915 |
+
- name: chr-F
|
1916 |
+
type: chrf
|
1917 |
+
value: 0.59241
|
1918 |
+
- task:
|
1919 |
+
name: Translation spa-deu
|
1920 |
+
type: translation
|
1921 |
+
args: spa-deu
|
1922 |
+
dataset:
|
1923 |
+
name: newstest2010
|
1924 |
+
type: wmt-2010-news
|
1925 |
+
args: spa-deu
|
1926 |
+
metrics:
|
1927 |
+
- name: BLEU
|
1928 |
+
type: bleu
|
1929 |
+
value: 26.2
|
1930 |
+
- name: chr-F
|
1931 |
+
type: chrf
|
1932 |
+
value: 0.55378
|
1933 |
+
- task:
|
1934 |
+
name: Translation spa-eng
|
1935 |
+
type: translation
|
1936 |
+
args: spa-eng
|
1937 |
+
dataset:
|
1938 |
+
name: newstest2010
|
1939 |
+
type: wmt-2010-news
|
1940 |
+
args: spa-eng
|
1941 |
+
metrics:
|
1942 |
+
- name: BLEU
|
1943 |
+
type: bleu
|
1944 |
+
value: 35.8
|
1945 |
+
- name: chr-F
|
1946 |
+
type: chrf
|
1947 |
+
value: 0.61316
|
1948 |
+
- task:
|
1949 |
+
name: Translation deu-eng
|
1950 |
+
type: translation
|
1951 |
+
args: deu-eng
|
1952 |
+
dataset:
|
1953 |
+
name: newstest2011
|
1954 |
+
type: wmt-2011-news
|
1955 |
+
args: deu-eng
|
1956 |
+
metrics:
|
1957 |
+
- name: BLEU
|
1958 |
+
type: bleu
|
1959 |
+
value: 26.1
|
1960 |
+
- name: chr-F
|
1961 |
+
type: chrf
|
1962 |
+
value: 0.54907
|
1963 |
+
- task:
|
1964 |
+
name: Translation eng-deu
|
1965 |
+
type: translation
|
1966 |
+
args: eng-deu
|
1967 |
+
dataset:
|
1968 |
+
name: newstest2011
|
1969 |
+
type: wmt-2011-news
|
1970 |
+
args: eng-deu
|
1971 |
+
metrics:
|
1972 |
+
- name: BLEU
|
1973 |
+
type: bleu
|
1974 |
+
value: 23.0
|
1975 |
+
- name: chr-F
|
1976 |
+
type: chrf
|
1977 |
+
value: 0.52873
|
1978 |
+
- task:
|
1979 |
+
name: Translation fra-deu
|
1980 |
+
type: translation
|
1981 |
+
args: fra-deu
|
1982 |
+
dataset:
|
1983 |
+
name: newstest2011
|
1984 |
+
type: wmt-2011-news
|
1985 |
+
args: fra-deu
|
1986 |
+
metrics:
|
1987 |
+
- name: BLEU
|
1988 |
+
type: bleu
|
1989 |
+
value: 23.0
|
1990 |
+
- name: chr-F
|
1991 |
+
type: chrf
|
1992 |
+
value: 0.52977
|
1993 |
+
- task:
|
1994 |
+
name: Translation fra-eng
|
1995 |
+
type: translation
|
1996 |
+
args: fra-eng
|
1997 |
+
dataset:
|
1998 |
+
name: newstest2011
|
1999 |
+
type: wmt-2011-news
|
2000 |
+
args: fra-eng
|
2001 |
+
metrics:
|
2002 |
+
- name: BLEU
|
2003 |
+
type: bleu
|
2004 |
+
value: 32.8
|
2005 |
+
- name: chr-F
|
2006 |
+
type: chrf
|
2007 |
+
value: 0.59565
|
2008 |
+
- task:
|
2009 |
+
name: Translation spa-deu
|
2010 |
+
type: translation
|
2011 |
+
args: spa-deu
|
2012 |
+
dataset:
|
2013 |
+
name: newstest2011
|
2014 |
+
type: wmt-2011-news
|
2015 |
+
args: spa-deu
|
2016 |
+
metrics:
|
2017 |
+
- name: BLEU
|
2018 |
+
type: bleu
|
2019 |
+
value: 23.4
|
2020 |
+
- name: chr-F
|
2021 |
+
type: chrf
|
2022 |
+
value: 0.53095
|
2023 |
+
- task:
|
2024 |
+
name: Translation spa-eng
|
2025 |
+
type: translation
|
2026 |
+
args: spa-eng
|
2027 |
+
dataset:
|
2028 |
+
name: newstest2011
|
2029 |
+
type: wmt-2011-news
|
2030 |
+
args: spa-eng
|
2031 |
+
metrics:
|
2032 |
+
- name: BLEU
|
2033 |
+
type: bleu
|
2034 |
+
value: 33.3
|
2035 |
+
- name: chr-F
|
2036 |
+
type: chrf
|
2037 |
+
value: 0.59513
|
2038 |
+
- task:
|
2039 |
+
name: Translation deu-eng
|
2040 |
+
type: translation
|
2041 |
+
args: deu-eng
|
2042 |
+
dataset:
|
2043 |
+
name: newstest2012
|
2044 |
+
type: wmt-2012-news
|
2045 |
+
args: deu-eng
|
2046 |
+
metrics:
|
2047 |
+
- name: BLEU
|
2048 |
+
type: bleu
|
2049 |
+
value: 28.1
|
2050 |
+
- name: chr-F
|
2051 |
+
type: chrf
|
2052 |
+
value: 0.56230
|
2053 |
+
- task:
|
2054 |
+
name: Translation eng-deu
|
2055 |
+
type: translation
|
2056 |
+
args: eng-deu
|
2057 |
+
dataset:
|
2058 |
+
name: newstest2012
|
2059 |
+
type: wmt-2012-news
|
2060 |
+
args: eng-deu
|
2061 |
+
metrics:
|
2062 |
+
- name: BLEU
|
2063 |
+
type: bleu
|
2064 |
+
value: 23.7
|
2065 |
+
- name: chr-F
|
2066 |
+
type: chrf
|
2067 |
+
value: 0.52871
|
2068 |
+
- task:
|
2069 |
+
name: Translation fra-deu
|
2070 |
+
type: translation
|
2071 |
+
args: fra-deu
|
2072 |
+
dataset:
|
2073 |
+
name: newstest2012
|
2074 |
+
type: wmt-2012-news
|
2075 |
+
args: fra-deu
|
2076 |
+
metrics:
|
2077 |
+
- name: BLEU
|
2078 |
+
type: bleu
|
2079 |
+
value: 24.1
|
2080 |
+
- name: chr-F
|
2081 |
+
type: chrf
|
2082 |
+
value: 0.53035
|
2083 |
+
- task:
|
2084 |
+
name: Translation fra-eng
|
2085 |
+
type: translation
|
2086 |
+
args: fra-eng
|
2087 |
+
dataset:
|
2088 |
+
name: newstest2012
|
2089 |
+
type: wmt-2012-news
|
2090 |
+
args: fra-eng
|
2091 |
+
metrics:
|
2092 |
+
- name: BLEU
|
2093 |
+
type: bleu
|
2094 |
+
value: 33.0
|
2095 |
+
- name: chr-F
|
2096 |
+
type: chrf
|
2097 |
+
value: 0.59137
|
2098 |
+
- task:
|
2099 |
+
name: Translation spa-deu
|
2100 |
+
type: translation
|
2101 |
+
args: spa-deu
|
2102 |
+
dataset:
|
2103 |
+
name: newstest2012
|
2104 |
+
type: wmt-2012-news
|
2105 |
+
args: spa-deu
|
2106 |
+
metrics:
|
2107 |
+
- name: BLEU
|
2108 |
+
type: bleu
|
2109 |
+
value: 24.3
|
2110 |
+
- name: chr-F
|
2111 |
+
type: chrf
|
2112 |
+
value: 0.53438
|
2113 |
+
- task:
|
2114 |
+
name: Translation spa-eng
|
2115 |
+
type: translation
|
2116 |
+
args: spa-eng
|
2117 |
+
dataset:
|
2118 |
+
name: newstest2012
|
2119 |
+
type: wmt-2012-news
|
2120 |
+
args: spa-eng
|
2121 |
+
metrics:
|
2122 |
+
- name: BLEU
|
2123 |
+
type: bleu
|
2124 |
+
value: 37.0
|
2125 |
+
- name: chr-F
|
2126 |
+
type: chrf
|
2127 |
+
value: 0.62058
|
2128 |
+
- task:
|
2129 |
+
name: Translation deu-eng
|
2130 |
+
type: translation
|
2131 |
+
args: deu-eng
|
2132 |
+
dataset:
|
2133 |
+
name: newstest2013
|
2134 |
+
type: wmt-2013-news
|
2135 |
+
args: deu-eng
|
2136 |
+
metrics:
|
2137 |
+
- name: BLEU
|
2138 |
+
type: bleu
|
2139 |
+
value: 31.5
|
2140 |
+
- name: chr-F
|
2141 |
+
type: chrf
|
2142 |
+
value: 0.57940
|
2143 |
+
- task:
|
2144 |
+
name: Translation eng-deu
|
2145 |
+
type: translation
|
2146 |
+
args: eng-deu
|
2147 |
+
dataset:
|
2148 |
+
name: newstest2013
|
2149 |
+
type: wmt-2013-news
|
2150 |
+
args: eng-deu
|
2151 |
+
metrics:
|
2152 |
+
- name: BLEU
|
2153 |
+
type: bleu
|
2154 |
+
value: 27.5
|
2155 |
+
- name: chr-F
|
2156 |
+
type: chrf
|
2157 |
+
value: 0.55718
|
2158 |
+
- task:
|
2159 |
+
name: Translation fra-deu
|
2160 |
+
type: translation
|
2161 |
+
args: fra-deu
|
2162 |
+
dataset:
|
2163 |
+
name: newstest2013
|
2164 |
+
type: wmt-2013-news
|
2165 |
+
args: fra-deu
|
2166 |
+
metrics:
|
2167 |
+
- name: BLEU
|
2168 |
+
type: bleu
|
2169 |
+
value: 25.6
|
2170 |
+
- name: chr-F
|
2171 |
+
type: chrf
|
2172 |
+
value: 0.54408
|
2173 |
+
- task:
|
2174 |
+
name: Translation fra-eng
|
2175 |
+
type: translation
