Initial commit
Browse files- .gitattributes +1 -0
- README.md +1259 -0
- benchmark_results.txt +85 -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
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
36 |
+
*.spm filter=lfs diff=lfs merge=lfs -text
|
README.md
ADDED
@@ -0,0 +1,1259 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: transformers
|
3 |
+
language:
|
4 |
+
- chm
|
5 |
+
- de
|
6 |
+
- en
|
7 |
+
- es
|
8 |
+
- et
|
9 |
+
- fi
|
10 |
+
- fkv
|
11 |
+
- fr
|
12 |
+
- hu
|
13 |
+
- izh
|
14 |
+
- krl
|
15 |
+
- kv
|
16 |
+
- liv
|
17 |
+
- mdf
|
18 |
+
- mrj
|
19 |
+
- myv
|
20 |
+
- pt
|
21 |
+
- se
|
22 |
+
- sma
|
23 |
+
- smn
|
24 |
+
- udm
|
25 |
+
- vep
|
26 |
+
- vot
|
27 |
+
|
28 |
+
tags:
|
29 |
+
- translation
|
30 |
+
- opus-mt-tc-bible
|
31 |
+
|
32 |
+
license: apache-2.0
|
33 |
+
model-index:
|
34 |
+
- name: opus-mt-tc-bible-big-fiu-deu_eng_fra_por_spa
|
35 |
+
results:
|
36 |
+
- task:
|
37 |
+
name: Translation est-deu
|
38 |
+
type: translation
|
39 |
+
args: est-deu
|
40 |
+
dataset:
|
41 |
+
name: flores200-devtest
|
42 |
+
type: flores200-devtest
|
43 |
+
args: est-deu
|
44 |
+
metrics:
|
45 |
+
- name: BLEU
|
46 |
+
type: bleu
|
47 |
+
value: 26.3
|
48 |
+
- name: chr-F
|
49 |
+
type: chrf
|
50 |
+
value: 0.55825
|
51 |
+
- task:
|
52 |
+
name: Translation est-eng
|
53 |
+
type: translation
|
54 |
+
args: est-eng
|
55 |
+
dataset:
|
56 |
+
name: flores200-devtest
|
57 |
+
type: flores200-devtest
|
58 |
+
args: est-eng
|
59 |
+
metrics:
|
60 |
+
- name: BLEU
|
61 |
+
type: bleu
|
62 |
+
value: 35.4
|
63 |
+
- name: chr-F
|
64 |
+
type: chrf
|
65 |
+
value: 0.62404
|
66 |
+
- task:
|
67 |
+
name: Translation est-fra
|
68 |
+
type: translation
|
69 |
+
args: est-fra
|
70 |
+
dataset:
|
71 |
+
name: flores200-devtest
|
72 |
+
type: flores200-devtest
|
73 |
+
args: est-fra
|
74 |
+
metrics:
|
75 |
+
- name: BLEU
|
76 |
+
type: bleu
|
77 |
+
value: 31.7
|
78 |
+
- name: chr-F
|
79 |
+
type: chrf
|
80 |
+
value: 0.58580
|
81 |
+
- task:
|
82 |
+
name: Translation est-por
|
83 |
+
type: translation
|
84 |
+
args: est-por
|
85 |
+
dataset:
|
86 |
+
name: flores200-devtest
|
87 |
+
type: flores200-devtest
|
88 |
+
args: est-por
|
89 |
+
metrics:
|
90 |
+
- name: BLEU
|
91 |
+
type: bleu
|
92 |
+
value: 27.3
|
93 |
+
- name: chr-F
|
94 |
+
type: chrf
|
95 |
+
value: 0.55070
|
96 |
+
- task:
|
97 |
+
name: Translation est-spa
|
98 |
+
type: translation
|
99 |
+
args: est-spa
|
100 |
+
dataset:
|
101 |
+
name: flores200-devtest
|
102 |
+
type: flores200-devtest
|
103 |
+
args: est-spa
|
104 |
+
metrics:
|
105 |
+
- name: BLEU
|
106 |
+
type: bleu
|
107 |
+
value: 21.5
|
108 |
+
- name: chr-F
|
109 |
+
type: chrf
|
110 |
+
value: 0.50188
|
111 |
+
- task:
|
112 |
+
name: Translation fin-deu
|
113 |
+
type: translation
|
114 |
+
args: fin-deu
|
115 |
+
dataset:
|
116 |
+
name: flores200-devtest
|
117 |
+
type: flores200-devtest
|
118 |
+
args: fin-deu
|
119 |
+
metrics:
|
120 |
+
- name: BLEU
|
121 |
+
type: bleu
|
122 |
+
value: 24.0
|
123 |
+
- name: chr-F
|
124 |
+
type: chrf
|
125 |
+
value: 0.54281
|
126 |
+
- task:
|
127 |
+
name: Translation fin-eng
|
128 |
+
type: translation
|
129 |
+
args: fin-eng
|
130 |
+
dataset:
|
131 |
+
name: flores200-devtest
|
132 |
+
type: flores200-devtest
|
133 |
+
args: fin-eng
|
134 |
+
metrics:
|
135 |
+
- name: BLEU
|
136 |
+
type: bleu
|
137 |
+
value: 33.1
|
138 |
+
- name: chr-F
|
139 |
+
type: chrf
|
140 |
+
value: 0.60642
|
141 |
+
- task:
|
142 |
+
name: Translation fin-fra
|
143 |
+
type: translation
|
144 |
+
args: fin-fra
|
145 |
+
dataset:
|
146 |
+
name: flores200-devtest
|
147 |
+
type: flores200-devtest
|
148 |
+
args: fin-fra
|
149 |
+
metrics:
|
150 |
+
- name: BLEU
|
151 |
+
type: bleu
|
152 |
+
value: 30.5
|
153 |
+
- name: chr-F
|
154 |
+
type: chrf
|
155 |
+
value: 0.57540
|
156 |
+
- task:
|
157 |
+
name: Translation fin-por
|
158 |
+
type: translation
|
159 |
+
args: fin-por
|
160 |
+
dataset:
|
161 |
+
name: flores200-devtest
|
162 |
+
type: flores200-devtest
|
163 |
+
args: fin-por
|
164 |
+
metrics:
|
165 |
+
- name: BLEU
|
166 |
+
type: bleu
|
167 |
+
value: 27.4
|
168 |
+
- name: chr-F
|
169 |
+
type: chrf
|
170 |
+
value: 0.55497
|
171 |
+
- task:
|
172 |
+
name: Translation fin-spa
|
173 |
+
type: translation
|
174 |
+
args: fin-spa
|
175 |
+
dataset:
|
176 |
+
name: flores200-devtest
|
177 |
+
type: flores200-devtest
|
178 |
+
args: fin-spa
|
179 |
+
metrics:
|
180 |
+
- name: BLEU
|
181 |
+
type: bleu
|
182 |
+
value: 21.4
|
183 |
+
- name: chr-F
|
184 |
+
type: chrf
|
185 |
+
value: 0.49847
|
186 |
+
- task:
|
187 |
+
name: Translation hun-deu
|
188 |
+
type: translation
|
189 |
+
args: hun-deu
|
190 |
+
dataset:
|
