Initial commit
Browse files- .gitattributes +1 -0
- README.md +1587 -0
- benchmark_results.txt +129 -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 +1,1587 @@
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|
1 |
+
---
|
2 |
+
library_name: transformers
|
3 |
+
language:
|
4 |
+
- aa
|
5 |
+
- am
|
6 |
+
- ar
|
7 |
+
- arc
|
8 |
+
- bcw
|
9 |
+
- byn
|
10 |
+
- cop
|
11 |
+
- daa
|
12 |
+
- de
|
13 |
+
- dsh
|
14 |
+
- en
|
15 |
+
- es
|
16 |
+
- fr
|
17 |
+
- gde
|
18 |
+
- gnd
|
19 |
+
- ha
|
20 |
+
- hbo
|
21 |
+
- he
|
22 |
+
- hig
|
23 |
+
- irk
|
24 |
+
- jpa
|
25 |
+
- kab
|
26 |
+
- ker
|
27 |
+
- kqp
|
28 |
+
- ktb
|
29 |
+
- kxc
|
30 |
+
- lln
|
31 |
+
- lme
|
32 |
+
- meq
|
33 |
+
- mfh
|
34 |
+
- mfi
|
35 |
+
- mfk
|
36 |
+
- mif
|
37 |
+
- mpg
|
38 |
+
- mqb
|
39 |
+
- mt
|
40 |
+
- muy
|
41 |
+
- oar
|
42 |
+
- om
|
43 |
+
- pbi
|
44 |
+
- phn
|
45 |
+
- pt
|
46 |
+
- rif
|
47 |
+
- sgw
|
48 |
+
- shi
|
49 |
+
- shy
|
50 |
+
- so
|
51 |
+
- sur
|
52 |
+
- syc
|
53 |
+
- syr
|
54 |
+
- taq
|
55 |
+
- thv
|
56 |
+
- ti
|
57 |
+
- tig
|
58 |
+
- tmc
|
59 |
+
- tmh
|
60 |
+
- tmr
|
61 |
+
- ttr
|
62 |
+
- tzm
|
63 |
+
- wal
|
64 |
+
- xed
|
65 |
+
- zgh
|
66 |
+
|
67 |
+
tags:
|
68 |
+
- translation
|
69 |
+
- opus-mt-tc-bible
|
70 |
+
|
71 |
+
license: apache-2.0
|
72 |
+
model-index:
|
73 |
+
- name: opus-mt-tc-bible-big-afa-deu_eng_fra_por_spa
|
74 |
+
results:
|
75 |
+
- task:
|
76 |
+
name: Translation acm-deu
|
77 |
+
type: translation
|
78 |
+
args: acm-deu
|
79 |
+
dataset:
|
80 |
+
name: flores200-devtest
|
81 |
+
type: flores200-devtest
|
82 |
+
args: acm-deu
|
83 |
+
metrics:
|
84 |
+
- name: BLEU
|
85 |
+
type: bleu
|
86 |
+
value: 17.6
|
87 |
+
- name: chr-F
|
88 |
+
type: chrf
|
89 |
+
value: 0.48947
|
90 |
+
- task:
|
91 |
+
name: Translation acm-eng
|
92 |
+
type: translation
|
93 |
+
args: acm-eng
|
94 |
+
dataset:
|
95 |
+
name: flores200-devtest
|
96 |
+
type: flores200-devtest
|
97 |
+
args: acm-eng
|
98 |
+
metrics:
|
99 |
+
- name: BLEU
|
100 |
+
type: bleu
|
101 |
+
value: 28.5
|
102 |
+
- name: chr-F
|
103 |
+
type: chrf
|
104 |
+
value: 0.56799
|
105 |
+
- task:
|
106 |
+
name: Translation acm-fra
|
107 |
+
type: translation
|
108 |
+
args: acm-fra
|
109 |
+
dataset:
|
110 |
+
name: flores200-devtest
|
111 |
+
type: flores200-devtest
|
112 |
+
args: acm-fra
|
113 |
+
metrics:
|
114 |
+
- name: BLEU
|
115 |
+
type: bleu
|
116 |
+
value: 26.1
|
117 |
+
- name: chr-F
|
118 |
+
type: chrf
|
119 |
+
value: 0.53577
|
120 |
+
- task:
|
121 |
+
name: Translation acm-por
|
122 |
+
type: translation
|
123 |
+
args: acm-por
|
124 |
+
dataset:
|
125 |
+
name: flores200-devtest
|
126 |
+
type: flores200-devtest
|
127 |
+
args: acm-por
|
128 |
+
metrics:
|
129 |
+
- name: BLEU
|
130 |
+
type: bleu
|
131 |
+
value: 23.9
|
132 |
+
- name: chr-F
|
133 |
+
type: chrf
|
134 |
+
value: 0.52441
|
135 |
+
- task:
|
136 |
+
name: Translation acm-spa
|
137 |
+
type: translation
|
138 |
+
args: acm-spa
|
139 |
+
dataset:
|
140 |
+
name: flores200-devtest
|
141 |
+
type: flores200-devtest
|
142 |
+
args: acm-spa
|
143 |
+
metrics:
|
144 |
+
- name: BLEU
|
145 |
+
type: bleu
|
146 |
+
value: 18.2
|
147 |
+
- name: chr-F
|
148 |
+
type: chrf
|
149 |
+
value: 0.46985
|
150 |
+
- task:
|
151 |
+
name: Translation amh-deu
|
152 |
+
type: translation
|
153 |
+
args: amh-deu
|
154 |
+
dataset:
|
155 |
+
name: flores200-devtest
|
156 |
+
type: flores200-devtest
|
157 |
+
args: amh-deu
|
158 |
+
metrics:
|
159 |
+
- name: BLEU
|
160 |
+
type: bleu
|
161 |
+
value: 12.6
|
162 |
+
- name: chr-F
|
163 |
+
type: chrf
|
164 |
+
value: 0.41553
|
165 |
+
- task:
|
166 |
+
name: Translation amh-eng
|
167 |
+
type: translation
|
168 |
+
args: amh-eng
|
169 |
+
dataset:
|
170 |
+
name: flores200-devtest
|
171 |
+
type: flores200-devtest
|
172 |
+
args: amh-eng
|
173 |
+
metrics:
|
174 |
+
- name: BLEU
|
175 |
+
type: bleu
|
176 |
+
value: 22.5
|
177 |
+
- name: chr-F
|
178 |
+
type: chrf
|
179 |
+
value: 0.49333
|
180 |
+
- task:
|
181 |
+
name: Translation amh-fra
|
182 |
+
type: translation
|
183 |
+
args: amh-fra
|
184 |
+
dataset:
|
185 |
+
name: flores200-devtest
|
186 |
+
type: flores200-devtest
|
187 |
+
args: amh-fra
|
188 |
+
metrics:
|
189 |
+
- name: BLEU
|
190 |
+
type: bleu
|
191 |
+
value: 17.8
|
192 |
+
- name: chr-F
|
193 |
+
type: chrf
|
194 |
+
value: 0.44890
|
195 |
+
- task:
|
196 |
+
name: Translation amh-por
|
197 |
+
type: translation
|
198 |
+
args: amh-por
|
199 |
+
dataset:
|
200 |
+
name: flores200-devtest
|
201 |
+
type: flores200-devtest
|
202 |
+
args: amh-por
|
203 |
+
metrics:
|
204 |
+
- name: BLEU
|
205 |
+
type: bleu
|
206 |
+
value: 16.5
|
207 |
+
- name: chr-F
|
208 |
+
type: chrf
|
209 |
+
value: 0.43771
|
210 |
+
- task:
|
211 |
+
name: Translation amh-spa
|
212 |
+
type: translation
|
213 |
+
args: amh-spa
|
214 |
+
dataset:
|
215 |
+
name: flores200-devtest
|
216 |
+
type: flores200-devtest
|
217 |
+
args: amh-spa
|
218 |
+
metrics:
|
219 |
+
- name: BLEU
|
220 |
+
type: bleu
|
221 |
+
value: 12.8
|
222 |
+
- name: chr-F
|
223 |
+
type: chrf
|
224 |
+
value: 0.39526
|
225 |
+
- task:
|
226 |
+
name: Translation apc-deu
|
227 |
+
type: translation
|
228 |
+
args: apc-deu
|
229 |
+
dataset:
|
230 |
+
name: flores200-devtest
|
231 |
+
type: flores200-devtest
|
232 |
+
args: apc-deu
|
233 |
+
metrics:
|
234 |
+
- name: BLEU
|
235 |
+
type: bleu
|
236 |
+
value: 16.0
|
237 |
+
- name: chr-F
|
238 |
+
type: chrf
|
239 |
+
value: 0.47480
|
240 |
+
- task:
|
241 |
+
name: Translation apc-eng
|
242 |
+
type: translation
|
243 |
+
args: apc-eng
|
244 |
+
dataset:
|
245 |
+
name: flores200-devtest
|
246 |
+
type: flores200-devtest
|
247 |
+
args: apc-eng
|
248 |
+
metrics:
|
249 |
+
- name: BLEU
|
250 |
+
type: bleu
|
251 |
+
value: 28.1
|
252 |
+
- name: chr-F
|
253 |
+
type: chrf
|
254 |
+
value: 0.56075
|
255 |
+
- task:
|
256 |
+
name: Translation apc-fra
|
257 |
+
type: translation
|
258 |
+
args: apc-fra
|
259 |
+
dataset:
|
260 |
+
name: flores200-devtest
|
261 |
+
type: flores200-devtest