|
2176 |
+
args: fra-eng
|
2177 |
+
dataset:
|
2178 |
+
name: newstest2013
|
2179 |
+
type: wmt-2013-news
|
2180 |
+
args: fra-eng
|
2181 |
+
metrics:
|
2182 |
+
- name: BLEU
|
2183 |
+
type: bleu
|
2184 |
+
value: 33.9
|
2185 |
+
- name: chr-F
|
2186 |
+
type: chrf
|
2187 |
+
value: 0.59151
|
2188 |
+
- task:
|
2189 |
+
name: Translation spa-deu
|
2190 |
+
type: translation
|
2191 |
+
args: spa-deu
|
2192 |
+
dataset:
|
2193 |
+
name: newstest2013
|
2194 |
+
type: wmt-2013-news
|
2195 |
+
args: spa-deu
|
2196 |
+
metrics:
|
2197 |
+
- name: BLEU
|
2198 |
+
type: bleu
|
2199 |
+
value: 26.2
|
2200 |
+
- name: chr-F
|
2201 |
+
type: chrf
|
2202 |
+
value: 0.55215
|
2203 |
+
- task:
|
2204 |
+
name: Translation spa-eng
|
2205 |
+
type: translation
|
2206 |
+
args: spa-eng
|
2207 |
+
dataset:
|
2208 |
+
name: newstest2013
|
2209 |
+
type: wmt-2013-news
|
2210 |
+
args: spa-eng
|
2211 |
+
metrics:
|
2212 |
+
- name: BLEU
|
2213 |
+
type: bleu
|
2214 |
+
value: 34.4
|
2215 |
+
- name: chr-F
|
2216 |
+
type: chrf
|
2217 |
+
value: 0.60465
|
2218 |
+
- task:
|
2219 |
+
name: Translation deu-eng
|
2220 |
+
type: translation
|
2221 |
+
args: deu-eng
|
2222 |
+
dataset:
|
2223 |
+
name: newstest2014
|
2224 |
+
type: wmt-2014-news
|
2225 |
+
args: deu-eng
|
2226 |
+
metrics:
|
2227 |
+
- name: BLEU
|
2228 |
+
type: bleu
|
2229 |
+
value: 33.1
|
2230 |
+
- name: chr-F
|
2231 |
+
type: chrf
|
2232 |
+
value: 0.59723
|
2233 |
+
- task:
|
2234 |
+
name: Translation eng-deu
|
2235 |
+
type: translation
|
2236 |
+
args: eng-deu
|
2237 |
+
dataset:
|
2238 |
+
name: newstest2014
|
2239 |
+
type: wmt-2014-news
|
2240 |
+
args: eng-deu
|
2241 |
+
metrics:
|
2242 |
+
- name: BLEU
|
2243 |
+
type: bleu
|
2244 |
+
value: 28.5
|
2245 |
+
- name: chr-F
|
2246 |
+
type: chrf
|
2247 |
+
value: 0.59127
|
2248 |
+
- task:
|
2249 |
+
name: Translation fra-eng
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2250 |
+
type: translation
|
2251 |
+
args: fra-eng
|
2252 |
+
dataset:
|
2253 |
+
name: newstest2014
|
2254 |
+
type: wmt-2014-news
|
2255 |
+
args: fra-eng
|
2256 |
+
metrics:
|
2257 |
+
- name: BLEU
|
2258 |
+
type: bleu
|
2259 |
+
value: 38.0
|
2260 |
+
- name: chr-F
|
2261 |
+
type: chrf
|
2262 |
+
value: 0.63411
|
2263 |
+
- task:
|
2264 |
+
name: Translation deu-eng
|
2265 |
+
type: translation
|
2266 |
+
args: deu-eng
|
2267 |
+
dataset:
|
2268 |
+
name: newstest2015
|
2269 |
+
type: wmt-2015-news
|
2270 |
+
args: deu-eng
|
2271 |
+
metrics:
|
2272 |
+
- name: BLEU
|
2273 |
+
type: bleu
|
2274 |
+
value: 33.7
|
2275 |
+
- name: chr-F
|
2276 |
+
type: chrf
|
2277 |
+
value: 0.59799
|
2278 |
+
- task:
|
2279 |
+
name: Translation eng-deu
|
2280 |
+
type: translation
|
2281 |
+
args: eng-deu
|
2282 |
+
dataset:
|
2283 |
+
name: newstest2015
|
2284 |
+
type: wmt-2015-news
|
2285 |
+
args: eng-deu
|
2286 |
+
metrics:
|
2287 |
+
- name: BLEU
|
2288 |
+
type: bleu
|
2289 |
+
value: 32.0
|
2290 |
+
- name: chr-F
|
2291 |
+
type: chrf
|
2292 |
+
value: 0.59977
|
2293 |
+
- task:
|
2294 |
+
name: Translation deu-eng
|
2295 |
+
type: translation
|
2296 |
+
args: deu-eng
|
2297 |
+
dataset:
|
2298 |
+
name: newstest2016
|
2299 |
+
type: wmt-2016-news
|
2300 |
+
args: deu-eng
|
2301 |
+
metrics:
|
2302 |
+
- name: BLEU
|
2303 |
+
type: bleu
|
2304 |
+
value: 40.4
|
2305 |
+
- name: chr-F
|
2306 |
+
type: chrf
|
2307 |
+
value: 0.65039
|
2308 |
+
- task:
|
2309 |
+
name: Translation eng-deu
|
2310 |
+
type: translation
|
2311 |
+
args: eng-deu
|
2312 |
+
dataset:
|
2313 |
+
name: newstest2016
|
2314 |
+
type: wmt-2016-news
|
2315 |
+
args: eng-deu
|
2316 |
+
metrics:
|
2317 |
+
- name: BLEU
|
2318 |
+
type: bleu
|
2319 |
+
value: 37.9
|
2320 |
+
- name: chr-F
|
2321 |
+
type: chrf
|
2322 |
+
value: 0.64144
|
2323 |
+
- task:
|
2324 |
+
name: Translation deu-eng
|
2325 |
+
type: translation
|
2326 |
+
args: deu-eng
|
2327 |
+
dataset:
|
2328 |
+
name: newstest2017
|
2329 |
+
type: wmt-2017-news
|
2330 |
+
args: deu-eng
|
2331 |
+
metrics:
|
2332 |
+
- name: BLEU
|
2333 |
+
type: bleu
|
2334 |
+
value: 35.3
|
2335 |
+
- name: chr-F
|
2336 |
+
type: chrf
|
2337 |
+
value: 0.60921
|
2338 |
+
- task:
|
2339 |
+
name: Translation eng-deu
|
2340 |
+
type: translation
|
2341 |
+
args: eng-deu
|
2342 |
+
dataset:
|
2343 |
+
name: newstest2017
|
2344 |
+
type: wmt-2017-news
|
2345 |
+
args: eng-deu
|
2346 |
+
metrics:
|
2347 |
+
- name: BLEU
|
2348 |
+
type: bleu
|
2349 |
+
value: 30.4
|
2350 |
+
- name: chr-F
|
2351 |
+
type: chrf
|
2352 |
+
value: 0.59114
|
2353 |
+
- task:
|
2354 |
+
name: Translation deu-eng
|
2355 |
+
type: translation
|
2356 |
+
args: deu-eng
|
2357 |
+
dataset:
|
2358 |
+
name: newstest2018
|
2359 |
+
type: wmt-2018-news
|
2360 |
+
args: deu-eng
|
2361 |
+
metrics:
|
2362 |
+
- name: BLEU
|
2363 |
+
type: bleu
|
2364 |
+
value: 42.6
|
2365 |
+
- name: chr-F
|
2366 |
+
type: chrf
|
2367 |
+
value: 0.66680
|
2368 |
+
- task:
|
2369 |
+
name: Translation eng-deu
|
2370 |
+
type: translation
|
2371 |
+
args: eng-deu
|
2372 |
+
dataset:
|
2373 |
+
name: newstest2018
|
2374 |
+
type: wmt-2018-news
|
2375 |
+
args: eng-deu
|
2376 |
+
metrics:
|
2377 |
+
- name: BLEU
|
2378 |
+
type: bleu
|
2379 |
+
value: 45.8
|
2380 |
+
- name: chr-F
|
2381 |
+
type: chrf
|
2382 |
+
value: 0.69428
|
2383 |
+
- task:
|
2384 |
+
name: Translation deu-eng
|
2385 |
+
type: translation
|
2386 |
+
args: deu-eng
|
2387 |
+
dataset:
|
2388 |
+
name: newstest2019
|
2389 |
+
type: wmt-2019-news
|
2390 |
+
args: deu-eng
|
2391 |
+
metrics:
|
2392 |
+
- name: BLEU
|
2393 |
+
type: bleu
|
2394 |
+
value: 39.1
|
2395 |
+
- name: chr-F
|
2396 |
+
type: chrf
|
2397 |
+
value: 0.63482
|
2398 |
+
- task:
|
2399 |
+
name: Translation eng-deu
|
2400 |
+
type: translation
|
2401 |
+
args: eng-deu
|
2402 |
+
dataset:
|
2403 |
+
name: newstest2019
|
2404 |
+
type: wmt-2019-news
|
2405 |
+
args: eng-deu
|
2406 |
+
metrics:
|
2407 |
+
- name: BLEU
|
2408 |
+
type: bleu
|
2409 |
+
value: 42.0
|
2410 |
+
- name: chr-F
|
2411 |
+
type: chrf
|
2412 |
+
value: 0.66430
|
2413 |
+
- task:
|
2414 |
+
name: Translation fra-deu
|
2415 |
+
type: translation
|
2416 |
+
args: fra-deu
|
2417 |
+
dataset:
|
2418 |
+
name: newstest2019
|
2419 |
+
type: wmt-2019-news
|
2420 |
+
args: fra-deu
|
2421 |
+
metrics:
|
2422 |
+
- name: BLEU
|
2423 |
+
type: bleu
|
2424 |
+
value: 29.4
|
2425 |
+
- name: chr-F
|
2426 |
+
type: chrf
|
2427 |
+
value: 0.60993
|
2428 |
+
- task:
|
2429 |
+
name: Translation deu-eng
|
2430 |
+
type: translation
|
2431 |
+
args: deu-eng
|
2432 |
+
dataset:
|
2433 |
+
name: newstest2020
|
2434 |
+
type: wmt-2020-news