191 |
+
name: flores200-devtest
|
192 |
+
type: flores200-devtest
|
193 |
+
args: hun-deu
|
194 |
+
metrics:
|
195 |
+
- name: BLEU
|
196 |
+
type: bleu
|
197 |
+
value: 25.1
|
198 |
+
- name: chr-F
|
199 |
+
type: chrf
|
200 |
+
value: 0.55180
|
201 |
+
- task:
|
202 |
+
name: Translation hun-eng
|
203 |
+
type: translation
|
204 |
+
args: hun-eng
|
205 |
+
dataset:
|
206 |
+
name: flores200-devtest
|
207 |
+
type: flores200-devtest
|
208 |
+
args: hun-eng
|
209 |
+
metrics:
|
210 |
+
- name: BLEU
|
211 |
+
type: bleu
|
212 |
+
value: 34.0
|
213 |
+
- name: chr-F
|
214 |
+
type: chrf
|
215 |
+
value: 0.61466
|
216 |
+
- task:
|
217 |
+
name: Translation hun-fra
|
218 |
+
type: translation
|
219 |
+
args: hun-fra
|
220 |
+
dataset:
|
221 |
+
name: flores200-devtest
|
222 |
+
type: flores200-devtest
|
223 |
+
args: hun-fra
|
224 |
+
metrics:
|
225 |
+
- name: BLEU
|
226 |
+
type: bleu
|
227 |
+
value: 30.6
|
228 |
+
- name: chr-F
|
229 |
+
type: chrf
|
230 |
+
value: 0.57670
|
231 |
+
- task:
|
232 |
+
name: Translation hun-por
|
233 |
+
type: translation
|
234 |
+
args: hun-por
|
235 |
+
dataset:
|
236 |
+
name: flores200-devtest
|
237 |
+
type: flores200-devtest
|
238 |
+
args: hun-por
|
239 |
+
metrics:
|
240 |
+
- name: BLEU
|
241 |
+
type: bleu
|
242 |
+
value: 28.9
|
243 |
+
- name: chr-F
|
244 |
+
type: chrf
|
245 |
+
value: 0.56510
|
246 |
+
- task:
|
247 |
+
name: Translation hun-spa
|
248 |
+
type: translation
|
249 |
+
args: hun-spa
|
250 |
+
dataset:
|
251 |
+
name: flores200-devtest
|
252 |
+
type: flores200-devtest
|
253 |
+
args: hun-spa
|
254 |
+
metrics:
|
255 |
+
- name: BLEU
|
256 |
+
type: bleu
|
257 |
+
value: 21.3
|
258 |
+
- name: chr-F
|
259 |
+
type: chrf
|
260 |
+
value: 0.49681
|
261 |
+
- task:
|
262 |
+
name: Translation est-deu
|
263 |
+
type: translation
|
264 |
+
args: est-deu
|
265 |
+
dataset:
|
266 |
+
name: flores101-devtest
|
267 |
+
type: flores_101
|
268 |
+
args: est deu devtest
|
269 |
+
metrics:
|
270 |
+
- name: BLEU
|
271 |
+
type: bleu
|
272 |
+
value: 25.7
|
273 |
+
- name: chr-F
|
274 |
+
type: chrf
|
275 |
+
value: 0.55353
|
276 |
+
- task:
|
277 |
+
name: Translation est-eng
|
278 |
+
type: translation
|
279 |
+
args: est-eng
|
280 |
+
dataset:
|
281 |
+
name: flores101-devtest
|
282 |
+
type: flores_101
|
283 |
+
args: est eng devtest
|
284 |
+
metrics:
|
285 |
+
- name: BLEU
|
286 |
+
type: bleu
|
287 |
+
value: 34.7
|
288 |
+
- name: chr-F
|
289 |
+
type: chrf
|
290 |
+
value: 0.61930
|
291 |
+
- task:
|
292 |
+
name: Translation est-fra
|
293 |
+
type: translation
|
294 |
+
args: est-fra
|
295 |
+
dataset:
|
296 |
+
name: flores101-devtest
|
297 |
+
type: flores_101
|
298 |
+
args: est fra devtest
|
299 |
+
metrics:
|
300 |
+
- name: BLEU
|
301 |
+
type: bleu
|
302 |
+
value: 31.3
|
303 |
+
- name: chr-F
|
304 |
+
type: chrf
|
305 |
+
value: 0.58199
|
306 |
+
- task:
|
307 |
+
name: Translation est-por
|
308 |
+
type: translation
|
309 |
+
args: est-por
|
310 |
+
dataset:
|
311 |
+
name: flores101-devtest
|
312 |
+
type: flores_101
|
313 |
+
args: est por devtest
|
314 |
+
metrics:
|
315 |
+
- name: BLEU
|
316 |
+
type: bleu
|
317 |
+
value: 26.5
|
318 |
+
- name: chr-F
|
319 |
+
type: chrf
|
320 |
+
value: 0.54388
|
321 |
+
- task:
|
322 |
+
name: Translation fin-eng
|
323 |
+
type: translation
|
324 |
+
args: fin-eng
|
325 |
+
dataset:
|
326 |
+
name: flores101-devtest
|
327 |
+
type: flores_101
|
328 |
+
args: fin eng devtest
|
329 |
+
metrics:
|
330 |
+
- name: BLEU
|
331 |
+
type: bleu
|
332 |
+
value: 32.2
|
333 |
+
- name: chr-F
|
334 |
+
type: chrf
|
335 |
+
value: 0.59914
|
336 |
+
- task:
|
337 |
+
name: Translation fin-por
|
338 |
+
type: translation
|
339 |
+
args: fin-por
|
340 |
+
dataset:
|
341 |
+
name: flores101-devtest
|
342 |
+
type: flores_101
|
343 |
+
args: fin por devtest
|
344 |
+
metrics:
|
345 |
+
- name: BLEU
|
346 |
+
type: bleu
|
347 |
+
value: 27.1
|
348 |
+
- name: chr-F
|
349 |
+
type: chrf
|
350 |
+
value: 0.55156
|
351 |
+
- task:
|
352 |
+
name: Translation hun-eng
|
353 |
+
type: translation
|
354 |
+
args: hun-eng
|
355 |
+
dataset:
|
356 |
+
name: flores101-devtest
|
357 |
+
type: flores_101
|
358 |
+
args: hun eng devtest
|
359 |
+
metrics:
|
360 |
+
- name: BLEU
|
361 |
+
type: bleu
|
362 |
+
value: 33.5
|
363 |
+
- name: chr-F
|
364 |
+
type: chrf
|
365 |
+
value: 0.61198
|
366 |
+
- task:
|
367 |
+
name: Translation hun-fra
|
368 |
+
type: translation
|
369 |
+
args: hun-fra
|
370 |
+
dataset:
|
371 |
+
name: flores101-devtest
|
372 |
+
type: flores_101
|
373 |
+
args: hun fra devtest
|
374 |
+
metrics:
|
375 |
+
- name: BLEU
|
376 |
+
type: bleu
|
377 |
+
value: 30.8
|
378 |
+
- name: chr-F
|
379 |
+
type: chrf
|
380 |
+