|
262 |
+
args: apc-fra
|
263 |
+
metrics:
|
264 |
+
- name: BLEU
|
265 |
+
type: bleu
|
266 |
+
value: 24.6
|
267 |
+
- name: chr-F
|
268 |
+
type: chrf
|
269 |
+
value: 0.52325
|
270 |
+
- task:
|
271 |
+
name: Translation apc-por
|
272 |
+
type: translation
|
273 |
+
args: apc-por
|
274 |
+
dataset:
|
275 |
+
name: flores200-devtest
|
276 |
+
type: flores200-devtest
|
277 |
+
args: apc-por
|
278 |
+
metrics:
|
279 |
+
- name: BLEU
|
280 |
+
type: bleu
|
281 |
+
value: 22.9
|
282 |
+
- name: chr-F
|
283 |
+
type: chrf
|
284 |
+
value: 0.51055
|
285 |
+
- task:
|
286 |
+
name: Translation apc-spa
|
287 |
+
type: translation
|
288 |
+
args: apc-spa
|
289 |
+
dataset:
|
290 |
+
name: flores200-devtest
|
291 |
+
type: flores200-devtest
|
292 |
+
args: apc-spa
|
293 |
+
metrics:
|
294 |
+
- name: BLEU
|
295 |
+
type: bleu
|
296 |
+
value: 17.2
|
297 |
+
- name: chr-F
|
298 |
+
type: chrf
|
299 |
+
value: 0.45634
|
300 |
+
- task:
|
301 |
+
name: Translation arz-deu
|
302 |
+
type: translation
|
303 |
+
args: arz-deu
|
304 |
+
dataset:
|
305 |
+
name: flores200-devtest
|
306 |
+
type: flores200-devtest
|
307 |
+
args: arz-deu
|
308 |
+
metrics:
|
309 |
+
- name: BLEU
|
310 |
+
type: bleu
|
311 |
+
value: 14.1
|
312 |
+
- name: chr-F
|
313 |
+
type: chrf
|
314 |
+
value: 0.45844
|
315 |
+
- task:
|
316 |
+
name: Translation arz-eng
|
317 |
+
type: translation
|
318 |
+
args: arz-eng
|
319 |
+
dataset:
|
320 |
+
name: flores200-devtest
|
321 |
+
type: flores200-devtest
|
322 |
+
args: arz-eng
|
323 |
+
metrics:
|
324 |
+
- name: BLEU
|
325 |
+
type: bleu
|
326 |
+
value: 22.7
|
327 |
+
- name: chr-F
|
328 |
+
type: chrf
|
329 |
+
value: 0.52534
|
330 |
+
- task:
|
331 |
+
name: Translation arz-fra
|
332 |
+
type: translation
|
333 |
+
args: arz-fra
|
334 |
+
dataset:
|
335 |
+
name: flores200-devtest
|
336 |
+
type: flores200-devtest
|
337 |
+
args: arz-fra
|
338 |
+
metrics:
|
339 |
+
- name: BLEU
|
340 |
+
type: bleu
|
341 |
+
value: 21.8
|
342 |
+
- name: chr-F
|
343 |
+
type: chrf
|
344 |
+
value: 0.50336
|
345 |
+
- task:
|
346 |
+
name: Translation arz-por
|
347 |
+
type: translation
|
348 |
+
args: arz-por
|
349 |
+
dataset:
|
350 |
+
name: flores200-devtest
|
351 |
+
type: flores200-devtest
|
352 |
+
args: arz-por
|
353 |
+
metrics:
|
354 |
+
- name: BLEU
|
355 |
+
type: bleu
|
356 |
+
value: 20.0
|
357 |
+
- name: chr-F
|
358 |
+
type: chrf
|
359 |
+
value: 0.48741
|
360 |
+
- task:
|
361 |
+
name: Translation arz-spa
|
362 |
+
type: translation
|
363 |
+
args: arz-spa
|
364 |
+
dataset:
|
365 |
+
name: flores200-devtest
|
366 |
+
type: flores200-devtest
|
367 |
+
args: arz-spa
|
368 |
+
metrics:
|
369 |
+
- name: BLEU
|
370 |
+
type: bleu
|
371 |
+
value: 15.8
|
372 |
+
- name: chr-F
|
373 |
+
type: chrf
|
374 |
+
value: 0.44516
|
375 |
+
- task:
|
376 |
+
name: Translation hau-eng
|
377 |
+
type: translation
|
378 |
+
args: hau-eng
|
379 |
+
dataset:
|
380 |
+
name: flores200-devtest
|
381 |
+
type: flores200-devtest
|
382 |
+
args: hau-eng
|
383 |
+
metrics:
|
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440 |
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500 |
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503 |
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511 |
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514 |
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515 |
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518 |
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522 |
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523 |
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525 |
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530 |
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537 |
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560 |
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585 |
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600 |
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601 |
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605 |
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615 |
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616 |
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617 |
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618 |
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620 |
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622 |
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630 |
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631 |
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635 |
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636 |
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637 |
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638 |
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dataset:
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860 |
+
name: flores101-devtest
|
861 |
+
type: flores_101
|
862 |
+
args: mlt por devtest
|
863 |
+
metrics:
|
864 |
+
- name: BLEU
|
865 |
+
type: bleu
|
866 |
+
value: 31.8
|
867 |
+
- name: chr-F
|
868 |
+
type: chrf
|
869 |
+
value: 0.59863
|
870 |
+
- task:
|
871 |
+
name: Translation amh-eng
|
872 |
+
type: translation
|
873 |
+
args: amh-eng
|
874 |
+
dataset:
|
875 |
+
name: ntrex128
|
876 |
+
type: ntrex128
|
877 |
+
args: amh-eng
|
878 |
+
metrics:
|
879 |
+
- name: BLEU
|
880 |
+
type: bleu
|
881 |
+
value: 15.0
|
882 |
+
- name: chr-F
|
883 |
+
type: chrf
|
884 |
+
value: 0.42042
|
885 |
+
- task:
|
886 |
+
name: Translation amh-fra
|
887 |
+
type: translation
|
888 |
+
args: amh-fra
|
889 |
+
dataset:
|
890 |
+
name: ntrex128
|
891 |
+
type: ntrex128
|
892 |
+
args: amh-fra
|
893 |
+
metrics:
|
894 |
+
- name: BLEU
|
895 |
+
type: bleu
|
896 |
+
value: 10.8
|
897 |
+
- name: chr-F
|
898 |
+
type: chrf
|
899 |
+
value: 0.37274
|
900 |
+
- task:
|
901 |
+
name: Translation amh-spa
|
902 |
+
type: translation
|
903 |
+
args: amh-spa
|
904 |
+
dataset:
|
905 |
+
name: ntrex128
|
906 |
+
type: ntrex128
|
907 |
+
args: amh-spa
|
908 |
+
metrics:
|