|
2435 |
+
args: deu-eng
|
2436 |
+
metrics:
|
2437 |
+
- name: BLEU
|
2438 |
+
type: bleu
|
2439 |
+
value: 34.0
|
2440 |
+
- name: chr-F
|
2441 |
+
type: chrf
|
2442 |
+
value: 0.60403
|
2443 |
+
- task:
|
2444 |
+
name: Translation eng-deu
|
2445 |
+
type: translation
|
2446 |
+
args: eng-deu
|
2447 |
+
dataset:
|
2448 |
+
name: newstest2020
|
2449 |
+
type: wmt-2020-news
|
2450 |
+
args: eng-deu
|
2451 |
+
metrics:
|
2452 |
+
- name: BLEU
|
2453 |
+
type: bleu
|
2454 |
+
value: 32.3
|
2455 |
+
- name: chr-F
|
2456 |
+
type: chrf
|
2457 |
+
value: 0.60255
|
2458 |
+
- task:
|
2459 |
+
name: Translation fra-deu
|
2460 |
+
type: translation
|
2461 |
+
args: fra-deu
|
2462 |
+
dataset:
|
2463 |
+
name: newstest2020
|
2464 |
+
type: wmt-2020-news
|
2465 |
+
args: fra-deu
|
2466 |
+
metrics:
|
2467 |
+
- name: BLEU
|
2468 |
+
type: bleu
|
2469 |
+
value: 29.2
|
2470 |
+
- name: chr-F
|
2471 |
+
type: chrf
|
2472 |
+
value: 0.61470
|
2473 |
+
- task:
|
2474 |
+
name: Translation deu-eng
|
2475 |
+
type: translation
|
2476 |
+
args: deu-eng
|
2477 |
+
dataset:
|
2478 |
+
name: newstest2021
|
2479 |
+
type: wmt-2021-news
|
2480 |
+
args: deu-eng
|
2481 |
+
metrics:
|
2482 |
+
- name: BLEU
|
2483 |
+
type: bleu
|
2484 |
+
value: 31.9
|
2485 |
+
- name: chr-F
|
2486 |
+
type: chrf
|
2487 |
+
value: 0.59738
|
2488 |
+
- task:
|
2489 |
+
name: Translation eng-deu
|
2490 |
+
type: translation
|
2491 |
+
args: eng-deu
|
2492 |
+
dataset:
|
2493 |
+
name: newstest2021
|
2494 |
+
type: wmt-2021-news
|
2495 |
+
args: eng-deu
|
2496 |
+
metrics:
|
2497 |
+
- name: BLEU
|
2498 |
+
type: bleu
|
2499 |
+
value: 26.1
|
2500 |
+
- name: chr-F
|
2501 |
+
type: chrf
|
2502 |
+
value: 0.56399
|
2503 |
+
- task:
|
2504 |
+
name: Translation fra-deu
|
2505 |
+
type: translation
|
2506 |
+
args: fra-deu
|
2507 |
+
dataset:
|
2508 |
+
name: newstest2021
|
2509 |
+
type: wmt-2021-news
|
2510 |
+
args: fra-deu
|
2511 |
+
metrics:
|
2512 |
+
- name: BLEU
|
2513 |
+
type: bleu
|
2514 |
+
value: 40.0
|
2515 |
+
- name: chr-F
|
2516 |
+
type: chrf
|
2517 |
+
value: 0.66155
|
2518 |
+
---
|
2519 |
+
# opus-mt-tc-bible-big-deu_eng_fra_por_spa-gmw
|
2520 |
+
|
2521 |
+
## Table of Contents
|
2522 |
+
- [Model Details](#model-details)
|
2523 |
+
- [Uses](#uses)
|
2524 |
+
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
|
2525 |
+
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
|
2526 |
+
- [Training](#training)
|
2527 |
+
- [Evaluation](#evaluation)
|
2528 |
+
- [Citation Information](#citation-information)
|
2529 |
+
- [Acknowledgements](#acknowledgements)
|
2530 |
+
|
2531 |
+
## Model Details
|
2532 |
+
|
2533 |
+
Neural machine translation model for translating from unknown (deu+eng+fra+por+spa) to West Germanic languages (gmw).
|
2534 |
+
|
2535 |
+
This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
|
2536 |
+
**Model Description:**
|
2537 |
+
- **Developed by:** Language Technology Research Group at the University of Helsinki
|
2538 |
+
- **Model Type:** Translation (transformer-big)
|
2539 |
+
- **Release**: 2024-05-30
|
2540 |
+
- **License:** Apache-2.0
|
2541 |
+
- **Language(s):**
|
2542 |
+
- Source Language(s): deu eng fra por spa
|
2543 |
+
- Target Language(s): afr ang bar bis bzj deu djk drt eng enm frr fry gos gsw hrx hwc icr jam kri ksh lim ltz nds nld ofs pcm pdc pfl pih pis rop sco srm srn stq swg tcs tpi vls wae yid zea
|
2544 |
+
- Valid Target Language Labels: >>act<< >>afr<< >>afs<< >>aig<< >>ang<< >>ang_Latn<< >>bah<< >>bar<< >>bis<< >>bjs<< >>brc<< >>bzj<< >>bzk<< >>cim<< >>dcr<< >>deu<< >>djk<< >>djk_Latn<< >>drt<< >>drt_Latn<< >>dum<< >>eng<< >>enm<< >>enm_Latn<< >>fpe<< >>frk<< >>frr<< >>fry<< >>gcl<< >>gct<< >>geh<< >>gmh<< >>gml<< >>goh<< >>gos<< >>gpe<< >>gsw<< >>gul<< >>gyn<< >>hrx<< >>hrx_Latn<< >>hwc<< >>icr<< >>jam<< >>jvd<< >>kri<< >>ksh<< >>kww<< >>lim<< >>lng<< >>ltz<< >>mhn<< >>nds<< >>nld<< >>odt<< >>ofs<< >>ofs_Latn<< >>oor<< >>osx<< >>pcm<< >>pdc<< >>pdt<< >>pey<< >>pfl<< >>pih<< >>pih_Latn<< >>pis<< >>rop<< >>sco<< >>sdz<< >>skw<< >>sli<< >>srm<< >>srn<< >>stl<< >>stq<< >>svc<< >>swg<< >>sxu<< >>tch<< >>tcs<< >>tgh<< >>tpi<< >>trf<< >>twd<< >>uln<< >>vel<< >>vic<< >>vls<< >>vmf<< >>wae<< >>wep<< >>wes<< >>wym<< >>xxx<< >>yec<< >>yid<< >>zea<<
|
2545 |
+
- **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-gmw/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
|
2546 |
+
- **Resources for more information:**
|
2547 |
+
- [OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/deu%2Beng%2Bfra%2Bpor%2Bspa-gmw/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
|
2548 |
+
- [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
|
2549 |
+
- [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
|
2550 |
+
- [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/)
|
2551 |
+
- [HPLT bilingual data v1 (as part of the Tatoeba Translation Challenge dataset)](https://hplt-project.org/datasets/v1)
|
2552 |
+
- [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)
|
2553 |
+
|
2554 |
+
This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>afr<<`
|
2555 |
+
|
2556 |
+
## Uses
|
2557 |
+
|
2558 |
+
This model can be used for translation and text-to-text generation.
|
2559 |
+
|
2560 |
+
## Risks, Limitations and Biases
|
2561 |
+
|
2562 |
+
**CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.**
|
2563 |
+
|
2564 |
+
Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
|
2565 |
+
|
2566 |
+
## How to Get Started With the Model
|
2567 |
+
|
2568 |
+
A short example code:
|
2569 |
+
|
2570 |
+
```python
|
2571 |
+
from transformers import MarianMTModel, MarianTokenizer
|
2572 |
+
|
2573 |
+
src_text = [
|
2574 |
+
">>afr<< Replace this with text in an accepted source language.",
|
2575 |
+
">>zea<< This is the second sentence."
|
2576 |
+
]
|
2577 |
+
|
2578 |
+
model_name = "pytorch-models/opus-mt-tc-bible-big-deu_eng_fra_por_spa-gmw"
|
2579 |
+
tokenizer = MarianTokenizer.from_pretrained(model_name)
|
2580 |
+
model = MarianMTModel.from_pretrained(model_name)
|
2581 |
+
translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
|
2582 |
+
|
2583 |
+
for t in translated:
|
2584 |
+
print( tokenizer.decode(t, skip_special_tokens=True) )
|
2585 |
+
```
|
2586 |
+
|
2587 |
+
You can also use OPUS-MT models with the transformers pipelines, for example:
|
2588 |
+
|
2589 |
+
```python
|
2590 |
+
from transformers import pipeline
|
2591 |
+
pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-bible-big-deu_eng_fra_por_spa-gmw")
|
2592 |
+
print(pipe(">>afr<< Replace this with text in an accepted source language."))