value: 0.57776
|
381 |
+
- task:
|
382 |
+
name: Translation hun-por
|
383 |
+
type: translation
|
384 |
+
args: hun-por
|
385 |
+
dataset:
|
386 |
+
name: flores101-devtest
|
387 |
+
type: flores_101
|
388 |
+
args: hun por devtest
|
389 |
+
metrics:
|
390 |
+
- name: BLEU
|
391 |
+
type: bleu
|
392 |
+
value: 28.4
|
393 |
+
- name: chr-F
|
394 |
+
type: chrf
|
395 |
+
value: 0.56263
|
396 |
+
- task:
|
397 |
+
name: Translation hun-spa
|
398 |
+
type: translation
|
399 |
+
args: hun-spa
|
400 |
+
dataset:
|
401 |
+
name: flores101-devtest
|
402 |
+
type: flores_101
|
403 |
+
args: hun spa devtest
|
404 |
+
metrics:
|
405 |
+
- name: BLEU
|
406 |
+
type: bleu
|
407 |
+
value: 20.7
|
408 |
+
- name: chr-F
|
409 |
+
type: chrf
|
410 |
+
value: 0.49140
|
411 |
+
- task:
|
412 |
+
name: Translation est-deu
|
413 |
+
type: translation
|
414 |
+
args: est-deu
|
415 |
+
dataset:
|
416 |
+
name: ntrex128
|
417 |
+
type: ntrex128
|
418 |
+
args: est-deu
|
419 |
+
metrics:
|
420 |
+
- name: BLEU
|
421 |
+
type: bleu
|
422 |
+
value: 21.4
|
423 |
+
- name: chr-F
|
424 |
+
type: chrf
|
425 |
+
value: 0.51377
|
426 |
+
- task:
|
427 |
+
name: Translation est-eng
|
428 |
+
type: translation
|
429 |
+
args: est-eng
|
430 |
+
dataset:
|
431 |
+
name: ntrex128
|
432 |
+
type: ntrex128
|
433 |
+
args: est-eng
|
434 |
+
metrics:
|
435 |
+
- name: BLEU
|
436 |
+
type: bleu
|
437 |
+
value: 29.9
|
438 |
+
- name: chr-F
|
439 |
+
type: chrf
|
440 |
+
value: 0.58358
|
441 |
+
- task:
|
442 |
+
name: Translation est-fra
|
443 |
+
type: translation
|
444 |
+
args: est-fra
|
445 |
+
dataset:
|
446 |
+
name: ntrex128
|
447 |
+
type: ntrex128
|
448 |
+
args: est-fra
|
449 |
+
metrics:
|
450 |
+
- name: BLEU
|
451 |
+
type: bleu
|
452 |
+
value: 24.9
|
453 |
+
- name: chr-F
|
454 |
+
type: chrf
|
455 |
+
value: 0.52713
|
456 |
+
- task:
|
457 |
+
name: Translation est-por
|
458 |
+
type: translation
|
459 |
+
args: est-por
|
460 |
+
dataset:
|
461 |
+
name: ntrex128
|
462 |
+
type: ntrex128
|
463 |
+
args: est-por
|
464 |
+
metrics:
|
465 |
+
- name: BLEU
|
466 |
+
type: bleu
|
467 |
+
value: 22.2
|
468 |
+
- name: chr-F
|
469 |
+
type: chrf
|
470 |
+
value: 0.50745
|
471 |
+
- task:
|
472 |
+
name: Translation est-spa
|
473 |
+
type: translation
|
474 |
+
args: est-spa
|
475 |
+
dataset:
|
476 |
+
name: ntrex128
|
477 |
+
type: ntrex128
|
478 |
+
args: est-spa
|
479 |
+
metrics:
|
480 |
+
- name: BLEU
|
481 |
+
type: bleu
|
482 |
+
value: 27.5
|
483 |
+
- name: chr-F
|
484 |
+
type: chrf
|
485 |
+
value: 0.54304
|
486 |
+
- task:
|
487 |
+
name: Translation fin-deu
|
488 |
+
type: translation
|
489 |
+
args: fin-deu
|
490 |
+
dataset:
|
491 |
+
name: ntrex128
|
492 |
+
type: ntrex128
|
493 |
+
args: fin-deu
|
494 |
+
metrics:
|
495 |
+
- name: BLEU
|
496 |
+
type: bleu
|
497 |
+
value: 19.8
|
498 |
+
- name: chr-F
|
499 |
+
type: chrf
|
500 |
+
value: 0.50282
|
501 |
+
- task:
|
502 |
+
name: Translation fin-eng
|
503 |
+
type: translation
|
504 |
+
args: fin-eng
|
505 |
+
dataset:
|
506 |
+
name: ntrex128
|
507 |
+
type: ntrex128
|
508 |
+
args: fin-eng
|
509 |
+
metrics:
|
510 |
+
- name: BLEU
|
511 |
+
type: bleu
|
512 |
+
value: 26.3
|
513 |
+
- name: chr-F
|
514 |
+
type: chrf
|
515 |
+
value: 0.55545
|
516 |
+
- task:
|
517 |
+
name: Translation fin-fra
|
518 |
+
type: translation
|
519 |
+
args: fin-fra
|
520 |
+
dataset:
|
521 |
+
name: ntrex128
|
522 |
+
type: ntrex128
|
523 |
+
args: fin-fra
|
524 |
+
metrics:
|
525 |
+
- name: BLEU
|
526 |
+
type: bleu
|
527 |
+
value: 22.9
|
528 |
+
- name: chr-F
|
529 |
+
type: chrf
|
530 |
+
value: 0.50946
|
531 |
+
- task:
|
532 |
+
name: Translation fin-por
|
533 |
+
type: translation
|
534 |
+
args: fin-por
|
535 |
+
dataset:
|
536 |
+
name: ntrex128
|
537 |
+
type: ntrex128
|
538 |
+
args: fin-por
|
539 |
+
metrics:
|
540 |
+
- name: BLEU
|
541 |
+
type: bleu
|
542 |
+
value: 21.3
|
543 |
+
- name: chr-F
|
544 |
+
type: chrf
|
545 |
+
value: 0.50404
|
546 |
+
- task:
|
547 |
+
name: Translation fin-spa
|
548 |
+
type: translation
|
549 |
+
args: fin-spa
|
550 |
+
dataset:
|
551 |
+
name: ntrex128
|
552 |
+
type: ntrex128
|
553 |
+
args: fin-spa
|
554 |
+
metrics:
|
555 |
+
- name: BLEU
|
556 |
+
type: bleu
|
557 |
+
value: 25.5
|
558 |
+
- name: chr-F
|
559 |
+
type: chrf
|
560 |
+
value: 0.52641
|
561 |
+
- task:
|
562 |
+
name: Translation hun-deu
|
563 |
+
type: translation
|
564 |
+
args: hun-deu
|
565 |
+
dataset:
|
566 |
+
name: ntrex128
|
567 |
+
type: ntrex128
|
568 |
+
args: hun-deu
|
569 |
+
metrics:
|
570 |
+
- name: BLEU
|
571 |
+
type: bleu
|
572 |
+
value: 18.5
|
573 |
+
- name: chr-F
|
574 |
+
type: chrf
|
575 |
+
value: 0.49322
|
576 |
+
- task:
|
577 |
+
name: Translation hun-eng