909 |
+
- name: BLEU
|
910 |
+
type: bleu
|
911 |
+
value: 12.1
|
912 |
+
- name: chr-F
|
913 |
+
type: chrf
|
914 |
+
value: 0.38306
|
915 |
+
- task:
|
916 |
+
name: Translation hau-eng
|
917 |
+
type: translation
|
918 |
+
args: hau-eng
|
919 |
+
dataset:
|
920 |
+
name: ntrex128
|
921 |
+
type: ntrex128
|
922 |
+
args: hau-eng
|
923 |
+
metrics:
|
924 |
+
- name: BLEU
|
925 |
+
type: bleu
|
926 |
+
value: 26.1
|
927 |
+
- name: chr-F
|
928 |
+
type: chrf
|
929 |
+
value: 0.50349
|
930 |
+
- task:
|
931 |
+
name: Translation hau-fra
|
932 |
+
type: translation
|
933 |
+
args: hau-fra
|
934 |
+
dataset:
|
935 |
+
name: ntrex128
|
936 |
+
type: ntrex128
|
937 |
+
args: hau-fra
|
938 |
+
metrics:
|
939 |
+
- name: BLEU
|
940 |
+
type: bleu
|
941 |
+
value: 15.8
|
942 |
+
- name: chr-F
|
943 |
+
type: chrf
|
944 |
+
value: 0.41837
|
945 |
+
- task:
|
946 |
+
name: Translation hau-por
|
947 |
+
type: translation
|
948 |
+
args: hau-por
|
949 |
+
dataset:
|
950 |
+
name: ntrex128
|
951 |
+
type: ntrex128
|
952 |
+
args: hau-por
|
953 |
+
metrics:
|
954 |
+
- name: BLEU
|
955 |
+
type: bleu
|
956 |
+
value: 15.3
|
957 |
+
- name: chr-F
|
958 |
+
type: chrf
|
959 |
+
value: 0.40851
|
960 |
+
- task:
|
961 |
+
name: Translation hau-spa
|
962 |
+
type: translation
|
963 |
+
args: hau-spa
|
964 |
+
dataset:
|
965 |
+
name: ntrex128
|
966 |
+
type: ntrex128
|
967 |
+
args: hau-spa
|
968 |
+
metrics:
|
969 |
+
- name: BLEU
|
970 |
+
type: bleu
|
971 |
+
value: 18.5
|
972 |
+
- name: chr-F
|
973 |
+
type: chrf
|
974 |
+
value: 0.43376
|
975 |
+
- task:
|
976 |
+
name: Translation heb-deu
|
977 |
+
type: translation
|
978 |
+
args: heb-deu
|
979 |
+
dataset:
|
980 |
+
name: ntrex128
|
981 |
+
type: ntrex128
|
982 |
+
args: heb-deu
|
983 |
+
metrics:
|
984 |
+
- name: BLEU
|
985 |
+
type: bleu
|
986 |
+
value: 17.7
|
987 |
+
- name: chr-F
|
988 |
+
type: chrf
|
989 |
+
value: 0.49482
|
990 |
+
- task:
|
991 |
+
name: Translation heb-eng
|
992 |
+
type: translation
|
993 |
+
args: heb-eng
|
994 |
+
dataset:
|
995 |
+
name: ntrex128
|
996 |
+
type: ntrex128
|
997 |
+
args: heb-eng
|
998 |
+
metrics:
|
999 |
+
- name: BLEU
|
1000 |
+
type: bleu
|
1001 |
+
value: 31.3
|
1002 |
+
- name: chr-F
|
1003 |
+
type: chrf
|
1004 |
+
value: 0.59241
|
1005 |
+
- task:
|
1006 |
+
name: Translation heb-fra
|
1007 |
+
type: translation
|
1008 |
+
args: heb-fra
|
1009 |
+
dataset:
|
1010 |
+
name: ntrex128
|
1011 |
+
type: ntrex128
|
1012 |
+
args: heb-fra
|
1013 |
+
metrics:
|
1014 |
+
- name: BLEU
|
1015 |
+
type: bleu
|
1016 |
+
value: 24.0
|
1017 |
+
- name: chr-F
|
1018 |
+
type: chrf
|
1019 |
+
value: 0.52180
|
1020 |
+
- task:
|
1021 |
+
name: Translation heb-por
|
1022 |
+
type: translation
|
1023 |
+
args: heb-por
|
1024 |
+
dataset:
|
1025 |
+
name: ntrex128
|
1026 |
+
type: ntrex128
|
1027 |
+
args: heb-por
|
1028 |
+
metrics:
|
1029 |
+
- name: BLEU
|
1030 |
+
type: bleu
|
1031 |
+
value: 23.2
|
1032 |
+
- name: chr-F
|
1033 |
+
type: chrf
|
1034 |
+
value: 0.51248
|
1035 |
+
- task:
|
1036 |
+
name: Translation mlt-spa
|
1037 |
+
type: translation
|
1038 |
+
args: mlt-spa
|
1039 |
+
dataset:
|
1040 |
+
name: ntrex128
|
1041 |
+
type: ntrex128
|
1042 |
+
args: mlt-spa
|
1043 |
+
metrics:
|
1044 |
+
- name: BLEU
|
1045 |
+
type: bleu
|
1046 |
+
value: 30.9
|
1047 |
+
- name: chr-F
|
1048 |
+
type: chrf
|
1049 |
+
value: 0.57078
|
1050 |
+
- task:
|
1051 |
+
name: Translation som-deu
|
1052 |
+
type: translation
|
1053 |
+
args: som-deu
|
1054 |
+
dataset:
|
1055 |
+
name: ntrex128
|
1056 |
+
type: ntrex128
|
1057 |
+
args: som-deu
|
1058 |
+
metrics:
|
1059 |
+
- name: BLEU
|
1060 |
+
type: bleu
|
1061 |
+
value: 11.0
|
1062 |
+
- name: chr-F
|
1063 |
+
type: chrf
|
1064 |
+
value: 0.39394
|
1065 |
+
- task:
|
1066 |
+
name: Translation som-eng
|
1067 |
+
type: translation
|
1068 |
+
args: som-eng
|
1069 |
+
dataset:
|
1070 |
+
name: ntrex128
|
1071 |
+
type: ntrex128
|
1072 |
+
args: som-eng
|
1073 |
+
metrics:
|
1074 |
+
- name: BLEU
|
1075 |
+
type: bleu
|
1076 |
+
value: 24.3
|
1077 |
+
- name: chr-F
|
1078 |
+
type: chrf
|
1079 |
+
value: 0.49187
|
1080 |
+
- task:
|
1081 |
+
name: Translation som-fra
|
1082 |
+
type: translation
|
1083 |
+
args: som-fra
|
1084 |
+
dataset:
|
1085 |
+
name: ntrex128
|
1086 |
+
type: ntrex128
|
1087 |
+
args: som-fra
|
1088 |
+
metrics:
|
1089 |
+
- name: BLEU
|
1090 |
+
type: bleu
|
1091 |
+
value: 15.1
|
1092 |
+
- name: chr-F
|
1093 |
+
type: chrf
|
1094 |
+
value: 0.41236
|
1095 |
+
- task:
|
1096 |
+
name: Translation som-por
|
1097 |
+
type: translation
|
1098 |
+
args: som-por
|
1099 |
+
dataset:
|
1100 |
+
name: ntrex128
|
1101 |
+
type: ntrex128
|
1102 |
+
args: som-por
|
1103 |
+
metrics:
|
1104 |
+
- name: BLEU
|
1105 |
+
type: bleu
|
1106 |
+
value: 15.2
|
1107 |
+
- name: chr-F
|
1108 |
+
type: chrf
|
1109 |
+
value: 0.41550
|
1110 |
+
- task:
|
1111 |
+
name: Translation som-spa
|
1112 |
+
type: translation
|
1113 |
+
args: som-spa
|
1114 |
+
dataset:
|
1115 |
+
name: ntrex128
|
1116 |
+
type: ntrex128
|
1117 |
+
args: som-spa
|
1118 |
+
metrics:
|
1119 |
+
- name: BLEU
|
1120 |
+
type: bleu
|
1121 |
+
value: 17.6
|
1122 |
+
- name: chr-F
|
1123 |
+
type: chrf
|
1124 |
+
value: 0.43278
|
1125 |
+
- task:
|
1126 |
+
name: Translation tir-eng
|
1127 |
+
type: translation
|
1128 |
+
args: tir-eng
|
1129 |
+
dataset:
|
1130 |
+
name: ntrex128
|
1131 |
+
type: ntrex128
|
1132 |
+
args: tir-eng
|
1133 |
+
metrics:
|
1134 |
+
- name: BLEU
|
1135 |
+
type: bleu
|
1136 |
+
value: 12.5
|
1137 |
+
- name: chr-F
|
1138 |
+
type: chrf
|
1139 |
+
value: 0.37185
|
1140 |
+
- task:
|
1141 |
+
name: Translation tir-spa
|
1142 |
+
type: translation
|
1143 |
+
args: tir-spa
|
1144 |
+
dataset:
|
1145 |
+
name: ntrex128
|
1146 |
+
type: ntrex128
|
1147 |
+
args: tir-spa
|
1148 |
+
metrics:
|
1149 |
+
- name: BLEU
|
1150 |
+
type: bleu
|
1151 |
+
value: 10.2
|
1152 |
+
- name: chr-F
|
1153 |
+
type: chrf
|
1154 |
+
value: 0.34985
|
1155 |
+
- task:
|
1156 |
+
name: Translation amh-eng
|
1157 |
+
type: translation