|
2593 |
+
```
|
2594 |
+
|
2595 |
+
## Training
|
2596 |
+
|
2597 |
+
- **Data**: opusTCv20230926max50+bt+jhubc ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
|
2598 |
+
- **Pre-processing**: SentencePiece (spm32k,spm32k)
|
2599 |
+
- **Model Type:** transformer-big
|
2600 |
+
- **Original MarianNMT Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-gmw/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
|
2601 |
+
- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
|
2602 |
+
|
2603 |
+
## Evaluation
|
2604 |
+
|
2605 |
+
* [Model scores at the OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/deu%2Beng%2Bfra%2Bpor%2Bspa-gmw/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
|
2606 |
+
* test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-gmw/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt)
|
2607 |
+
* test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-gmw/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt)
|
2608 |
+
* benchmark results: [benchmark_results.txt](benchmark_results.txt)
|
2609 |
+
* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
|
2610 |
+
|
2611 |
+
| langpair | testset | chr-F | BLEU | #sent | #words |
|
2612 |
+
|----------|---------|-------|-------|-------|--------|
|
2613 |
+
| deu-afr | tatoeba-test-v2021-08-07 | 0.72039 | 56.7 | 1583 | 9507 |
|
2614 |
+
| deu-deu | tatoeba-test-v2021-08-07 | 0.59545 | 33.7 | 2500 | 20806 |
|
2615 |
+
| deu-eng | tatoeba-test-v2021-08-07 | 0.66015 | 48.6 | 17565 | 149462 |
|
2616 |
+
| deu-ltz | tatoeba-test-v2021-08-07 | 0.53760 | 34.2 | 347 | 2206 |
|
2617 |
+
| deu-nds | tatoeba-test-v2021-08-07 | 0.44534 | 20.1 | 9999 | 76137 |
|
2618 |
+
| deu-nld | tatoeba-test-v2021-08-07 | 0.71276 | 54.4 | 10218 | 75235 |
|
2619 |
+
| eng-afr | tatoeba-test-v2021-08-07 | 0.72087 | 56.6 | 1374 | 10317 |
|
2620 |
+
| eng-deu | tatoeba-test-v2021-08-07 | 0.62971 | 41.4 | 17565 | 151568 |
|
2621 |
+
| eng-eng | tatoeba-test-v2021-08-07 | 0.80306 | 58.0 | 12062 | 115106 |
|
2622 |
+
| eng-fry | tatoeba-test-v2021-08-07 | 0.40324 | 13.8 | 220 | 1600 |
|
2623 |
+
| eng-ltz | tatoeba-test-v2021-08-07 | 0.64423 | 45.8 | 293 | 1828 |
|
2624 |
+
| eng-nds | tatoeba-test-v2021-08-07 | 0.46446 | 22.2 | 2500 | 18264 |
|
2625 |
+
| eng-nld | tatoeba-test-v2021-08-07 | 0.71190 | 54.5 | 12696 | 91796 |
|
2626 |
+
| fra-deu | tatoeba-test-v2021-08-07 | 0.68991 | 50.3 | 12418 | 100545 |
|
2627 |
+
| fra-eng | tatoeba-test-v2021-08-07 | 0.72564 | 58.0 | 12681 | 101754 |
|
2628 |
+
| fra-nld | tatoeba-test-v2021-08-07 | 0.67078 | 48.7 | 11548 | 82164 |
|
2629 |
+
| por-deu | tatoeba-test-v2021-08-07 | 0.68437 | 48.7 | 10000 | 81246 |
|
2630 |
+
| por-eng | tatoeba-test-v2021-08-07 | 0.77081 | 64.3 | 13222 | 105351 |
|
2631 |
+
| por-nds | tatoeba-test-v2021-08-07 | 0.45864 | 20.7 | 207 | 1292 |
|
2632 |
+
| por-nld | tatoeba-test-v2021-08-07 | 0.69865 | 52.8 | 2500 | 17816 |
|
2633 |
+
| spa-afr | tatoeba-test-v2021-08-07 | 0.77148 | 63.3 | 448 | 3044 |
|
2634 |
+
| spa-deu | tatoeba-test-v2021-08-07 | 0.68037 | 49.1 | 10521 | 86430 |
|
2635 |
+
| spa-eng | tatoeba-test-v2021-08-07 | 0.74575 | 60.2 | 16583 | 138123 |
|
2636 |
+
| spa-nds | tatoeba-test-v2021-08-07 | 0.43154 | 18.5 | 923 | 5941 |
|
2637 |
+
| spa-nld | tatoeba-test-v2021-08-07 | 0.68988 | 51.1 | 10113 | 79162 |
|
2638 |
+
| deu-afr | flores101-devtest | 0.57287 | 26.0 | 1012 | 25740 |
|
2639 |
+
| deu-eng | flores101-devtest | 0.66660 | 40.9 | 1012 | 24721 |
|
2640 |
+
| deu-nld | flores101-devtest | 0.55423 | 23.6 | 1012 | 25467 |
|
2641 |
+
| eng-afr | flores101-devtest | 0.67793 | 40.0 | 1012 | 25740 |
|
2642 |
+
| eng-deu | flores101-devtest | 0.64295 | 37.2 | 1012 | 25094 |
|
2643 |
+
| eng-nld | flores101-devtest | 0.57690 | 26.2 | 1012 | 25467 |
|
2644 |
+
| fra-ltz | flores101-devtest | 0.49430 | 17.3 | 1012 | 25087 |
|
2645 |
+
| fra-nld | flores101-devtest | 0.54318 | 22.2 | 1012 | 25467 |
|
2646 |
+
| por-deu | flores101-devtest | 0.58851 | 29.8 | 1012 | 25094 |
|
2647 |
+
| por-nld | flores101-devtest | 0.54571 | 22.6 | 1012 | 25467 |
|
2648 |
+
| spa-nld | flores101-devtest | 0.50968 | 17.5 | 1012 | 25467 |
|
2649 |
+
| deu-afr | flores200-devtest | 0.57725 | 26.2 | 1012 | 25740 |
|
2650 |
+
| deu-eng | flores200-devtest | 0.67043 | 41.5 | 1012 | 24721 |
|
2651 |
+
| deu-ltz | flores200-devtest | 0.54626 | 21.6 | 1012 | 25087 |
|
2652 |
+
| deu-nld | flores200-devtest | 0.55679 | 24.0 | 1012 | 25467 |
|
2653 |
+
| eng-afr | flores200-devtest | 0.68115 | 40.2 | 1012 | 25740 |
|
2654 |
+
| eng-deu | flores200-devtest | 0.64561 | 37.4 | 1012 | 25094 |
|
2655 |
+
| eng-ltz | flores200-devtest | 0.54932 | 22.0 | 1012 | 25087 |
|
2656 |
+
| eng-nld | flores200-devtest | 0.58124 | 26.8 | 1012 | 25467 |
|
2657 |
+
| eng-tpi | flores200-devtest | 0.40338 | 15.9 | 1012 | 35240 |
|
2658 |
+
| fra-afr | flores200-devtest | 0.57320 | 26.4 | 1012 | 25740 |
|
2659 |
+
| fra-deu | flores200-devtest | 0.58974 | 29.5 | 1012 | 25094 |
|
2660 |
+
| fra-eng | flores200-devtest | 0.68106 | 43.7 | 1012 | 24721 |
|
2661 |
+
| fra-ltz | flores200-devtest | 0.49618 | 17.8 | 1012 | 25087 |
|
2662 |
+
| fra-nld | flores200-devtest | 0.54623 | 22.5 | 1012 | 25467 |
|
2663 |
+
| por-afr | flores200-devtest | 0.58408 | 27.6 | 1012 | 25740 |
|
2664 |
+
| por-deu | flores200-devtest | 0.59121 | 30.4 | 1012 | 25094 |
|
2665 |
+
| por-eng | flores200-devtest | 0.71418 | 48.3 | 1012 | 24721 |
|
2666 |
+
| por-nld | flores200-devtest | 0.54828 | 22.9 | 1012 | 25467 |
|
2667 |
+
| spa-afr | flores200-devtest | 0.51514 | 17.8 | 1012 | 25740 |
|
2668 |
+
| spa-deu | flores200-devtest | 0.53603 | 21.4 | 1012 | 25094 |
|
2669 |
+
| spa-eng | flores200-devtest | 0.58604 | 28.2 | 1012 | 24721 |
|
2670 |
+
| spa-nld | flores200-devtest | 0.51244 | 17.9 | 1012 | 25467 |
|
2671 |
+
| deu-eng | generaltest2022 | 0.55777 | 30.6 | 1984 | 37634 |
|
2672 |
+
| eng-deu | generaltest2022 | 0.60792 | 33.0 | 2037 | 38914 |
|
2673 |
+
| fra-deu | generaltest2022 | 0.67039 | 44.5 | 2006 | 37696 |
|
2674 |
+
| deu-eng | multi30k_test_2016_flickr | 0.60981 | 40.1 | 1000 | 12955 |
|
2675 |
+
| eng-deu | multi30k_test_2016_flickr | 0.64153 | 34.9 | 1000 | 12106 |
|
2676 |
+
| fra-deu | multi30k_test_2016_flickr | 0.61781 | 32.1 | 1000 | 12106 |
|
2677 |
+
| fra-eng | multi30k_test_2016_flickr | 0.66703 | 47.9 | 1000 | 12955 |
|
2678 |
+
| deu-eng | multi30k_test_2017_flickr | 0.63624 | 41.0 | 1000 | 11374 |
|
2679 |
+
| eng-deu | multi30k_test_2017_flickr | 0.63423 | 34.6 | 1000 | 10755 |
|
2680 |
+
| fra-deu | multi30k_test_2017_flickr | 0.60084 | 29.7 | 1000 | 10755 |
|
2681 |
+
| fra-eng | multi30k_test_2017_flickr | 0.69254 | 50.4 | 1000 | 11374 |
|
2682 |
+
| deu-eng | multi30k_test_2017_mscoco | 0.55790 | 32.5 | 461 | 5231 |
|
2683 |
+
| eng-deu | multi30k_test_2017_mscoco | 0.57491 | 28.6 | 461 | 5158 |
|
2684 |
+
| fra-deu | multi30k_test_2017_mscoco | 0.56108 | 26.4 | 461 | 5158 |
|
2685 |
+
| fra-eng | multi30k_test_2017_mscoco | 0.68212 | 49.1 | 461 | 5231 |
|
2686 |