|
578 |
+
type: translation
|
579 |
+
args: hun-eng
|
580 |
+
dataset:
|
581 |
+
name: ntrex128
|
582 |
+
type: ntrex128
|
583 |
+
args: hun-eng
|
584 |
+
metrics:
|
585 |
+
- name: BLEU
|
586 |
+
type: bleu
|
587 |
+
value: 23.3
|
588 |
+
- name: chr-F
|
589 |
+
type: chrf
|
590 |
+
value: 0.52964
|
591 |
+
- task:
|
592 |
+
name: Translation hun-fra
|
593 |
+
type: translation
|
594 |
+
args: hun-fra
|
595 |
+
dataset:
|
596 |
+
name: ntrex128
|
597 |
+
type: ntrex128
|
598 |
+
args: hun-fra
|
599 |
+
metrics:
|
600 |
+
- name: BLEU
|
601 |
+
type: bleu
|
602 |
+
value: 21.8
|
603 |
+
- name: chr-F
|
604 |
+
type: chrf
|
605 |
+
value: 0.49800
|
606 |
+
- task:
|
607 |
+
name: Translation hun-por
|
608 |
+
type: translation
|
609 |
+
args: hun-por
|
610 |
+
dataset:
|
611 |
+
name: ntrex128
|
612 |
+
type: ntrex128
|
613 |
+
args: hun-por
|
614 |
+
metrics:
|
615 |
+
- name: BLEU
|
616 |
+
type: bleu
|
617 |
+
value: 20.5
|
618 |
+
- name: chr-F
|
619 |
+
type: chrf
|
620 |
+
value: 0.48941
|
621 |
+
- task:
|
622 |
+
name: Translation hun-spa
|
623 |
+
type: translation
|
624 |
+
args: hun-spa
|
625 |
+
dataset:
|
626 |
+
name: ntrex128
|
627 |
+
type: ntrex128
|
628 |
+
args: hun-spa
|
629 |
+
metrics:
|
630 |
+
- name: BLEU
|
631 |
+
type: bleu
|
632 |
+
value: 24.2
|
633 |
+
- name: chr-F
|
634 |
+
type: chrf
|
635 |
+
value: 0.51123
|
636 |
+
- task:
|
637 |
+
name: Translation est-deu
|
638 |
+
type: translation
|
639 |
+
args: est-deu
|
640 |
+
dataset:
|
641 |
+
name: tatoeba-test-v2021-08-07
|
642 |
+
type: tatoeba_mt
|
643 |
+
args: est-deu
|
644 |
+
metrics:
|
645 |
+
- name: BLEU
|
646 |
+
type: bleu
|
647 |
+
value: 53.9
|
648 |
+
- name: chr-F
|
649 |
+
type: chrf
|
650 |
+
value: 0.69451
|
651 |
+
- task:
|
652 |
+
name: Translation est-eng
|
653 |
+
type: translation
|
654 |
+
args: est-eng
|
655 |
+
dataset:
|
656 |
+
name: tatoeba-test-v2021-08-07
|
657 |
+
type: tatoeba_mt
|
658 |
+
args: est-eng
|
659 |
+
metrics:
|
660 |
+
- name: BLEU
|
661 |
+
type: bleu
|
662 |
+
value: 58.2
|
663 |
+
- name: chr-F
|
664 |
+
type: chrf
|
665 |
+
value: 0.72437
|
666 |
+
- task:
|
667 |
+
name: Translation fin-deu
|
668 |
+
type: translation
|
669 |
+
args: fin-deu
|
670 |
+
dataset:
|
671 |
+
name: tatoeba-test-v2021-08-07
|
672 |
+
type: tatoeba_mt
|
673 |
+
args: fin-deu
|
674 |
+
metrics:
|
675 |
+
- name: BLEU
|
676 |
+
type: bleu
|
677 |
+
value: 47.3
|
678 |
+
- name: chr-F
|
679 |
+
type: chrf
|
680 |
+
value: 0.66025
|
681 |
+
- task:
|
682 |
+
name: Translation fin-eng
|
683 |
+
type: translation
|
684 |
+
args: fin-eng
|
685 |
+
dataset:
|
686 |
+
name: tatoeba-test-v2021-08-07
|
687 |
+
type: tatoeba_mt
|
688 |
+
args: fin-eng
|
689 |
+
metrics:
|
690 |
+
- name: BLEU
|
691 |
+
type: bleu
|
692 |
+
value: 53.7
|
693 |
+
- name: chr-F
|
694 |
+
type: chrf
|
695 |
+
value: 0.69685
|
696 |
+
- task:
|
697 |
+
name: Translation fin-fra
|
698 |
+
type: translation
|
699 |
+
args: fin-fra
|
700 |
+
dataset:
|
701 |
+
name: tatoeba-test-v2021-08-07
|
702 |
+
type: tatoeba_mt
|
703 |
+
args: fin-fra
|
704 |
+
metrics:
|
705 |
+
- name: BLEU
|
706 |
+
type: bleu
|
707 |
+
value: 48.3
|
708 |
+
- name: chr-F
|
709 |
+
type: chrf
|
710 |
+
value: 0.65900
|
711 |
+
- task:
|
712 |
+
name: Translation fin-por
|
713 |
+
type: translation
|
714 |
+
args: fin-por
|
715 |
+
dataset:
|
716 |
+
name: tatoeba-test-v2021-08-07
|
717 |
+
type: tatoeba_mt
|
718 |
+
args: fin-por
|
719 |
+
metrics:
|
720 |
+
- name: BLEU
|
721 |
+
type: bleu
|
722 |
+
value: 54.0
|
723 |
+
- name: chr-F
|
724 |
+
type: chrf
|
725 |
+
value: 0.72250
|
726 |
+
- task:
|
727 |
+
name: Translation fin-spa
|
728 |
+
type: translation
|
729 |
+
args: fin-spa
|
730 |
+
dataset:
|
731 |
+
name: tatoeba-test-v2021-08-07
|
732 |
+
type: tatoeba_mt
|
733 |
+
args: fin-spa
|
734 |
+
metrics:
|
735 |
+
- name: BLEU
|
736 |
+
type: bleu
|
737 |
+
value: 52.1
|
738 |
+
- name: chr-F
|
739 |
+
type: chrf
|
740 |
+
value: 0.69600
|
741 |
+
- task:
|
742 |
+
name: Translation hun-deu
|
743 |
+
type: translation
|
744 |
+
args: hun-deu
|
745 |
+
dataset:
|
746 |
+
name: tatoeba-test-v2021-08-07
|
747 |
+
type: tatoeba_mt
|
748 |
+
args: hun-deu
|
749 |
+
metrics:
|
750 |
+
- name: BLEU
|
751 |
+
type: bleu
|
752 |
+
value: 41.1
|
753 |
+
- name: chr-F
|
754 |
+
type: chrf
|
755 |
+
value: 0.62418
|
756 |
+
- task:
|
757 |
+
name: Translation hun-eng
|
758 |
+
type: translation
|
759 |
+
args: hun-eng
|
760 |
+
dataset:
|
761 |
+
name: tatoeba-test-v2021-08-07
|
762 |
+
type: tatoeba_mt
|
763 |
+
args: hun-eng
|
764 |
+
metrics:
|
765 |
+
- name: BLEU
|
766 |
+
type: bleu
|
767 |
+
value: 48.7
|
768 |
+
- name: chr-F
|
769 |
+
type: chrf
|
770 |
+
value: 0.65626