|
1158 |
+
args: amh-eng
|
1159 |
+
dataset:
|
1160 |
+
name: tatoeba-test-v2021-03-30
|
1161 |
+
type: tatoeba_mt
|
1162 |
+
args: amh-eng
|
1163 |
+
metrics:
|
1164 |
+
- name: BLEU
|
1165 |
+
type: bleu
|
1166 |
+
value: 59.5
|
1167 |
+
- name: chr-F
|
1168 |
+
type: chrf
|
1169 |
+
value: 0.70202
|
1170 |
+
- task:
|
1171 |
+
name: Translation ara-deu
|
1172 |
+
type: translation
|
1173 |
+
args: ara-deu
|
1174 |
+
dataset:
|
1175 |
+
name: tatoeba-test-v2021-08-07
|
1176 |
+
type: tatoeba_mt
|
1177 |
+
args: ara-deu
|
1178 |
+
metrics:
|
1179 |
+
- name: BLEU
|
1180 |
+
type: bleu
|
1181 |
+
value: 41.7
|
1182 |
+
- name: chr-F
|
1183 |
+
type: chrf
|
1184 |
+
value: 0.61039
|
1185 |
+
- task:
|
1186 |
+
name: Translation ara-eng
|
1187 |
+
type: translation
|
1188 |
+
args: ara-eng
|
1189 |
+
dataset:
|
1190 |
+
name: tatoeba-test-v2020-07-28
|
1191 |
+
type: tatoeba_mt
|
1192 |
+
args: ara-eng
|
1193 |
+
metrics:
|
1194 |
+
- name: BLEU
|
1195 |
+
type: bleu
|
1196 |
+
value: 42.8
|
1197 |
+
- name: chr-F
|
1198 |
+
type: chrf
|
1199 |
+
value: 0.60134
|
1200 |
+
- task:
|
1201 |
+
name: Translation ara-fra
|
1202 |
+
type: translation
|
1203 |
+
args: ara-fra
|
1204 |
+
dataset:
|
1205 |
+
name: tatoeba-test-v2021-08-07
|
1206 |
+
type: tatoeba_mt
|
1207 |
+
args: ara-fra
|
1208 |
+
metrics:
|
1209 |
+
- name: BLEU
|
1210 |
+
type: bleu
|
1211 |
+
value: 38.8
|
1212 |
+
- name: chr-F
|
1213 |
+
type: chrf
|
1214 |
+
value: 0.56120
|
1215 |
+
- task:
|
1216 |
+
name: Translation ara-spa
|
1217 |
+
type: translation
|
1218 |
+
args: ara-spa
|
1219 |
+
dataset:
|
1220 |
+
name: tatoeba-test-v2021-08-07
|
1221 |
+
type: tatoeba_mt
|
1222 |
+
args: ara-spa
|
1223 |
+
metrics:
|
1224 |
+
- name: BLEU
|
1225 |
+
type: bleu
|
1226 |
+
value: 43.7
|
1227 |
+
- name: chr-F
|
1228 |
+
type: chrf
|
1229 |
+
value: 0.62567
|
1230 |
+
- task:
|
1231 |
+
name: Translation heb-deu
|
1232 |
+
type: translation
|
1233 |
+
args: heb-deu
|
1234 |
+
dataset:
|
1235 |
+
name: tatoeba-test-v2021-08-07
|
1236 |
+
type: tatoeba_mt
|
1237 |
+
args: heb-deu
|
1238 |
+
metrics:
|
1239 |
+
- name: BLEU
|
1240 |
+
type: bleu
|
1241 |
+
value: 42.4
|
1242 |
+
- name: chr-F
|
1243 |
+
type: chrf
|
1244 |
+
value: 0.63131
|
1245 |
+
- task:
|
1246 |
+
name: Translation heb-eng
|
1247 |
+
type: translation
|
1248 |
+
args: heb-eng
|
1249 |
+
dataset:
|
1250 |
+
name: tatoeba-test-v2021-08-07
|
1251 |
+
type: tatoeba_mt
|
1252 |
+
args: heb-eng
|
1253 |
+
metrics:
|
1254 |
+
- name: BLEU
|
1255 |
+
type: bleu
|
1256 |
+
value: 49.2
|
1257 |
+
- name: chr-F
|
1258 |
+
type: chrf
|
1259 |
+
value: 0.64960
|
1260 |
+
- task:
|
1261 |
+
name: Translation heb-fra
|
1262 |
+
type: translation
|
1263 |
+
args: heb-fra
|
1264 |
+
dataset:
|
1265 |
+
name: tatoeba-test-v2021-08-07
|
1266 |
+
type: tatoeba_mt
|
1267 |
+
args: heb-fra
|
1268 |
+
metrics:
|
1269 |
+
- name: BLEU
|
1270 |
+
type: bleu
|
1271 |
+
value: 46.3
|
1272 |
+
- name: chr-F
|
1273 |
+
type: chrf
|
1274 |
+
value: 0.64348
|
1275 |
+
- task:
|
1276 |
+
name: Translation heb-por
|
1277 |
+
type: translation
|
1278 |
+
args: heb-por
|
1279 |
+
dataset:
|
1280 |
+
name: tatoeba-test-v2021-08-07
|
1281 |
+
type: tatoeba_mt
|
1282 |
+
args: heb-por
|
1283 |
+
metrics:
|
1284 |
+
- name: BLEU
|
1285 |
+
type: bleu
|
1286 |
+
value: 43.2
|
1287 |
+
- name: chr-F
|
1288 |
+
type: chrf
|
1289 |
+
value: 0.63350
|
1290 |
+
- task:
|
1291 |
+
name: Translation kab-eng
|
1292 |
+
type: translation
|
1293 |
+
args: kab-eng
|
1294 |
+
dataset:
|
1295 |
+
name: tatoeba-test-v2021-03-30
|
1296 |
+
type: tatoeba_mt
|
1297 |
+
args: kab-eng
|
1298 |
+
metrics:
|
1299 |
+
- name: BLEU
|
1300 |
+
type: bleu
|
1301 |
+
value: 27.8
|
1302 |
+
- name: chr-F
|
1303 |
+
type: chrf
|
1304 |
+
value: 0.44646
|
1305 |
+
- task:
|
1306 |
+
name: Translation kab-spa
|
1307 |
+
type: translation
|
1308 |
+
args: kab-spa
|
1309 |
+
dataset:
|
1310 |
+
name: tatoeba-test-v2020-07-28
|
1311 |
+
type: tatoeba_mt
|
1312 |
+
args: kab-spa
|
1313 |
+
metrics:
|
1314 |
+
- name: BLEU
|
1315 |
+
type: bleu
|
1316 |
+
value: 23.4
|
1317 |
+
- name: chr-F
|
1318 |
+
type: chrf
|
1319 |
+
value: 0.41526
|
1320 |
+
- task:
|
1321 |
+
name: Translation mlt-eng
|
1322 |
+
type: translation
|
1323 |
+
args: mlt-eng
|
1324 |
+
dataset:
|
1325 |
+
name: tatoeba-test-v2021-08-07
|
1326 |
+
type: tatoeba_mt
|
1327 |
+
args: mlt-eng
|
1328 |
+
metrics:
|
1329 |
+
- name: BLEU
|
1330 |
+
type: bleu
|
1331 |
+
value: 51.0
|
1332 |
+
- name: chr-F
|
1333 |
+
type: chrf
|
1334 |
+
value: 0.66653
|
1335 |
+
- task:
|
1336 |
+
name: Translation multi-multi
|
1337 |
+
type: translation
|
1338 |
+
args: multi-multi
|
1339 |
+
dataset:
|
1340 |
+
name: tatoeba-test-v2020-07-28-v2023-09-26
|
1341 |
+
type: tatoeba_mt
|
1342 |
+
args: multi-multi
|
1343 |
+
metrics:
|
1344 |
+
- name: BLEU
|
1345 |
+
type: bleu
|
1346 |
+
value: 34.0
|
1347 |
+
- name: chr-F
|
1348 |
+
type: chrf
|
1349 |
+
value: 0.51369
|
1350 |
+
- task:
|
1351 |
+
name: Translation hau-eng
|
1352 |
+
type: translation
|
1353 |
+
args: hau-eng
|
1354 |
+
dataset:
|
1355 |
+
name: newstest2021
|
1356 |
+
type: wmt-2021-news
|
1357 |
+
args: hau-eng
|
1358 |
+
metrics:
|
1359 |
+
- name: BLEU
|
1360 |
+
type: bleu
|
1361 |
+
value: 15.5
|
1362 |
+
- name: chr-F
|
1363 |
+
type: chrf
|
1364 |
+
value: 0.43744
|
1365 |
+
---
|
1366 |
+
# opus-mt-tc-bible-big-afa-deu_eng_fra_por_spa
|
1367 |
+
|
1368 |
+
## Table of Contents
|
1369 |
+
- [Model Details](#model-details)
|
1370 |
+
- [Uses](#uses)
|
1371 |
+
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
|
1372 |
+
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
|
1373 |
+
- [Training](#training)
|
1374 |
+
- [Evaluation](#evaluation)
|
1375 |
+
- [Citation Information](#citation-information)
|
1376 |
+
- [Acknowledgements](#acknowledgements)
|
1377 |
+
|
1378 |
+
## Model Details
|
1379 |
+
|
1380 |
+
Neural machine translation model for translating from Afro-Asiatic languages (afa) to unknown (deu+eng+fra+por+spa).