+
| deu-eng | multi30k_test_2018_flickr | 0.59322 | 36.6 | 1071 | 14689 |
|
2687 |
+
| eng-deu | multi30k_test_2018_flickr | 0.59858 | 30.0 | 1071 | 13703 |
|
2688 |
+
| fra-deu | multi30k_test_2018_flickr | 0.55667 | 24.7 | 1071 | 13703 |
|
2689 |
+
| fra-eng | multi30k_test_2018_flickr | 0.64702 | 43.4 | 1071 | 14689 |
|
2690 |
+
| fra-eng | newsdiscusstest2015 | 0.61399 | 38.5 | 1500 | 26982 |
|
2691 |
+
| deu-eng | newssyscomb2009 | 0.55180 | 28.8 | 502 | 11818 |
|
2692 |
+
| eng-deu | newssyscomb2009 | 0.53676 | 22.9 | 502 | 11271 |
|
2693 |
+
| fra-deu | newssyscomb2009 | 0.53733 | 23.9 | 502 | 11271 |
|
2694 |
+
| fra-eng | newssyscomb2009 | 0.57219 | 31.1 | 502 | 11818 |
|
2695 |
+
| spa-deu | newssyscomb2009 | 0.53056 | 22.0 | 502 | 11271 |
|
2696 |
+
| spa-eng | newssyscomb2009 | 0.57225 | 30.8 | 502 | 11818 |
|
2697 |
+
| deu-eng | newstest2008 | 0.54506 | 26.9 | 2051 | 49380 |
|
2698 |
+
| eng-deu | newstest2008 | 0.53077 | 23.1 | 2051 | 47447 |
|
2699 |
+
| fra-deu | newstest2008 | 0.53204 | 22.9 | 2051 | 47447 |
|
2700 |
+
| fra-eng | newstest2008 | 0.54320 | 26.4 | 2051 | 49380 |
|
2701 |
+
| spa-deu | newstest2008 | 0.52066 | 21.6 | 2051 | 47447 |
|
2702 |
+
| spa-eng | newstest2008 | 0.55305 | 27.9 | 2051 | 49380 |
|
2703 |
+
| deu-eng | newstest2009 | 0.53773 | 26.2 | 2525 | 65399 |
|
2704 |
+
| eng-deu | newstest2009 | 0.53217 | 22.3 | 2525 | 62816 |
|
2705 |
+
| fra-deu | newstest2009 | 0.52995 | 22.9 | 2525 | 62816 |
|
2706 |
+
| fra-eng | newstest2009 | 0.56663 | 30.0 | 2525 | 65399 |
|
2707 |
+
| spa-deu | newstest2009 | 0.52586 | 22.1 | 2525 | 62816 |
|
2708 |
+
| spa-eng | newstest2009 | 0.56756 | 29.9 | 2525 | 65399 |
|
2709 |
+
| deu-eng | newstest2010 | 0.58365 | 30.4 | 2489 | 61711 |
|
2710 |
+
| eng-deu | newstest2010 | 0.54917 | 25.7 | 2489 | 61503 |
|
2711 |
+
| fra-deu | newstest2010 | 0.53904 | 24.3 | 2489 | 61503 |
|
2712 |
+
| fra-eng | newstest2010 | 0.59241 | 32.4 | 2489 | 61711 |
|
2713 |
+
| spa-deu | newstest2010 | 0.55378 | 26.2 | 2489 | 61503 |
|
2714 |
+
| spa-eng | newstest2010 | 0.61316 | 35.8 | 2489 | 61711 |
|
2715 |
+
| deu-eng | newstest2011 | 0.54907 | 26.1 | 3003 | 74681 |
|
2716 |
+
| eng-deu | newstest2011 | 0.52873 | 23.0 | 3003 | 72981 |
|
2717 |
+
| fra-deu | newstest2011 | 0.52977 | 23.0 | 3003 | 72981 |
|
2718 |
+
| fra-eng | newstest2011 | 0.59565 | 32.8 | 3003 | 74681 |
|
2719 |
+
| spa-deu | newstest2011 | 0.53095 | 23.4 | 3003 | 72981 |
|
2720 |
+
| spa-eng | newstest2011 | 0.59513 | 33.3 | 3003 | 74681 |
|
2721 |
+
| deu-eng | newstest2012 | 0.56230 | 28.1 | 3003 | 72812 |
|
2722 |
+
| eng-deu | newstest2012 | 0.52871 | 23.7 | 3003 | 72886 |
|
2723 |
+
| fra-deu | newstest2012 | 0.53035 | 24.1 | 3003 | 72886 |
|
2724 |
+
| fra-eng | newstest2012 | 0.59137 | 33.0 | 3003 | 72812 |
|
2725 |
+
| spa-deu | newstest2012 | 0.53438 | 24.3 | 3003 | 72886 |
|
2726 |
+
| spa-eng | newstest2012 | 0.62058 | 37.0 | 3003 | 72812 |
|
2727 |
+
| deu-eng | newstest2013 | 0.57940 | 31.5 | 3000 | 64505 |
|
2728 |
+
| eng-deu | newstest2013 | 0.55718 | 27.5 | 3000 | 63737 |
|
2729 |
+
| fra-deu | newstest2013 | 0.54408 | 25.6 | 3000 | 63737 |
|
2730 |
+
| fra-eng | newstest2013 | 0.59151 | 33.9 | 3000 | 64505 |
|
2731 |
+
| spa-deu | newstest2013 | 0.55215 | 26.2 | 3000 | 63737 |
|
2732 |
+
| spa-eng | newstest2013 | 0.60465 | 34.4 | 3000 | 64505 |
|
2733 |
+
| deu-eng | newstest2014 | 0.59723 | 33.1 | 3003 | 67337 |
|
2734 |
+
| eng-deu | newstest2014 | 0.59127 | 28.5 | 3003 | 62688 |
|
2735 |
+
| fra-eng | newstest2014 | 0.63411 | 38.0 | 3003 | 70708 |
|
2736 |
+
| deu-eng | newstest2015 | 0.59799 | 33.7 | 2169 | 46443 |
|
2737 |
+
| eng-deu | newstest2015 | 0.59977 | 32.0 | 2169 | 44260 |
|
2738 |
+
| deu-eng | newstest2016 | 0.65039 | 40.4 | 2999 | 64119 |
|
2739 |
+
| eng-deu | newstest2016 | 0.64144 | 37.9 | 2999 | 62669 |
|
2740 |
+
| deu-eng | newstest2017 | 0.60921 | 35.3 | 3004 | 64399 |
|
2741 |
+
| eng-deu | newstest2017 | 0.59114 | 30.4 | 3004 | 61287 |
|
2742 |
+
| deu-eng | newstest2018 | 0.66680 | 42.6 | 2998 | 67012 |
|
2743 |
+
| eng-deu | newstest2018 | 0.69428 | 45.8 | 2998 | 64276 |
|
2744 |
+
| deu-eng | newstest2019 | 0.63482 | 39.1 | 2000 | 39227 |
|
2745 |
+
| eng-deu | newstest2019 | 0.66430 | 42.0 | 1997 | 48746 |
|
2746 |
+
| fra-deu | newstest2019 | 0.60993 | 29.4 | 1701 | 36446 |
|
2747 |
+
| deu-eng | newstest2020 | 0.60403 | 34.0 | 785 | 38220 |
|
2748 |
+
| eng-deu | newstest2020 | 0.60255 | 32.3 | 1418 | 52383 |
|
2749 |
+
| fra-deu | newstest2020 | 0.61470 | 29.2 | 1619 | 30265 |
|
2750 |
+
| deu-eng | newstest2021 | 0.59738 | 31.9 | 1000 | 20180 |
|
2751 |
+
| eng-deu | newstest2021 | 0.56399 | 26.1 | 1002 | 27970 |
|
2752 |
+
| fra-deu | newstest2021 | 0.66155 | 40.0 | 1026 | 26077 |
|
2753 |
+
| deu-eng | newstestALL2020 | 0.60403 | 34.0 | 785 | 38220 |
|
2754 |
+
| eng-deu | newstestALL2020 | 0.60255 | 32.3 | 1418 | 52383 |
|
2755 |
+
| deu-eng | newstestB2020 | 0.60520 | 34.2 | 785 | 37696 |
|
2756 |
+
| eng-deu | newstestB2020 | 0.59226 | 31.6 | 1418 | 53092 |
|
2757 |
+
| deu-afr | ntrex128 | 0.57109 | 27.9 | 1997 | 50050 |
|
2758 |
+
| deu-eng | ntrex128 | 0.62043 | 34.5 | 1997 | 47673 |
|
2759 |
+
| deu-ltz | ntrex128 | 0.47642 | 15.4 | 1997 | 49763 |
|
2760 |
+
| deu-nld | ntrex128 | 0.56777 | 27.6 | 1997 | 51884 |
|
2761 |
+
| eng-afr | ntrex128 | 0.68616 | 44.1 | 1997 | 50050 |
|
2762 |
+
| eng-deu | ntrex128 | 0.58743 | 30.2 | 1997 | 48761 |
|
2763 |
+
| eng-ltz | ntrex128 | 0.50083 | 18.0 | 1997 | 49763 |
|
2764 |
+
| eng-nld | ntrex128 | 0.61041 | 33.8 | 1997 | 51884 |
|
2765 |
+
| fra-afr | ntrex128 | 0.55607 | 26.5 | 1997 | 50050 |
|
2766 |
+
| fra-deu | ntrex128 | 0.53269 | 23.6 | 1997 | 48761 |
|
2767 |
+
| fra-eng | ntrex128 | 0.61058 | 34.4 | 1997 | 47673 |
|
2768 |
+
| fra-ltz | ntrex128 | 0.41312 | 12.0 | 1997 | 49763 |
|
2769 |
+
| fra-nld | ntrex128 | 0.54615 | 25.2 | 1997 | 51884 |
|
2770 |
+
| por-afr | ntrex128 | 0.58296 | 29.2 | 1997 | 50050 |
|
2771 |
+
| por-deu | ntrex128 | 0.54944 | 24.7 | 1997 | 48761 |
|
2772 |
+
| por-eng | ntrex128 | 0.65002 | 39.6 | 1997 | 47673 |
|
2773 |
+
| por-nld | ntrex128 | 0.56384 | 28.1 | 1997 | 51884 |
|
2774 |
+
| spa-afr | ntrex128 | 0.57772 | 27.7 | 1997 | 50050 |
|
2775 |
+
| spa-deu | ntrex128 | 0.54561 | 24.0 | 1997 | 48761 |
|
2776 |
+
| spa-eng | ntrex128 | 0.64305 | 37.3 | 1997 | 47673 |
|
2777 |
+
| spa-nld | ntrex128 | 0.56397 | 27.8 | 1997 | 51884 |
|
2778 |
+
| fra-eng | tico19-test | 0.62059 | 39.2 | 2100 | 56323 |
|
2779 |
+
| por-eng | tico19-test | 0.73896 | 50.3 | 2100 | 56315 |
|
2780 |
+
| spa-eng | tico19-test | 0.72923 | 49.6 | 2100 | 56315 |
|
2781 |
+
|
2782 |
+
## Citation Information
|
2783 |
+
|
2784 |
+
* Publications: [Democratizing neural machine translation with OPUS-MT](https://doi.org/10.1007/s10579-023-09704-w) and [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
|
2785 |
+
|
2786 |
+
```bibtex
|
2787 |
+
@article{tiedemann2023democratizing,
|
2788 |
+
title={Democratizing neural machine translation with {OPUS-MT}},