|
771 |
+
- task:
|
772 |
+
name: Translation hun-fra
|
773 |
+
type: translation
|
774 |
+
args: hun-fra
|
775 |
+
dataset:
|
776 |
+
name: tatoeba-test-v2021-08-07
|
777 |
+
type: tatoeba_mt
|
778 |
+
args: hun-fra
|
779 |
+
metrics:
|
780 |
+
- name: BLEU
|
781 |
+
type: bleu
|
782 |
+
value: 50.3
|
783 |
+
- name: chr-F
|
784 |
+
type: chrf
|
785 |
+
value: 0.66840
|
786 |
+
- task:
|
787 |
+
name: Translation hun-por
|
788 |
+
type: translation
|
789 |
+
args: hun-por
|
790 |
+
dataset:
|
791 |
+
name: tatoeba-test-v2021-08-07
|
792 |
+
type: tatoeba_mt
|
793 |
+
args: hun-por
|
794 |
+
metrics:
|
795 |
+
- name: BLEU
|
796 |
+
type: bleu
|
797 |
+
value: 43.1
|
798 |
+
- name: chr-F
|
799 |
+
type: chrf
|
800 |
+
value: 0.65281
|
801 |
+
- task:
|
802 |
+
name: Translation hun-spa
|
803 |
+
type: translation
|
804 |
+
args: hun-spa
|
805 |
+
dataset:
|
806 |
+
name: tatoeba-test-v2021-08-07
|
807 |
+
type: tatoeba_mt
|
808 |
+
args: hun-spa
|
809 |
+
metrics:
|
810 |
+
- name: BLEU
|
811 |
+
type: bleu
|
812 |
+
value: 48.7
|
813 |
+
- name: chr-F
|
814 |
+
type: chrf
|
815 |
+
value: 0.67467
|
816 |
+
- task:
|
817 |
+
name: Translation multi-multi
|
818 |
+
type: translation
|
819 |
+
args: multi-multi
|
820 |
+
dataset:
|
821 |
+
name: tatoeba-test-v2020-07-28-v2023-09-26
|
822 |
+
type: tatoeba_mt
|
823 |
+
args: multi-multi
|
824 |
+
metrics:
|
825 |
+
- name: BLEU
|
826 |
+
type: bleu
|
827 |
+
value: 44.6
|
828 |
+
- name: chr-F
|
829 |
+
type: chrf
|
830 |
+
value: 0.63895
|
831 |
+
- task:
|
832 |
+
name: Translation hun-deu
|
833 |
+
type: translation
|
834 |
+
args: hun-deu
|
835 |
+
dataset:
|
836 |
+
name: newstest2008
|
837 |
+
type: wmt-2008-news
|
838 |
+
args: hun-deu
|
839 |
+
metrics:
|
840 |
+
- name: BLEU
|
841 |
+
type: bleu
|
842 |
+
value: 19.0
|
843 |
+
- name: chr-F
|
844 |
+
type: chrf
|
845 |
+
value: 0.50164
|
846 |
+
- task:
|
847 |
+
name: Translation hun-eng
|
848 |
+
type: translation
|
849 |
+
args: hun-eng
|
850 |
+
dataset:
|
851 |
+
name: newstest2008
|
852 |
+
type: wmt-2008-news
|
853 |
+
args: hun-eng
|
854 |
+
metrics:
|
855 |
+
- name: BLEU
|
856 |
+
type: bleu
|
857 |
+
value: 20.4
|
858 |
+
- name: chr-F
|
859 |
+
type: chrf
|
860 |
+
value: 0.49802
|
861 |
+
- task:
|
862 |
+
name: Translation hun-fra
|
863 |
+
type: translation
|
864 |
+
args: hun-fra
|
865 |
+
dataset:
|
866 |
+
name: newstest2008
|
867 |
+
type: wmt-2008-news
|
868 |
+
args: hun-fra
|
869 |
+
metrics:
|
870 |
+
- name: BLEU
|
871 |
+
type: bleu
|
872 |
+
value: 21.6
|
873 |
+
- name: chr-F
|
874 |
+
type: chrf
|
875 |
+
value: 0.51012
|
876 |
+
- task:
|
877 |
+
name: Translation hun-spa
|
878 |
+
type: translation
|
879 |
+
args: hun-spa
|
880 |
+
dataset:
|
881 |
+
name: newstest2008
|
882 |
+
type: wmt-2008-news
|
883 |
+
args: hun-spa
|
884 |
+
metrics:
|
885 |
+
- name: BLEU
|
886 |
+
type: bleu
|
887 |
+
value: 22.3
|
888 |
+
- name: chr-F
|
889 |
+
type: chrf
|
890 |
+
value: 0.50719
|
891 |
+
- task:
|
892 |
+
name: Translation hun-deu
|
893 |
+
type: translation
|
894 |
+
args: hun-deu
|
895 |
+
dataset:
|
896 |
+
name: newstest2009
|
897 |
+
type: wmt-2009-news
|
898 |
+
args: hun-deu
|
899 |
+
metrics:
|
900 |
+
- name: BLEU
|
901 |
+
type: bleu
|
902 |
+
value: 18.6
|
903 |
+
- name: chr-F
|
904 |
+
type: chrf
|
905 |
+
value: 0.49902
|
906 |
+
- task:
|
907 |
+
name: Translation hun-eng
|
908 |
+
type: translation
|
909 |
+
args: hun-eng
|
910 |
+
dataset:
|
911 |
+
name: newstest2009
|
912 |
+
type: wmt-2009-news
|
913 |
+
args: hun-eng
|
914 |
+
metrics:
|
915 |
+
- name: BLEU
|
916 |
+
type: bleu
|
917 |
+
value: 22.3
|
918 |
+
- name: chr-F
|
919 |
+
type: chrf
|
920 |
+
value: 0.50950
|
921 |
+
- task:
|
922 |
+
name: Translation hun-fra
|
923 |
+
type: translation
|
924 |
+
args: hun-fra
|
925 |
+
dataset:
|
926 |
+
name: newstest2009
|
927 |
+
type: wmt-2009-news
|
928 |
+
args: hun-fra
|
929 |
+
metrics:
|
930 |
+
- name: BLEU
|
931 |
+
type: bleu
|
932 |
+
value: 21.6
|
933 |
+
- name: chr-F
|
934 |
+
type: chrf
|
935 |
+
value: 0.50742
|
936 |
+
- task:
|
937 |
+
name: Translation hun-spa
|
938 |
+
type: translation
|
939 |
+
args: hun-spa
|
940 |
+
dataset:
|
941 |
+
name: newstest2009
|
942 |
+
type: wmt-2009-news
|
943 |
+
args: hun-spa
|
944 |
+
metrics:
|
945 |
+
- name: BLEU
|
946 |
+
type: bleu
|
947 |
+
value: 22.2
|
948 |
+
- name: chr-F
|
949 |
+
type: chrf
|
950 |
+
value: 0.50788
|
951 |
+
- task:
|
952 |
+
name: Translation fin-eng
|
953 |
+
type: translation
|
954 |
+
args: fin-eng
|
955 |
+
dataset:
|
956 |
+
name: newstest2015
|
957 |
+
type: wmt-2015-news
|
958 |
+
args: fin-eng
|
959 |
+
metrics:
|
960 |
+
- name: BLEU
|
961 |
+
type: bleu
|
962 |
+