|
1381 |
+
|
1382 |
+
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).
|
1383 |
+
**Model Description:**
|
1384 |
+
- **Developed by:** Language Technology Research Group at the University of Helsinki
|
1385 |
+
- **Model Type:** Translation (transformer-big)
|
1386 |
+
- **Release**: 2024-05-29
|
1387 |
+
- **License:** Apache-2.0
|
1388 |
+
- **Language(s):**
|
1389 |
+
- Source Language(s): aar acm afb amh apc ara arc arq arz bcw byn cop daa dsh gde gnd hau hbo heb hig irk jpa kab ker kqp ktb kxc lln lme meq mfh mfi mfk mif mlt mpg mqb muy oar orm pbi phn rif sgw shi shy som sur syc syr taq thv tig tir tmc tmh tmr ttr tzm wal xed zgh
|
1390 |
+
- Target Language(s): deu eng fra por spa
|
1391 |
+
- Valid Target Language Labels: >>deu<< >>eng<< >>fra<< >>por<< >>spa<< >>xxx<<
|
1392 |
+
- **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip)
|
1393 |
+
- **Resources for more information:**
|
1394 |
+
- [OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/afa-deu%2Beng%2Bfra%2Bpor%2Bspa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-29)
|
1395 |
+
- [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
|
1396 |
+
- [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
|
1397 |
+
- [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/)
|
1398 |
+
- [HPLT bilingual data v1 (as part of the Tatoeba Translation Challenge dataset)](https://hplt-project.org/datasets/v1)
|
1399 |
+
- [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)
|
1400 |
+
|
1401 |
+
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. `>>deu<<`
|
1402 |
+
|
1403 |
+
## Uses
|
1404 |
+
|
1405 |
+
This model can be used for translation and text-to-text generation.
|
1406 |
+
|
1407 |
+
## Risks, Limitations and Biases
|
1408 |
+
|
1409 |
+
**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.**
|
1410 |
+
|
1411 |
+
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)).
|
1412 |
+
|
1413 |
+
## How to Get Started With the Model
|
1414 |
+
|
1415 |
+
A short example code:
|
1416 |
+
|
1417 |
+
```python
|
1418 |
+
from transformers import MarianMTModel, MarianTokenizer
|
1419 |
+
|
1420 |
+
src_text = [
|
1421 |
+
">>eng<< Anta i ak-d-yennan ur yerbiḥ ara Tom?",
|
1422 |
+
">>fra<< Iselman d aɣbalu axatar i wučči n yemdanen."
|
1423 |
+
]
|
1424 |
+
|
1425 |
+
model_name = "pytorch-models/opus-mt-tc-bible-big-afa-deu_eng_fra_por_spa"
|
1426 |
+
tokenizer = MarianTokenizer.from_pretrained(model_name)
|
1427 |
+
model = MarianMTModel.from_pretrained(model_name)
|
1428 |
+
translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
|
1429 |
+
|
1430 |
+
for t in translated:
|
1431 |
+
print( tokenizer.decode(t, skip_special_tokens=True) )
|
1432 |
+
|
1433 |
+
# expected output:
|
1434 |
+
# Who told you that he didn't?
|
1435 |
+
# L'eau est une source importante de nourriture pour les gens.
|
1436 |
+
```
|
1437 |
+
|
1438 |
+
You can also use OPUS-MT models with the transformers pipelines, for example:
|
1439 |
+
|
1440 |
+
```python
|
1441 |
+
from transformers import pipeline
|
1442 |
+
pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-bible-big-afa-deu_eng_fra_por_spa")
|
1443 |
+
print(pipe(">>eng<< Anta i ak-d-yennan ur yerbiḥ ara Tom?"))