|
2789 |
+
author={Tiedemann, J{\"o}rg and Aulamo, Mikko and Bakshandaeva, Daria and Boggia, Michele and Gr{\"o}nroos, Stig-Arne and Nieminen, Tommi and Raganato, Alessandro and Scherrer, Yves and Vazquez, Raul and Virpioja, Sami},
|
2790 |
+
journal={Language Resources and Evaluation},
|
2791 |
+
number={58},
|
2792 |
+
pages={713--755},
|
2793 |
+
year={2023},
|
2794 |
+
publisher={Springer Nature},
|
2795 |
+
issn={1574-0218},
|
2796 |
+
doi={10.1007/s10579-023-09704-w}
|
2797 |
+
}
|
2798 |
+
|
2799 |
+
@inproceedings{tiedemann-thottingal-2020-opus,
|
2800 |
+
title = "{OPUS}-{MT} {--} Building open translation services for the World",
|
2801 |
+
author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh},
|
2802 |
+
booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
|
2803 |
+
month = nov,
|
2804 |
+
year = "2020",
|
2805 |
+
address = "Lisboa, Portugal",
|
2806 |
+
publisher = "European Association for Machine Translation",
|
2807 |
+
url = "https://aclanthology.org/2020.eamt-1.61",
|
2808 |
+
pages = "479--480",
|
2809 |
+
}
|
2810 |
+
|
2811 |
+
@inproceedings{tiedemann-2020-tatoeba,
|
2812 |
+
title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
|
2813 |
+
author = {Tiedemann, J{\"o}rg},
|
2814 |
+
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
|
2815 |
+
month = nov,
|
2816 |
+
year = "2020",
|
2817 |
+
address = "Online",
|
2818 |
+
publisher = "Association for Computational Linguistics",
|
2819 |
+
url = "https://aclanthology.org/2020.wmt-1.139",
|
2820 |
+
pages = "1174--1182",
|
2821 |
+
}
|
2822 |
+
```
|
2823 |
+
|
2824 |
+
## Acknowledgements
|
2825 |
+
|
2826 |
+
The work is supported by the [HPLT project](https://hplt-project.org/), funded by the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070350. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland, and the [EuroHPC supercomputer LUMI](https://www.lumi-supercomputer.eu/).
|
2827 |
+
|
2828 |
+
## Model conversion info
|
2829 |
+
|
2830 |
+
* transformers version: 4.45.1
|
2831 |
+
* OPUS-MT git hash: 0882077
|
2832 |
+
* port time: Tue Oct 8 10:01:07 EEST 2024
|
2833 |
+
* port machine: LM0-400-22516.local
|
benchmark_results.txt
ADDED
@@ -0,0 +1,227 @@
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1 |
+
multi-multi tatoeba-test-v2020-07-28-v2023-09-26 0.67078 48.7 10000 86220
|
2 |
+
deu-afr flores101-devtest 0.57287 26.0 1012 25740
|
3 |
+
deu-eng flores101-devtest 0.66660 40.9 1012 24721
|
4 |
+
deu-nld flores101-devtest 0.55423 23.6 1012 25467
|
5 |
+
eng-afr flores101-devtest 0.67793 40.0 1012 25740
|
6 |
+
eng-deu flores101-devtest 0.64295 37.2 1012 25094
|
7 |
+
eng-nld flores101-devtest 0.57690 26.2 1012 25467
|
8 |
+
fra-ltz flores101-devtest 0.49430 17.3 1012 25087
|
9 |
+
fra-nld flores101-devtest 0.54318 22.2 1012 25467
|
10 |
+
por-deu flores101-devtest 0.58851 29.8 1012 25094
|
11 |
+
por-nld flores101-devtest 0.54571 22.6 1012 25467
|
12 |
+
spa-nld flores101-devtest 0.50968 17.5 1012 25467
|
13 |
+
deu-afr flores200-devtest 0.57725 26.2 1012 25740
|
14 |
+
deu-eng flores200-devtest 0.67043 41.5 1012 24721
|
15 |
+
deu-lim flores200-devtest 0.21909 2.4 1012 24889
|
16 |
+
deu-ltz flores200-devtest 0.54626 21.6 1012 25087
|
17 |
+
deu-nld flores200-devtest 0.55679 24.0 1012 25467
|
18 |
+
deu-tpi flores200-devtest 0.39146 13.5 1012 35240
|
19 |
+
eng-afr flores200-devtest 0.68115 40.2 1012 25740
|
20 |
+
eng-deu flores200-devtest 0.64561 37.4 1012 25094
|
21 |
+
eng-lim flores200-devtest 0.30658 4.7 1012 24889
|
22 |
+
eng-ltz flores200-devtest 0.54932 22.0 1012 25087
|
23 |
+
eng-nld flores200-devtest 0.58124 26.8 1012 25467
|
24 |
+
eng-tpi flores200-devtest 0.40338 15.9 1012 35240
|
25 |
+
fra-afr flores200-devtest 0.57320 26.4 1012 25740
|
26 |
+
fra-deu flores200-devtest 0.58974 29.5 1012 25094
|
27 |
+
fra-eng flores200-devtest 0.68106 43.7 1012 24721
|
28 |
+
fra-lim flores200-devtest 0.31100 4.5 1012 24889
|
29 |
+
fra-ltz flores200-devtest 0.49618 17.8 1012 25087
|
30 |
+
fra-nld flores200-devtest 0.54623 22.5 1012 25467
|
31 |
+
fra-tpi flores200-devtest 0.39334 13.7 1012 35240
|
32 |
+
por-afr flores200-devtest 0.58408 27.6 1012 25740
|
33 |
+
por-deu flores200-devtest 0.59121 30.4 1012 25094
|
34 |
+
por-eng flores200-devtest 0.71418 48.3 1012 24721
|
35 |
+
por-lim flores200-devtest 0.30653 4.6 1012 24889
|
36 |
+
por-ltz flores200-devtest 0.39073 12.3 1012 25087
|
37 |
+
por-nld flores200-devtest 0.54828 22.9 1012 25467
|
38 |
+
por-tpi flores200-devtest 0.38929 13.7 1012 35240
|
39 |
+
spa-afr flores200-devtest 0.51514 17.8 1012 25740
|
40 |
+
spa-deu flores200-devtest 0.53603 21.4 1012 25094
|
41 |
+
spa-eng flores200-devtest 0.58604 28.2 1012 24721
|
42 |
+
spa-lim flores200-devtest 0.28237 3.2 1012 24889
|
43 |
+
spa-ltz flores200-devtest 0.35047 8.5 1012 25087
|
44 |
+
spa-nld flores200-devtest 0.51244 17.9 1012 25467
|
45 |
+
spa-tpi flores200-devtest 0.37967 12.2 1012 35240
|
46 |
+
deu-eng generaltest2022 0.55777 30.6 1984 37634
|
47 |
+
eng-deu generaltest2022 0.60792 33.0 2037 38914
|
48 |
+
fra-deu generaltest2022 0.67039 44.5 2006 37696
|
49 |
+
deu-eng multi30k_task2_test_2016 0.21562 4.1 5000 67382
|
50 |
+
eng-deu multi30k_task2_test_2016 0.26922 2.6 5000 51501
|
51 |
+
deu-eng multi30k_test_2016_flickr 0.60981 40.1 1000 12955
|
52 |
+
eng-deu multi30k_test_2016_flickr 0.64153 34.9 1000 12106
|
53 |
+
fra-deu multi30k_test_2016_flickr 0.61781 32.1 1000 12106
|
54 |
+
fra-eng multi30k_test_2016_flickr 0.66703 47.9 1000 12955
|
55 |
+
deu-eng multi30k_test_2017_flickr 0.63624 41.0 1000 11374
|
56 |
+
eng-deu multi30k_test_2017_flickr 0.63423 34.6 1000 10755
|
57 |
+
fra-deu multi30k_test_2017_flickr 0.60084 29.7 1000 10755
|
58 |
+
fra-eng multi30k_test_2017_flickr 0.69254 50.4 1000 11374
|
59 |
+
deu-eng multi30k_test_2017_mscoco 0.55790 32.5 461 5231
|
60 |
+
eng-deu multi30k_test_2017_mscoco 0.57491 28.6 461 5158
|
61 |
+
fra-deu multi30k_test_2017_mscoco 0.56108 26.4 461 5158
|
62 |
+
fra-eng multi30k_test_2017_mscoco 0.68212 49.1 461 5231
|
63 |
+
deu-eng multi30k_test_2018_flickr 0.59322 36.6 1071 14689
|
64 |
+
eng-deu multi30k_test_2018_flickr 0.59858 30.0 1071 13703
|
65 |
+
fra-deu multi30k_test_2018_flickr 0.55667 24.7 1071 13703
|
66 |
+
fra-eng multi30k_test_2018_flickr 0.64702 43.4 1071 14689
|
67 |
+
fra-eng newsdiscusstest2015 0.61399 38.5 1500 26982
|
68 |
+
deu-eng newssyscomb2009 0.55180 28.8 502 11818
|
69 |
+
eng-deu newssyscomb2009 0.53676 22.9 502 11271
|
70 |
+
fra-deu newssyscomb2009 0.53733 23.9 502 11271
|
71 |
+
fra-eng newssyscomb2009 0.57219 31.1 502 11818
|
72 |
+
spa-deu newssyscomb2009 0.53056 22.0 502 11271
|
73 |
+
spa-eng newssyscomb2009 0.57225 30.8 502 11818
|
74 |
+
deu-eng newstest2008 0.54506 26.9 2051 49380
|
75 |
+
eng-deu newstest2008 0.53077 23.1 2051 47447
|
76 |
+
fra-deu newstest2008 0.53204 22.9 2051 47447
|
77 |
+
fra-eng newstest2008 0.54320 26.4 2051 49380
|
78 |
+
spa-deu newstest2008 0.52066 21.6 2051 47447
|
79 |
+
spa-eng newstest2008 0.55305 27.9 2051 49380