value: 27.0
|
963 |
+
- name: chr-F
|
964 |
+
type: chrf
|
965 |
+
value: 0.55249
|
966 |
+
- task:
|
967 |
+
name: Translation fin-eng
|
968 |
+
type: translation
|
969 |
+
args: fin-eng
|
970 |
+
dataset:
|
971 |
+
name: newstest2016
|
972 |
+
type: wmt-2016-news
|
973 |
+
args: fin-eng
|
974 |
+
metrics:
|
975 |
+
- name: BLEU
|
976 |
+
type: bleu
|
977 |
+
value: 30.7
|
978 |
+
- name: chr-F
|
979 |
+
type: chrf
|
980 |
+
value: 0.57961
|
981 |
+
- task:
|
982 |
+
name: Translation fin-eng
|
983 |
+
type: translation
|
984 |
+
args: fin-eng
|
985 |
+
dataset:
|
986 |
+
name: newstest2017
|
987 |
+
type: wmt-2017-news
|
988 |
+
args: fin-eng
|
989 |
+
metrics:
|
990 |
+
- name: BLEU
|
991 |
+
type: bleu
|
992 |
+
value: 33.2
|
993 |
+
- name: chr-F
|
994 |
+
type: chrf
|
995 |
+
value: 0.59973
|
996 |
+
- task:
|
997 |
+
name: Translation est-eng
|
998 |
+
type: translation
|
999 |
+
args: est-eng
|
1000 |
+
dataset:
|
1001 |
+
name: newstest2018
|
1002 |
+
type: wmt-2018-news
|
1003 |
+
args: est-eng
|
1004 |
+
metrics:
|
1005 |
+
- name: BLEU
|
1006 |
+
type: bleu
|
1007 |
+
value: 31.5
|
1008 |
+
- name: chr-F
|
1009 |
+
type: chrf
|
1010 |
+
value: 0.59190
|
1011 |
+
- task:
|
1012 |
+
name: Translation fin-eng
|
1013 |
+
type: translation
|
1014 |
+
args: fin-eng
|
1015 |
+
dataset:
|
1016 |
+
name: newstest2018
|
1017 |
+
type: wmt-2018-news
|
1018 |
+
args: fin-eng
|
1019 |
+
metrics:
|
1020 |
+
- name: BLEU
|
1021 |
+
type: bleu
|
1022 |
+
value: 24.4
|
1023 |
+
- name: chr-F
|
1024 |
+
type: chrf
|
1025 |
+
value: 0.52373
|
1026 |
+
- task:
|
1027 |
+
name: Translation fin-eng
|
1028 |
+
type: translation
|
1029 |
+
args: fin-eng
|
1030 |
+
dataset:
|
1031 |
+
name: newstest2019
|
1032 |
+
type: wmt-2019-news
|
1033 |
+
args: fin-eng
|
1034 |
+
metrics:
|
1035 |
+
- name: BLEU
|
1036 |
+
type: bleu
|
1037 |
+
value: 30.3
|
1038 |
+
- name: chr-F
|
1039 |
+
type: chrf
|
1040 |
+
value: 0.57079
|
1041 |
+
---
|
1042 |
+
# opus-mt-tc-bible-big-fiu-deu_eng_fra_por_spa
|
1043 |
+
|
1044 |
+
## Table of Contents
|
1045 |
+
- [Model Details](#model-details)
|
1046 |
+
- [Uses](#uses)
|
1047 |
+
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
|
1048 |
+
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
|
1049 |
+
- [Training](#training)
|
1050 |
+
- [Evaluation](#evaluation)
|
1051 |
+
- [Citation Information](#citation-information)
|
1052 |
+
- [Acknowledgements](#acknowledgements)
|
1053 |
+
|
1054 |
+
## Model Details
|
1055 |
+
|
1056 |
+
Neural machine translation model for translating from Finno-Ugrian languages (fiu) to unknown (deu+eng+fra+por+spa).
|
1057 |
+
|
1058 |
+
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).
|
1059 |
+
**Model Description:**
|
1060 |
+
- **Developed by:** Language Technology Research Group at the University of Helsinki
|
1061 |
+
- **Model Type:** Translation (transformer-big)
|
1062 |
+
- **Release**: 2024-05-30
|
1063 |
+
- **License:** Apache-2.0
|
1064 |
+
- **Language(s):**
|
1065 |
+
- Source Language(s): chm est fin fkv hun izh koi kom kpv krl liv mdf mrj myv sma sme smn udm vep vot vro
|
1066 |
+
- Target Language(s): deu eng fra por spa
|
1067 |
+
- Valid Target Language Labels: >>deu<< >>eng<< >>fra<< >>por<< >>spa<< >>xxx<<
|
1068 |
+
- **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
|
1069 |
+
- **Resources for more information:**
|
1070 |
+
- [OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/fiu-deu%2Beng%2Bfra%2Bpor%2Bspa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
|
1071 |
+
- [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
|
1072 |
+
- [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
|
1073 |
+
- [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/)
|
1074 |
+
- [HPLT bilingual data v1 (as part of the Tatoeba Translation Challenge dataset)](https://hplt-project.org/datasets/v1)
|
1075 |
+
- [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)
|
1076 |
+
|
1077 |
+
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<<`
|
1078 |
+
|
1079 |
+
## Uses
|
1080 |
+
|
1081 |
+
This model can be used for translation and text-to-text generation.
|
1082 |
+
|
1083 |
+
## Risks, Limitations and Biases
|
1084 |
+
|
1085 |
+
**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.**
|
1086 |
+
|
1087 |
+
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)).
|
1088 |
+
|
1089 |
+
## How to Get Started With the Model
|
1090 |
+
|
1091 |
+
A short example code:
|
1092 |
+
|
1093 |
+
```python
|
1094 |
+
from transformers import MarianMTModel, MarianTokenizer
|
1095 |
+
|
1096 |
+
src_text = [
|
1097 |
+
">>deu<< Replace this with text in an accepted source language.",
|
1098 |
+
">>spa<< This is the second sentence."