|
1444 |
+
|
1445 |
+
# expected output: Who told you that he didn't?
|
1446 |
+
```
|
1447 |
+
|
1448 |
+
## Training
|
1449 |
+
|
1450 |
+
- **Data**: opusTCv20230926max50+bt+jhubc ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
|
1451 |
+
- **Pre-processing**: SentencePiece (spm32k,spm32k)
|
1452 |
+
- **Model Type:** transformer-big
|
1453 |
+
- **Original MarianNMT Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.zip)
|
1454 |
+
- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
|
1455 |
+
|
1456 |
+
## Evaluation
|
1457 |
+
|
1458 |
+
* [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/afa-deu%2Beng%2Bfra%2Bpor%2Bspa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-29)
|
1459 |
+
* test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt)
|
1460 |
+
* test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt)
|
1461 |
+
* benchmark results: [benchmark_results.txt](benchmark_results.txt)
|
1462 |
+
* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
|
1463 |
+
|
1464 |
+
| langpair | testset | chr-F | BLEU | #sent | #words |
|
1465 |
+
|----------|---------|-------|-------|-------|--------|
|
1466 |
+
| ara-deu | tatoeba-test-v2021-08-07 | 0.61039 | 41.7 | 1209 | 8371 |
|
1467 |
+
| ara-eng | tatoeba-test-v2021-08-07 | 5.430 | 0.0 | 10305 | 76975 |
|
1468 |
+
| ara-fra | tatoeba-test-v2021-08-07 | 0.56120 | 38.8 | 1569 | 11066 |
|
1469 |
+
| ara-spa | tatoeba-test-v2021-08-07 | 0.62567 | 43.7 | 1511 | 9708 |
|
1470 |
+
| heb-deu | tatoeba-test-v2021-08-07 | 0.63131 | 42.4 | 3090 | 25101 |
|
1471 |
+
| heb-eng | tatoeba-test-v2021-08-07 | 0.64960 | 49.2 | 10519 | 77427 |
|
1472 |
+
| heb-fra | tatoeba-test-v2021-08-07 | 0.64348 | 46.3 | 3281 | 26123 |
|
1473 |
+
| heb-por | tatoeba-test-v2021-08-07 | 0.63350 | 43.2 | 719 | 5335 |
|
1474 |
+
| mlt-eng | tatoeba-test-v2021-08-07 | 0.66653 | 51.0 | 203 | 1165 |
|
1475 |
+
| amh-eng | flores101-devtest | 0.47357 | 21.0 | 1012 | 24721 |
|
1476 |
+
| amh-fra | flores101-devtest | 0.43155 | 16.2 | 1012 | 28343 |
|
1477 |
+
| amh-por | flores101-devtest | 0.42109 | 15.1 | 1012 | 26519 |
|
1478 |
+
| ara-deu | flores101-devtest | 0.51110 | 20.4 | 1012 | 25094 |
|
1479 |
+
| ara-fra | flores101-devtest | 0.56934 | 29.7 | 1012 | 28343 |
|
1480 |
+
| ara-por | flores101-devtest | 0.55727 | 28.2 | 1012 | 26519 |
|
1481 |
+
| ara-spa | flores101-devtest | 0.48350 | 19.5 | 1012 | 29199 |
|
1482 |
+
| hau-eng | flores101-devtest | 0.46804 | 21.6 | 1012 | 24721 |
|
1483 |
+
| hau-fra | flores101-devtest | 0.41827 | 15.9 | 1012 | 28343 |
|
1484 |
+
| heb-eng | flores101-devtest | 0.62422 | 36.6 | 1012 | 24721 |
|
1485 |
+
| mlt-eng | flores101-devtest | 0.72390 | 49.1 | 1012 | 24721 |
|
1486 |
+
| mlt-fra | flores101-devtest | 0.60840 | 34.7 | 1012 | 28343 |
|
1487 |
+
| mlt-por | flores101-devtest | 0.59863 | 31.8 | 1012 | 26519 |
|
1488 |
+
| acm-deu | flores200-devtest | 0.48947 | 17.6 | 1012 | 25094 |
|
1489 |
+
| acm-eng | flores200-devtest | 0.56799 | 28.5 | 1012 | 24721 |
|
1490 |
+
| acm-fra | flores200-devtest | 0.53577 | 26.1 | 1012 | 28343 |
|
1491 |
+
| acm-por | flores200-devtest | 0.52441 | 23.9 | 1012 | 26519 |
|
1492 |
+
| acm-spa | flores200-devtest | 0.46985 | 18.2 | 1012 | 29199 |
|
1493 |
+
| amh-deu | flores200-devtest | 0.41553 | 12.6 | 1012 | 25094 |
|
1494 |
+
| amh-eng | flores200-devtest | 0.49333 | 22.5 | 1012 | 24721 |
|
1495 |
+
| amh-fra | flores200-devtest | 0.44890 | 17.8 | 1012 | 28343 |
|
1496 |
+
| amh-por | flores200-devtest | 0.43771 | 16.5 | 1012 | 26519 |
|
1497 |
+
| apc-deu | flores200-devtest | 0.47480 | 16.0 | 1012 | 25094 |
|
1498 |
+
| apc-eng | flores200-devtest | 0.56075 | 28.1 | 1012 | 24721 |
|
1499 |
+
| apc-fra | flores200-devtest | 0.52325 | 24.6 | 1012 | 28343 |
|
1500 |
+
| apc-por | flores200-devtest | 0.51055 | 22.9 | 1012 | 26519 |
|
1501 |
+
| apc-spa | flores200-devtest | 0.45634 | 17.2 | 1012 | 29199 |
|
1502 |
+
| arz-deu | flores200-devtest | 0.45844 | 14.1 | 1012 | 25094 |
|
1503 |
+
| arz-eng | flores200-devtest | 0.52534 | 22.7 | 1012 | 24721 |
|
1504 |
+
| arz-fra | flores200-devtest | 0.50336 | 21.8 | 1012 | 28343 |
|
1505 |
+
| arz-por | flores200-devtest | 0.48741 | 20.0 | 1012 | 26519 |
|
1506 |
+
| arz-spa | flores200-devtest | 0.44516 | 15.8 | 1012 | 29199 |
|
1507 |
+
| hau-eng | flores200-devtest | 0.48137 | 23.4 | 1012 | 24721 |
|
1508 |
+
| hau-fra | flores200-devtest | 0.42981 | 17.2 | 1012 | 28343 |
|
1509 |
+
| hau-por | flores200-devtest | 0.41385 | 15.7 | 1012 | 26519 |
|
1510 |
+
| heb-deu | flores200-devtest | 0.53482 | 22.8 | 1012 | 25094 |
|
1511 |
+
| heb-eng | flores200-devtest | 0.63368 | 38.0 | 1012 | 24721 |
|
1512 |
+
| heb-fra | flores200-devtest | 0.58417 | 32.6 | 1012 | 28343 |
|
1513 |
+
| heb-por | flores200-devtest | 0.57140 | 30.7 | 1012 | 26519 |
|
1514 |
+
| mlt-eng | flores200-devtest | 0.73415 | 51.1 | 1012 | 24721 |
|
1515 |
+
| mlt-fra | flores200-devtest | 0.61626 | 35.8 | 1012 | 28343 |
|
1516 |
+
| mlt-spa | flores200-devtest | 0.50534 | 21.8 | 1012 | 29199 |
|
1517 |
+
| som-eng | flores200-devtest | 0.42764 | 17.7 | 1012 | 24721 |
|
1518 |
+
| tir-por | flores200-devtest | 2.931 | 0.0 | 1012 | 26519 |
|
1519 |
+
| hau-eng | newstest2021 | 0.43744 | 15.5 | 997 | 27372 |
|
1520 |
+
| amh-eng | ntrex128 | 0.42042 | 15.0 | 1997 | 47673 |
|
1521 |
+
| hau-eng | ntrex128 | 0.50349 | 26.1 | 1997 | 47673 |
|
1522 |
+
| hau-fra | ntrex128 | 0.41837 | 15.8 | 1997 | 53481 |
|
1523 |
+
| hau-por | ntrex128 | 0.40851 | 15.3 | 1997 | 51631 |
|
1524 |
+
| hau-spa | ntrex128 | 0.43376 | 18.5 | 1997 | 54107 |
|
1525 |
+
| heb-deu | ntrex128 | 0.49482 | 17.7 | 1997 | 48761 |
|
1526 |
+
| heb-eng | ntrex128 | 0.59241 | 31.3 | 1997 | 47673 |
|
1527 |
+
| heb-fra | ntrex128 | 0.52180 | 24.0 | 1997 | 53481 |
|
1528 |
+
| heb-por | ntrex128 | 0.51248 | 23.2 | 1997 | 51631 |
|
1529 |
+
| mlt-spa | ntrex128 | 0.57078 | 30.9 | 1997 | 54107 |
|
1530 |
+
| som-eng | ntrex128 | 0.49187 | 24.3 | 1997 | 47673 |
|
1531 |
+
| som-fra | ntrex128 | 0.41236 | 15.1 | 1997 | 53481 |
|
1532 |
+
| som-por | ntrex128 | 0.41550 | 15.2 | 1997 | 51631 |
|
1533 |
+
| som-spa | ntrex128 | 0.43278 | 17.6 | 1997 | 54107 |
|
1534 |
+
| tir-eng | tico19-test | 2.655 | 0.0 | 2100 | 56824 |
|
1535 |
+
|
1536 |
+
## Citation Information
|
1537 |
+
|
1538 |
+
* 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.)
|
1539 |
+
|
1540 |
+
```bibtex
|
1541 |
+
@article{tiedemann2023democratizing,
|
1542 |
+
title={Democratizing neural machine translation with {OPUS-MT}},
|
1543 |
+
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},
|
1544 |
+
journal={Language Resources and Evaluation},
|
1545 |
+
number={58},
|
1546 |
+
pages={713--755},
|
1547 |
+
year={2023},
|
1548 |
+
publisher={Springer Nature},
|
1549 |
+
issn={1574-0218},
|
1550 |
+
doi={10.1007/s10579-023-09704-w}
|
1551 |
+
}
|
1552 |
+
|
1553 |
+
@inproceedings{tiedemann-thottingal-2020-opus,
|
1554 |
+
title = "{OPUS}-{MT} {--} Building open translation services for the World",
|
1555 |
+
author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh},
|
1556 |
+
booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
|
1557 |
+
month = nov,
|
1558 |
+
year = "2020",
|
1559 |
+
address = "Lisboa, Portugal",
|
1560 |
+
publisher = "European Association for Machine Translation",
|
1561 |
+
url = "https://aclanthology.org/2020.eamt-1.61",
|
1562 |
+
pages = "479--480",
|
1563 |
+
}
|
1564 |
+
|
1565 |
+
@inproceedings{tiedemann-2020-tatoeba,
|
1566 |
+
title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
|
1567 |
+
author = {Tiedemann, J{\"o}rg},
|
1568 |
+
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
|
1569 |
+
month = nov,
|
1570 |
+
year = "2020",
|
1571 |
+
address = "Online",
|
1572 |
+
publisher = "Association for Computational Linguistics",
|
1573 |
+
url = "https://aclanthology.org/2020.wmt-1.139",
|
1574 |
+
pages = "1174--1182",
|
1575 |
+
}
|
1576 |
+
```
|
1577 |
+
|
1578 |
+
## Acknowledgements
|
1579 |
+
|
1580 |
+
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/).