|
80 |
+
deu-eng newstest2009 0.53773 26.2 2525 65399
|
81 |
+
eng-deu newstest2009 0.53217 22.3 2525 62816
|
82 |
+
fra-deu newstest2009 0.52995 22.9 2525 62816
|
83 |
+
fra-eng newstest2009 0.56663 30.0 2525 65399
|
84 |
+
spa-deu newstest2009 0.52586 22.1 2525 62816
|
85 |
+
spa-eng newstest2009 0.56756 29.9 2525 65399
|
86 |
+
deu-eng newstest2010 0.58365 30.4 2489 61711
|
87 |
+
eng-deu newstest2010 0.54917 25.7 2489 61503
|
88 |
+
fra-deu newstest2010 0.53904 24.3 2489 61503
|
89 |
+
fra-eng newstest2010 0.59241 32.4 2489 61711
|
90 |
+
spa-deu newstest2010 0.55378 26.2 2489 61503
|
91 |
+
spa-eng newstest2010 0.61316 35.8 2489 61711
|
92 |
+
deu-eng newstest2011 0.54907 26.1 3003 74681
|
93 |
+
eng-deu newstest2011 0.52873 23.0 3003 72981
|
94 |
+
fra-deu newstest2011 0.52977 23.0 3003 72981
|
95 |
+
fra-eng newstest2011 0.59565 32.8 3003 74681
|
96 |
+
spa-deu newstest2011 0.53095 23.4 3003 72981
|
97 |
+
spa-eng newstest2011 0.59513 33.3 3003 74681
|
98 |
+
deu-eng newstest2012 0.56230 28.1 3003 72812
|
99 |
+
eng-deu newstest2012 0.52871 23.7 3003 72886
|
100 |
+
fra-deu newstest2012 0.53035 24.1 3003 72886
|
101 |
+
fra-eng newstest2012 0.59137 33.0 3003 72812
|
102 |
+
spa-deu newstest2012 0.53438 24.3 3003 72886
|
103 |
+
spa-eng newstest2012 0.62058 37.0 3003 72812
|
104 |
+
deu-eng newstest2013 0.57940 31.5 3000 64505
|
105 |
+
eng-deu newstest2013 0.55718 27.5 3000 63737
|
106 |
+
fra-deu newstest2013 0.54408 25.6 3000 63737
|
107 |
+
fra-eng newstest2013 0.59151 33.9 3000 64505
|
108 |
+
spa-deu newstest2013 0.55215 26.2 3000 63737
|
109 |
+
spa-eng newstest2013 0.60465 34.4 3000 64505
|
110 |
+
deu-eng newstest2014 0.59723 33.1 3003 67337
|
111 |
+
eng-deu newstest2014 0.59127 28.5 3003 62688
|
112 |
+
fra-eng newstest2014 0.63411 38.0 3003 70708
|
113 |
+
deu-eng newstest2015 0.59799 33.7 2169 46443
|
114 |
+
eng-deu newstest2015 0.59977 32.0 2169 44260
|
115 |
+
deu-eng newstest2016 0.65039 40.4 2999 64119
|
116 |
+
eng-deu newstest2016 0.64144 37.9 2999 62669
|
117 |
+
deu-eng newstest2017 0.60921 35.3 3004 64399
|
118 |
+
eng-deu newstest2017 0.59114 30.4 3004 61287
|
119 |
+
deu-eng newstest2018 0.66680 42.6 2998 67012
|
120 |
+
eng-deu newstest2018 0.69428 45.8 2998 64276
|
121 |
+
deu-eng newstest2019 0.63482 39.1 2000 39227
|
122 |
+
eng-deu newstest2019 0.66430 42.0 1997 48746
|
123 |
+
fra-deu newstest2019 0.60993 29.4 1701 36446
|
124 |
+
deu-eng newstest2020 0.60403 34.0 785 38220
|
125 |
+
eng-deu newstest2020 0.60255 32.3 1418 52383
|
126 |
+
fra-deu newstest2020 0.61470 29.2 1619 30265
|
127 |
+
deu-eng newstest2021 0.59738 31.9 1000 20180
|
128 |
+
eng-deu newstest2021 0.56399 26.1 1002 27970
|
129 |
+
fra-deu newstest2021 0.66155 40.0 1026 26077
|
130 |
+
deu-eng newstestALL2020 0.60403 34.0 785 38220
|
131 |
+
eng-deu newstestALL2020 0.60255 32.3 1418 52383
|
132 |
+
deu-eng newstestB2020 0.60520 34.2 785 37696
|
133 |
+
eng-deu newstestB2020 0.59226 31.6 1418 53092
|
134 |
+
deu-afr ntrex128 0.57109 27.9 1997 50050
|
135 |
+
deu-eng ntrex128 0.62043 34.5 1997 47673
|
136 |
+
deu-ltz ntrex128 0.47642 15.4 1997 49763
|
137 |
+
deu-nld ntrex128 0.56777 27.6 1997 51884
|
138 |
+
eng-afr ntrex128 0.68616 44.1 1997 50050
|
139 |
+
eng-deu ntrex128 0.58743 30.2 1997 48761
|
140 |
+
eng-ltz ntrex128 0.50083 18.0 1997 49763
|
141 |
+
eng-nld ntrex128 0.61041 33.8 1997 51884
|
142 |
+
fra-afr ntrex128 0.55607 26.5 1997 50050
|
143 |
+
fra-deu ntrex128 0.53269 23.6 1997 48761
|
144 |
+
fra-eng ntrex128 0.61058 34.4 1997 47673
|
145 |
+
fra-ltz ntrex128 0.41312 12.0 1997 49763
|
146 |
+
fra-nld ntrex128 0.54615 25.2 1997 51884
|
147 |
+
por-afr ntrex128 0.58296 29.2 1997 50050
|
148 |
+
por-deu ntrex128 0.54944 24.7 1997 48761
|
149 |
+
por-eng ntrex128 0.65002 39.6 1997 47673
|
150 |
+
por-ltz ntrex128 0.35212 9.5 1997 49763
|
151 |
+
por-nld ntrex128 0.56384 28.1 1997 51884
|
152 |
+
spa-afr ntrex128 0.57772 27.7 1997 50050
|
153 |
+
spa-deu ntrex128 0.54561 24.0 1997 48761
|
154 |
+
spa-eng ntrex128 0.64305 37.3 1997 47673
|
155 |
+
spa-ltz ntrex128 0.35540 9.7 1997 49763
|
156 |
+
spa-nld ntrex128 0.56397 27.8 1997 51884
|
157 |
+
deu-ltz tatoeba-test-v2020-07-28 0.52660 32.3 337 2135
|
158 |
+
deu-nds tatoeba-test-v2020-07-28 0.44577 19.8 10000 76144
|
159 |
+
deu-yid tatoeba-test-v2020-07-28 0.15568 2.3 556 3425
|
160 |
+
eng-deu tatoeba-test-v2020-07-28 0.63613 43.0 10000 83347
|
161 |
+
eng-fry tatoeba-test-v2020-07-28 0.40596 12.8 205 1529
|
162 |
+
eng-ltz tatoeba-test-v2020-07-28 0.64082 45.2 283 1733
|
163 |
+
eng-nld tatoeba-test-v2020-07-28 0.71526 55.2 10000 71436
|
164 |
+
eng-yid tatoeba-test-v2020-07-28 0.37185 9.0 1168 8094
|
165 |
+
fra-nds tatoeba-test-v2020-07-28 0.39471 15.9 831 5571
|
166 |
+
fra-nld tatoeba-test-v2020-07-28 0.66599 48.8 10000 69845
|
167 |
+
fra-yid tatoeba-test-v2020-07-28 0.40041 9.8 230 1358
|
168 |
+
por-eng tatoeba-test-v2020-07-28 0.76063 62.8 10000 75240
|
169 |
+
spa-deu tatoeba-test-v2020-07-28 0.67395 48.3 10000 81214
|
170 |
+
spa-eng tatoeba-test-v2020-07-28 0.73258 58.9 10000 79376
|
171 |
+
spa-nld tatoeba-test-v2020-07-28 0.68457 50.6 10000 78395
|
172 |
+
deu-deu tatoeba-test-v2021-03-30 0.59934 35.0 2500 20806
|
173 |
+
deu-frr tatoeba-test-v2021-03-30 0.18528 0.7 279 1861
|
174 |
+
deu-gos tatoeba-test-v2021-03-30 0.27291 5.1 210 1140
|
175 |
+
deu-ltz tatoeba-test-v2021-03-30 0.52966 33.0 350 2227
|
176 |
+
deu-nds tatoeba-test-v2021-03-30 0.44577 19.8 10000 76144
|
177 |
+
deu-nld tatoeba-test-v2021-03-30 0.71040 54.1 10124 74568
|
178 |
+
deu-yid tatoeba-test-v2021-03-30 0.15883 2.2 830 5207
|
179 |
+
eng-deu tatoeba-test-v2021-03-30 0.62946 41.8 12664 107460
|
180 |
+
eng-gos tatoeba-test-v2021-03-30 0.21072 2.9 1193 5711
|
181 |
+
eng-gsw tatoeba-test-v2021-03-30 0.20552 0.9 210 1013
|
182 |
+
eng-ltz tatoeba-test-v2021-03-30 0.64514 45.8 299 1833
|
183 |
+
eng-nld tatoeba-test-v2021-03-30 0.70834 54.3 11660 83811
|
184 |
+
fra-eng tatoeba-test-v2021-03-30 0.71919 57.3 10892 85143
|
185 |
+
por-eng tatoeba-test-v2021-03-30 0.76398 63.4 11574 87523
|
186 |
+
spa-deu tatoeba-test-v2021-03-30 0.67408 48.3 10138 82525
|
187 |
+
spa-eng tatoeba-test-v2021-03-30 0.73396 59.0 11940 96122
|
188 |
+
spa-nld tatoeba-test-v2021-03-30 0.68521 50.7 10083 78945
|
189 |
+
spa-yid tatoeba-test-v2021-03-30 0.37513 10.4 336 2076
|
190 |
+
deu-afr tatoeba-test-v2021-08-07 0.72039 56.7 1583 9507
|
191 |
+
deu-deu tatoeba-test-v2021-08-07 0.59545 33.7 2500 20806
|
192 |
+
deu-eng tatoeba-test-v2021-08-07 0.66015 48.6 17565 149462
|
193 |
+
deu-frr tatoeba-test-v2021-08-07 0.18304 0.7 278 1855
|
194 |
+
deu-gos tatoeba-test-v2021-08-07 0.27546 5.4 207 1135
|
195 |
+
deu-ltz tatoeba-test-v2021-08-07 0.53760 34.2 347 2206
|
196 |
+
deu-nds tatoeba-test-v2021-08-07 0.44534 20.1 9999 76137
|
197 |
+
deu-nld tatoeba-test-v2021-08-07 0.71276 54.4 10218 75235
|
198 |
+
deu-swg tatoeba-test-v2021-08-07 0.16214 0.2 1523 15448
|
199 |
+
deu-yid tatoeba-test-v2021-08-07 0.15599 1.8 853 5355
|
200 |
+