|
1099 |
+
]
|
1100 |
+
|
1101 |
+
model_name = "pytorch-models/opus-mt-tc-bible-big-fiu-deu_eng_fra_por_spa"
|
1102 |
+
tokenizer = MarianTokenizer.from_pretrained(model_name)
|
1103 |
+
model = MarianMTModel.from_pretrained(model_name)
|
1104 |
+
translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
|
1105 |
+
|
1106 |
+
for t in translated:
|
1107 |
+
print( tokenizer.decode(t, skip_special_tokens=True) )
|
1108 |
+
```
|
1109 |
+
|
1110 |
+
You can also use OPUS-MT models with the transformers pipelines, for example:
|
1111 |
+
|
1112 |
+
```python
|
1113 |
+
from transformers import pipeline
|
1114 |
+
pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-bible-big-fiu-deu_eng_fra_por_spa")
|
1115 |
+
print(pipe(">>deu<< Replace this with text in an accepted source language."))
|
1116 |
+
```
|
1117 |
+
|
1118 |
+
## Training
|
1119 |
+
|
1120 |
+
- **Data**: opusTCv20230926max50+bt+jhubc ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
|
1121 |
+
- **Pre-processing**: SentencePiece (spm32k,spm32k)
|
1122 |
+
- **Model Type:** transformer-big
|
1123 |
+
- **Original MarianNMT Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
|
1124 |
+
- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
|
1125 |
+
|
1126 |
+
## Evaluation
|
1127 |
+
|
1128 |
+
* [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/fiu-deu%2Beng%2Bfra%2Bpor%2Bspa/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
|
1129 |
+
* test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt)
|
1130 |
+
* test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/fiu-deu+eng+fra+por+spa/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt)
|
1131 |
+
* benchmark results: [benchmark_results.txt](benchmark_results.txt)
|
1132 |
+
* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
|
1133 |
+
|
1134 |
+
| langpair | testset | chr-F | BLEU | #sent | #words |
|
1135 |
+
|----------|---------|-------|-------|-------|--------|
|
1136 |
+
| est-deu | tatoeba-test-v2021-08-07 | 0.69451 | 53.9 | 244 | 1611 |
|
1137 |
+
| est-eng | tatoeba-test-v2021-08-07 | 0.72437 | 58.2 | 1359 | 8811 |
|
1138 |
+
| fin-deu | tatoeba-test-v2021-08-07 | 0.66025 | 47.3 | 2647 | 19163 |
|
1139 |
+
| fin-eng | tatoeba-test-v2021-08-07 | 0.69685 | 53.7 | 10690 | 80552 |
|
1140 |
+
| fin-fra | tatoeba-test-v2021-08-07 | 0.65900 | 48.3 | 1920 | 12193 |
|
1141 |
+
| fin-por | tatoeba-test-v2021-08-07 | 0.72250 | 54.0 | 477 | 3021 |
|
1142 |
+
| fin-spa | tatoeba-test-v2021-08-07 | 0.69600 | 52.1 | 2513 | 16912 |
|
1143 |
+
| hun-deu | tatoeba-test-v2021-08-07 | 0.62418 | 41.1 | 15342 | 127344 |
|
1144 |
+
| hun-eng | tatoeba-test-v2021-08-07 | 0.65626 | 48.7 | 13037 | 94699 |
|
1145 |
+
| hun-fra | tatoeba-test-v2021-08-07 | 0.66840 | 50.3 | 2494 | 16914 |
|
1146 |
+
| hun-por | tatoeba-test-v2021-08-07 | 0.65281 | 43.1 | 2500 | 16563 |
|
1147 |
+
| hun-spa | tatoeba-test-v2021-08-07 | 0.67467 | 48.7 | 2500 | 16670 |
|
1148 |
+
| est-deu | flores101-devtest | 0.55353 | 25.7 | 1012 | 25094 |
|
1149 |
+
| est-eng | flores101-devtest | 0.61930 | 34.7 | 1012 | 24721 |
|
1150 |
+
| est-fra | flores101-devtest | 0.58199 | 31.3 | 1012 | 28343 |
|
1151 |
+
| est-por | flores101-devtest | 0.54388 | 26.5 | 1012 | 26519 |
|
1152 |
+
| fin-eng | flores101-devtest | 0.59914 | 32.2 | 1012 | 24721 |
|
1153 |
+
| fin-por | flores101-devtest | 0.55156 | 27.1 | 1012 | 26519 |
|
1154 |
+
| hun-eng | flores101-devtest | 0.61198 | 33.5 | 1012 | 24721 |
|
1155 |
+
| hun-fra | flores101-devtest | 0.57776 | 30.8 | 1012 | 28343 |
|
1156 |
+
| hun-por | flores101-devtest | 0.56263 | 28.4 | 1012 | 26519 |
|
1157 |
+
| hun-spa | flores101-devtest | 0.49140 | 20.7 | 1012 | 29199 |
|
1158 |
+
| est-deu | flores200-devtest | 0.55825 | 26.3 | 1012 | 25094 |
|
1159 |
+
| est-eng | flores200-devtest | 0.62404 | 35.4 | 1012 | 24721 |
|
1160 |
+
| est-fra | flores200-devtest | 0.58580 | 31.7 | 1012 | 28343 |
|
1161 |
+
| est-por | flores200-devtest | 0.55070 | 27.3 | 1012 | 26519 |
|
1162 |
+
| est-spa | flores200-devtest | 0.50188 | 21.5 | 1012 | 29199 |
|
1163 |
+
| fin-deu | flores200-devtest | 0.54281 | 24.0 | 1012 | 25094 |
|
1164 |
+
| fin-eng | flores200-devtest | 0.60642 | 33.1 | 1012 | 24721 |
|
1165 |
+
| fin-fra | flores200-devtest | 0.57540 | 30.5 | 1012 | 28343 |
|
1166 |
+
| fin-por | flores200-devtest | 0.55497 | 27.4 | 1012 | 26519 |
|
1167 |
+
| fin-spa | flores200-devtest | 0.49847 | 21.4 | 1012 | 29199 |
|
1168 |
+
| hun-deu | flores200-devtest | 0.55180 | 25.1 | 1012 | 25094 |
|
1169 |
+
| hun-eng | flores200-devtest | 0.61466 | 34.0 | 1012 | 24721 |
|
1170 |
+
| hun-fra | flores200-devtest | 0.57670 | 30.6 | 1012 | 28343 |
|
1171 |
+
| hun-por | flores200-devtest | 0.56510 | 28.9 | 1012 | 26519 |
|
1172 |
+
| hun-spa | flores200-devtest | 0.49681 | 21.3 | 1012 | 29199 |
|
1173 |
+
| hun-deu | newssyscomb2009 | 0.49819 | 17.9 | 502 | 11271 |
|
1174 |
+
| hun-eng | newssyscomb2009 | 0.52063 | 24.4 | 502 | 11818 |
|
1175 |
+
| hun-fra | newssyscomb2009 | 0.51589 | 22.0 | 502 | 12331 |
|
1176 |
+