|
1581 |
+
|
1582 |
+
## Model conversion info
|
1583 |
+
|
1584 |
+
* transformers version: 4.45.1
|
1585 |
+
* OPUS-MT git hash: a0ea3b3
|
1586 |
+
* port time: Mon Oct 7 16:01:48 EEST 2024
|
1587 |
+
* port machine: LM0-400-22516.local
|
benchmark_results.txt
ADDED
@@ -0,0 +1,129 @@
|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
1 |
+
multi-multi tatoeba-test-v2020-07-28-v2023-09-26 0.51369 34.0 10000 74513
|
2 |
+
amh-deu flores101-devtest 0.39890 11.5 1012 25094
|
3 |
+
amh-eng flores101-devtest 0.47357 21.0 1012 24721
|
4 |
+
amh-fra flores101-devtest 0.43155 16.2 1012 28343
|
5 |
+
amh-por flores101-devtest 0.42109 15.1 1012 26519
|
6 |
+
amh-spa flores101-devtest 0.38003 11.5 1012 29199
|
7 |
+
ara-deu flores101-devtest 0.51110 20.4 1012 25094
|
8 |
+
ara-fra flores101-devtest 0.56934 29.7 1012 28343
|
9 |
+
ara-por flores101-devtest 0.55727 28.2 1012 26519
|
10 |
+
ara-spa flores101-devtest 0.48350 19.5 1012 29199
|
11 |
+
hau-deu flores101-devtest 0.30486 6.3 1012 25094
|
12 |
+
hau-eng flores101-devtest 0.46804 21.6 1012 24721
|
13 |
+
hau-fra flores101-devtest 0.41827 15.9 1012 28343
|
14 |
+
hau-spa flores101-devtest 0.37201 11.5 1012 29199
|
15 |
+
heb-eng flores101-devtest 0.62422 36.6 1012 24721
|
16 |
+
mlt-eng flores101-devtest 0.72390 49.1 1012 24721
|
17 |
+
mlt-fra flores101-devtest 0.60840 34.7 1012 28343
|
18 |
+
mlt-por flores101-devtest 0.59863 31.8 1012 26519
|
19 |
+
orm-deu flores101-devtest 0.28280 4.1 1012 25094
|
20 |
+
orm-fra flores101-devtest 0.28443 6.1 1012 28343
|
21 |
+
orm-por flores101-devtest 0.28741 5.9 1012 26519
|
22 |
+
orm-spa flores101-devtest 0.27579 5.3 1012 29199
|
23 |
+
acm-deu flores200-devtest 0.48947 17.6 1012 25094
|
24 |
+
acm-eng flores200-devtest 0.56799 28.5 1012 24721
|
25 |
+
acm-fra flores200-devtest 0.53577 26.1 1012 28343
|
26 |
+
acm-por flores200-devtest 0.52441 23.9 1012 26519
|
27 |
+
acm-spa flores200-devtest 0.46985 18.2 1012 29199
|
28 |
+
amh-deu flores200-devtest 0.41553 12.6 1012 25094
|
29 |
+
amh-eng flores200-devtest 0.49333 22.5 1012 24721
|
30 |
+
amh-fra flores200-devtest 0.44890 17.8 1012 28343
|
31 |
+
amh-por flores200-devtest 0.43771 16.5 1012 26519
|
32 |
+
amh-spa flores200-devtest 0.39526 12.8 1012 29199
|
33 |
+
apc-deu flores200-devtest 0.47480 16.0 1012 25094
|
34 |
+
apc-eng flores200-devtest 0.56075 28.1 1012 24721
|
35 |
+
apc-fra flores200-devtest 0.52325 24.6 1012 28343
|
36 |
+
apc-por flores200-devtest 0.51055 22.9 1012 26519
|
37 |
+
apc-spa flores200-devtest 0.45634 17.2 1012 29199
|
38 |
+
ara-deu flores200-devtest 4.103 0.9 1 21
|
39 |
+
ara-eng flores200-devtest 4.219 0.9 1 21
|
40 |
+
ara-fra flores200-devtest 3.444 0.6 1 24
|
41 |
+
ara-por flores200-devtest 4.490 0.8 1 22
|
42 |
+
ara-spa flores200-devtest 0.16385 0.0 1 23
|
43 |
+
arz-deu flores200-devtest 0.45844 14.1 1012 25094
|
44 |
+
arz-eng flores200-devtest 0.52534 22.7 1012 24721
|
45 |
+
arz-fra flores200-devtest 0.50336 21.8 1012 28343
|
46 |
+
arz-por flores200-devtest 0.48741 20.0 1012 26519
|
47 |
+
arz-spa flores200-devtest 0.44516 15.8 1012 29199
|
48 |
+
hau-deu flores200-devtest 0.31338 6.9 1012 25094
|
49 |
+
hau-eng flores200-devtest 0.48137 23.4 1012 24721
|
50 |
+
hau-fra flores200-devtest 0.42981 17.2 1012 28343
|
51 |
+
hau-por flores200-devtest 0.41385 15.7 1012 26519
|
52 |
+
hau-spa flores200-devtest 0.37800 11.7 1012 29199
|
53 |
+
heb-deu flores200-devtest 0.53482 22.8 1012 25094
|
54 |
+
heb-eng flores200-devtest 0.63368 38.0 1012 24721
|
55 |
+
heb-fra flores200-devtest 0.58417 32.6 1012 28343
|
56 |
+
heb-por flores200-devtest 0.57140 30.7 1012 26519
|
57 |
+
kab-deu flores200-devtest 0.29507 5.1 1012 25094
|
58 |
+
kab-eng flores200-devtest 0.32121 10.0 1012 24721
|
59 |
+
kab-por flores200-devtest 0.32076 9.0 1012 26519
|
60 |
+
mlt-eng flores200-devtest 0.73415 51.1 1012 24721
|
61 |
+
mlt-fra flores200-devtest 0.61626 35.8 1012 28343
|
62 |
+
mlt-spa flores200-devtest 0.50534 21.8 1012 29199
|
63 |
+
som-deu flores200-devtest 0.37017 9.7 1012 25094
|
64 |
+
som-eng flores200-devtest 0.42764 17.7 1012 24721
|
65 |
+
som-fra flores200-devtest 0.39536 14.4 1012 28343
|
66 |
+
som-por flores200-devtest 0.39440 14.1 1012 26519
|
67 |
+
som-spa flores200-devtest 0.35321 10.0 1012 29199
|
68 |
+
tir-deu flores200-devtest 0.33956 6.5 1012 25094
|
69 |
+
tir-eng flores200-devtest 0.37119 11.6 1012 24721
|
70 |
+
tir-fra flores200-devtest 0.35347 9.7 1012 28343
|
71 |
+
tir-por flores200-devtest 2.931 0.0 1012 26519
|
72 |
+
tir-spa flores200-devtest 0.32859 7.6 1012 29199
|
73 |
+
hau-eng newstest2021 0.43744 15.5 997 27372
|
74 |
+
amh-deu ntrex128 0.35473 7.8 1997 48761
|
75 |
+
amh-eng ntrex128 0.42042 15.0 1997 47673
|
76 |
+
amh-fra ntrex128 0.37274 10.8 1997 53481
|
77 |
+
amh-por ntrex128 0.36420 9.8 1997 51631
|
78 |
+
amh-spa ntrex128 0.38306 12.1 1997 54107
|
79 |
+
hau-deu ntrex128 0.31360 6.6 1997 48761
|
80 |
+
hau-eng ntrex128 0.50349 26.1 1997 47673
|
81 |
+
hau-fra ntrex128 0.41837 15.8 1997 53481
|
82 |
+
hau-por ntrex128 0.40851 15.3 1997 51631
|
83 |
+
hau-spa ntrex128 0.43376 18.5 1997 54107
|
84 |
+
heb-deu ntrex128 0.49482 17.7 1997 48761
|
85 |
+
heb-eng ntrex128 0.59241 31.3 1997 47673
|
86 |
+
heb-fra ntrex128 0.52180 24.0 1997 53481
|
87 |
+
heb-por ntrex128 0.51248 23.2 1997 51631
|
88 |
+
mlt-spa ntrex128 0.57078 30.9 1997 54107
|
89 |
+