eng-afr tatoeba-test-v2021-08-07 0.72087 56.6 1374 10317
|
201 |
+
eng-deu tatoeba-test-v2021-08-07 0.62971 41.4 17565 151568
|
202 |
+
eng-eng tatoeba-test-v2021-08-07 0.80306 58.0 12062 115106
|
203 |
+
eng-fry tatoeba-test-v2021-08-07 0.40324 13.8 220 1600
|
204 |
+
eng-gos tatoeba-test-v2021-08-07 0.20426 1.1 1154 5525
|
205 |
+
eng-gsw tatoeba-test-v2021-08-07 0.20266 1.0 205 984
|
206 |
+
eng-ltz tatoeba-test-v2021-08-07 0.64423 45.8 293 1828
|
207 |
+
eng-nds tatoeba-test-v2021-08-07 0.46446 22.2 2500 18264
|
208 |
+
eng-nld tatoeba-test-v2021-08-07 0.71190 54.5 12696 91796
|
209 |
+
eng-yid tatoeba-test-v2021-08-07 0.37401 9.5 2483 16395
|
210 |
+
fra-deu tatoeba-test-v2021-08-07 0.68991 50.3 12418 100545
|
211 |
+
fra-eng tatoeba-test-v2021-08-07 0.72564 58.0 12681 101754
|
212 |
+
fra-nds tatoeba-test-v2021-08-07 0.39555 16.2 857 5760
|
213 |
+
fra-nld tatoeba-test-v2021-08-07 0.67078 48.7 11548 82164
|
214 |
+
fra-yid tatoeba-test-v2021-08-07 0.39100 10.0 384 2381
|
215 |
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por-deu tatoeba-test-v2021-08-07 0.68437 48.7 10000 81246
|
216 |
+
por-eng tatoeba-test-v2021-08-07 0.77081 64.3 13222 105351
|
217 |
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por-nds tatoeba-test-v2021-08-07 0.45864 20.7 207 1292
|
218 |
+
por-nld tatoeba-test-v2021-08-07 0.69865 52.8 2500 17816
|
219 |
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spa-afr tatoeba-test-v2021-08-07 0.77148 63.3 448 3044
|
220 |
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spa-deu tatoeba-test-v2021-08-07 0.68037 49.1 10521 86430
|
221 |
+
spa-eng tatoeba-test-v2021-08-07 0.74575 60.2 16583 138123
|
222 |
+
spa-nds tatoeba-test-v2021-08-07 0.43154 18.5 923 5941
|
223 |
+
spa-nld tatoeba-test-v2021-08-07 0.68988 51.1 10113 79162
|
224 |
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spa-yid tatoeba-test-v2021-08-07 0.34472 8.9 407 2599
|
225 |
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fra-eng tico19-test 0.62059 39.2 2100 56323
|
226 |
+
por-eng tico19-test 0.73896 50.3 2100 56315
|
227 |
+
spa-eng tico19-test 0.72923 49.6 2100 56315
|
benchmark_translations.zip
ADDED
File without changes
|
config.json
ADDED
@@ -0,0 +1,41 @@
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1 |
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{
|
2 |
+
"_name_or_path": "pytorch-models/opus-mt-tc-bible-big-deu_eng_fra_por_spa-gmw",
|
3 |
+
"activation_dropout": 0.0,
|
4 |
+
"activation_function": "relu",
|
5 |
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"architectures": [
|
6 |
+
"MarianMTModel"
|
7 |
+
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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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|
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"decoder_layers": 6,
|
16 |
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"decoder_start_token_id": 48182,
|
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|
18 |
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|
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|
20 |
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|
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|
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|
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"eos_token_id": 453,
|
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|
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"init_std": 0.02,
|
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"is_encoder_decoder": true,
|
27 |
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"max_length": null,
|
28 |
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"max_position_embeddings": 1024,
|
29 |
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"model_type": "marian",
|
30 |
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"normalize_embedding": false,
|
31 |
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"num_beams": null,
|
32 |
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"num_hidden_layers": 6,
|
33 |
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|
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|
35 |
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"share_encoder_decoder_embeddings": true,
|
36 |
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"static_position_embeddings": true,
|
37 |
+
"torch_dtype": "float32",
|
38 |
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"transformers_version": "4.45.1",
|
39 |
+
"use_cache": true,
|
40 |
+
"vocab_size": 48183
|
41 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,16 @@
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|
1 |
+
{
|
2 |
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"_from_model_config": true,
|
3 |
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"bad_words_ids": [
|
4 |
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[
|
5 |
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48182
|
6 |
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|
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|
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"bos_token_id": 0,
|
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|
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"eos_token_id": 453,
|
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|
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"max_length": 512,
|
13 |
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"num_beams": 4,
|
14 |
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"pad_token_id": 48182,
|
15 |
+
"transformers_version": "4.45.1"
|
16 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
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version https://git-lfs.github.com/spec/v1
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pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
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|
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|
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|
1 |
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source.spm
ADDED
@@ -0,0 +1,3 @@
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1 |
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|
special_tokens_map.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}
|
target.spm
ADDED
@@ -0,0 +1,3 @@
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1 |
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|
tokenizer_config.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"source_lang": "deu+eng+fra+por+spa", "target_lang": "gmw", "unk_token": "<unk>", "eos_token": "</s>", "pad_token": "<pad>", "model_max_length": 512, "sp_model_kwargs": {}, "separate_vocabs": false, "special_tokens_map_file": null, "name_or_path": "marian-models/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30/deu+eng+fra+por+spa-gmw", "tokenizer_class": "MarianTokenizer"}
|
vocab.json
ADDED
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|