orm-deu ntrex128 0.24414 3.7 1997 48761
|
90 |
+
orm-eng ntrex128 0.23820 4.7 1997 47673
|
91 |
+
orm-por ntrex128 0.24063 4.0 1997 51631
|
92 |
+
shi-deu ntrex128 0.20534 1.0 1997 48761
|
93 |
+
shi-eng ntrex128 0.22850 1.8 1997 47673
|
94 |
+
shi-fra ntrex128 0.22309 2.4 1997 53481
|
95 |
+
shi-por ntrex128 0.21646 1.9 1997 51631
|
96 |
+
shi-spa ntrex128 0.23162 2.8 1997 54107
|
97 |
+
som-deu ntrex128 0.39394 11.0 1997 48761
|
98 |
+
som-eng ntrex128 0.49187 24.3 1997 47673
|
99 |
+
som-fra ntrex128 0.41236 15.1 1997 53481
|
100 |
+
som-por ntrex128 0.41550 15.2 1997 51631
|
101 |
+
som-spa ntrex128 0.43278 17.6 1997 54107
|
102 |
+
tir-deu ntrex128 0.32512 6.2 1997 48761
|
103 |
+
tir-eng ntrex128 0.37185 12.5 1997 47673
|
104 |
+
tir-fra ntrex128 0.32879 8.6 1997 53481
|
105 |
+
tir-por ntrex128 0.33090 8.5 1997 51631
|
106 |
+
tir-spa ntrex128 0.34985 10.2 1997 54107
|
107 |
+
ara-eng tatoeba-test-v2020-07-28 0.60134 42.8 10000 73977
|
108 |
+
arq-eng tatoeba-test-v2020-07-28 0.23786 6.6 403 3059
|
109 |
+
heb-eng tatoeba-test-v2020-07-28 0.63689 47.7 10000 73560
|
110 |
+
kab-spa tatoeba-test-v2020-07-28 0.41526 23.4 212 1333
|
111 |
+
amh-eng tatoeba-test-v2021-03-30 0.70202 59.5 202 1055
|
112 |
+
arq-eng tatoeba-test-v2021-03-30 0.23812 6.7 405 3075
|
113 |
+
kab-deu tatoeba-test-v2021-03-30 0.35013 15.0 376 2425
|
114 |
+
kab-eng tatoeba-test-v2021-03-30 0.44646 27.8 11692 73688
|
115 |
+
kab-fra tatoeba-test-v2021-03-30 0.35443 16.8 11158 89678
|
116 |
+
mlt-eng tatoeba-test-v2021-03-30 0.66333 50.6 206 1183
|
117 |
+
ara-deu tatoeba-test-v2021-08-07 0.61039 41.7 1209 8371
|
118 |
+
ara-eng tatoeba-test-v2021-08-07 5.430 0.0 10305 76975
|
119 |
+
ara-fra tatoeba-test-v2021-08-07 0.56120 38.8 1569 11066
|
120 |
+
ara-spa tatoeba-test-v2021-08-07 0.62567 43.7 1511 9708
|
121 |
+
arq-eng tatoeba-test-v2021-08-07 0.24532 7.0 405 3075
|
122 |
+
heb-deu tatoeba-test-v2021-08-07 0.63131 42.4 3090 25101
|
123 |
+
heb-eng tatoeba-test-v2021-08-07 0.64960 49.2 10519 77427
|
124 |
+
heb-fra tatoeba-test-v2021-08-07 0.64348 46.3 3281 26123
|
125 |
+
heb-por tatoeba-test-v2021-08-07 0.63350 43.2 719 5335
|
126 |
+
kab-spa tatoeba-test-v2021-08-07 0.36828 18.2 883 6705
|
127 |
+
mlt-eng tatoeba-test-v2021-08-07 0.66653 51.0 203 1165
|
128 |
+
ara-spa tico19-test 0.23860 1.0 2100 66563
|
129 |
+
tir-eng tico19-test 2.655 0.0 2100 56824
|
benchmark_translations.zip
ADDED
File without changes
|
config.json
ADDED
@@ -0,0 +1,41 @@
|
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|
|
|
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|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "pytorch-models/opus-mt-tc-bible-big-afa-deu_eng_fra_por_spa",
|
3 |
+
"activation_dropout": 0.0,
|
4 |
+
"activation_function": "relu",
|
5 |
+
"architectures": [
|
6 |
+
"MarianMTModel"
|
7 |
+
],
|
8 |
+
"attention_dropout": 0.0,
|
9 |
+
"bos_token_id": 0,
|
10 |
+
"classifier_dropout": 0.0,
|
11 |
+
"d_model": 1024,
|
12 |
+
"decoder_attention_heads": 16,
|
13 |
+
"decoder_ffn_dim": 4096,
|
14 |
+
"decoder_layerdrop": 0.0,
|
15 |
+
"decoder_layers": 6,
|
16 |
+
"decoder_start_token_id": 61447,
|
17 |
+
"decoder_vocab_size": 61448,
|
18 |
+
"dropout": 0.1,
|
19 |
+
"encoder_attention_heads": 16,
|
20 |
+
"encoder_ffn_dim": 4096,
|
21 |
+
"encoder_layerdrop": 0.0,
|
22 |
+
"encoder_layers": 6,
|
23 |
+
"eos_token_id": 406,
|
24 |
+
"forced_eos_token_id": null,
|
25 |
+
"init_std": 0.02,
|
26 |
+
"is_encoder_decoder": true,
|
27 |
+
"max_length": null,
|
28 |
+
"max_position_embeddings": 1024,
|
29 |
+
"model_type": "marian",
|
30 |
+
"normalize_embedding": false,
|
31 |
+
"num_beams": null,
|
32 |
+
"num_hidden_layers": 6,
|
33 |
+
"pad_token_id": 61447,
|
34 |
+
"scale_embedding": true,
|
35 |
+
"share_encoder_decoder_embeddings": true,
|
36 |
+
"static_position_embeddings": true,
|
37 |
+
"torch_dtype": "float32",
|
38 |
+
"transformers_version": "4.45.1",
|
39 |
+
"use_cache": true,
|
40 |
+
"vocab_size": 61448
|
41 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_from_model_config": true,
|
3 |
+
"bad_words_ids": [
|
4 |
+
[
|
5 |
+
61447
|
6 |
+
]
|
7 |
+
],
|
8 |
+
"bos_token_id": 0,
|
9 |
+
"decoder_start_token_id": 61447,
|
10 |
+
"eos_token_id": 406,
|
11 |
+
"forced_eos_token_id": 406,
|
12 |
+
"max_length": 512,
|
13 |
+
"num_beams": 4,
|
14 |
+
"pad_token_id": 61447,
|
15 |
+
"transformers_version": "4.45.1"
|
16 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:eae21f9f138f8296ba401a07f5d6bbf93ed8717e549ebddbf8ec4af701b7277e
|
3 |
+
size 957395920
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:574d19800a181a2f7b5816203b20e5b9d2610ff1298761c9eec16d80852be20e
|
3 |
+
size 957447173
|
source.spm
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:15ae3e79502defa35938861792ef2e0a159e2492926e83abb71aba173620c3ed
|
3 |
+
size 806005
|
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 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:bdcc6b68a87bf83097afc16df9e5f63b005f2dd7bb6262d4b98a2ffe365697b7
|
3 |
+
size 812456
|
tokenizer_config.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"source_lang": "afa", "target_lang": "deu+eng+fra+por+spa", "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_2024-05-29/afa-deu+eng+fra+por+spa", "tokenizer_class": "MarianTokenizer"}
|
vocab.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|