| hun-spa | newssyscomb2009 | 0.51508 | 22.7 | 502 | 12503 |
|
1177 |
+
| hun-deu | newstest2008 | 0.50164 | 19.0 | 2051 | 47447 |
|
1178 |
+
| hun-eng | newstest2008 | 0.49802 | 20.4 | 2051 | 49380 |
|
1179 |
+
| hun-fra | newstest2008 | 0.51012 | 21.6 | 2051 | 52685 |
|
1180 |
+
| hun-spa | newstest2008 | 0.50719 | 22.3 | 2051 | 52586 |
|
1181 |
+
| hun-deu | newstest2009 | 0.49902 | 18.6 | 2525 | 62816 |
|
1182 |
+
| hun-eng | newstest2009 | 0.50950 | 22.3 | 2525 | 65399 |
|
1183 |
+
| hun-fra | newstest2009 | 0.50742 | 21.6 | 2525 | 69263 |
|
1184 |
+
| hun-spa | newstest2009 | 0.50788 | 22.2 | 2525 | 68111 |
|
1185 |
+
| fin-eng | newstest2015 | 0.55249 | 27.0 | 1370 | 27270 |
|
1186 |
+
| fin-eng | newstest2016 | 0.57961 | 30.7 | 3000 | 62945 |
|
1187 |
+
| fin-eng | newstest2017 | 0.59973 | 33.2 | 3002 | 61846 |
|
1188 |
+
| est-eng | newstest2018 | 0.59190 | 31.5 | 2000 | 45405 |
|
1189 |
+
| fin-eng | newstest2018 | 0.52373 | 24.4 | 3000 | 62325 |
|
1190 |
+
| fin-eng | newstest2019 | 0.57079 | 30.3 | 1996 | 36215 |
|
1191 |
+
| fin-eng | newstestB2017 | 0.56420 | 28.9 | 3002 | 61846 |
|
1192 |
+
| est-deu | ntrex128 | 0.51377 | 21.4 | 1997 | 48761 |
|
1193 |
+
| est-eng | ntrex128 | 0.58358 | 29.9 | 1997 | 47673 |
|
1194 |
+
| est-fra | ntrex128 | 0.52713 | 24.9 | 1997 | 53481 |
|
1195 |
+
| est-por | ntrex128 | 0.50745 | 22.2 | 1997 | 51631 |
|
1196 |
+
| est-spa | ntrex128 | 0.54304 | 27.5 | 1997 | 54107 |
|
1197 |
+
| fin-deu | ntrex128 | 0.50282 | 19.8 | 1997 | 48761 |
|
1198 |
+
| fin-eng | ntrex128 | 0.55545 | 26.3 | 1997 | 47673 |
|
1199 |
+
| fin-fra | ntrex128 | 0.50946 | 22.9 | 1997 | 53481 |
|
1200 |
+
| fin-por | ntrex128 | 0.50404 | 21.3 | 1997 | 51631 |
|
1201 |
+
| fin-spa | ntrex128 | 0.52641 | 25.5 | 1997 | 54107 |
|
1202 |
+
| hun-deu | ntrex128 | 0.49322 | 18.5 | 1997 | 48761 |
|
1203 |
+
| hun-eng | ntrex128 | 0.52964 | 23.3 | 1997 | 47673 |
|
1204 |
+
| hun-fra | ntrex128 | 0.49800 | 21.8 | 1997 | 53481 |
|
1205 |
+
| hun-por | ntrex128 | 0.48941 | 20.5 | 1997 | 51631 |
|
1206 |
+
| hun-spa | ntrex128 | 0.51123 | 24.2 | 1997 | 54107 |
|
1207 |
+
|
1208 |
+
## Citation Information
|
1209 |
+
|
1210 |
+
* 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.)
|
1211 |
+
|
1212 |
+
```bibtex
|
1213 |
+
@article{tiedemann2023democratizing,
|
1214 |
+
title={Democratizing neural machine translation with {OPUS-MT}},
|
1215 |
+
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},
|
1216 |
+
journal={Language Resources and Evaluation},
|
1217 |
+
number={58},
|
1218 |
+
pages={713--755},
|
1219 |
+
year={2023},
|
1220 |
+
publisher={Springer Nature},
|
1221 |
+
issn={1574-0218},
|
1222 |
+
doi={10.1007/s10579-023-09704-w}
|
1223 |
+
}
|
1224 |
+
|
1225 |
+
@inproceedings{tiedemann-thottingal-2020-opus,
|
1226 |
+
title = "{OPUS}-{MT} {--} Building open translation services for the World",
|
1227 |
+
author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh},
|
1228 |
+
booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
|
1229 |
+
month = nov,
|
1230 |
+
year = "2020",
|
1231 |
+
address = "Lisboa, Portugal",
|
1232 |
+
publisher = "European Association for Machine Translation",
|
1233 |
+
url = "https://aclanthology.org/2020.eamt-1.61",
|
1234 |
+
pages = "479--480",
|
1235 |
+
}
|
1236 |
+
|
1237 |
+
@inproceedings{tiedemann-2020-tatoeba,
|
1238 |
+
title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
|
1239 |
+
author = {Tiedemann, J{\"o}rg},
|
1240 |
+
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
|
1241 |
+
month = nov,
|
1242 |
+
year = "2020",
|
1243 |
+
address = "Online",
|
1244 |
+
publisher = "Association for Computational Linguistics",
|
1245 |
+
url = "https://aclanthology.org/2020.wmt-1.139",
|
1246 |
+
pages = "1174--1182",
|
1247 |
+
}
|
1248 |
+
```
|
1249 |
+
|
1250 |
+
## Acknowledgements
|
1251 |
+
|
1252 |
+
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/).
|
1253 |
+
|
1254 |
+
## Model conversion info
|
1255 |
+
|
1256 |
+
* transformers version: 4.45.1
|
1257 |
+
* OPUS-MT git hash: 0882077
|
1258 |
+
* port time: Tue Oct 8 10:53:49 EEST 2024
|
1259 |
+
* port machine: LM0-400-22516.local
|
benchmark_results.txt
ADDED
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
multi-multi tatoeba-test-v2020-07-28-v2023-09-26 0.63895 44.6 10000 77412
|
2 |
+
est-deu flores101-devtest 0.55353 25.7 1012 25094
|
3 |
+
est-eng flores101-devtest 0.61930 34.7 1012 24721
|
4 |
+
est-fra flores101-devtest 0.58199 31.3 1012 28343
|
5 |
+
est-por flores101-devtest 0.54388 26.5 1012 26519
|
6 |
+
fin-eng flores101-devtest 0.59914 32.2 1012 24721
|
7 |
+
fin-por flores101-devtest 0.55156 27.1 1012 26519
|
8 |
+
hun-eng flores101-devtest 0.61198 33.5 1012 24721
|
9 |
+
hun-fra flores101-devtest 0.57776 30.8 1012 28343
|
10 |
+
hun-por flores101-devtest 0.56263 28.4 1012 26519
|
11 |
+
hun-spa flores101-devtest 0.49140 20.7 1012 29199
|
12 |
+
est-deu flores200-devtest 0.55825 26.3 1012 25094
|
13 |
+
est-eng flores200-devtest 0.62404 35.4 1012 24721
|
14 |
+
est-fra flores200-devtest 0.58580 31.7 1012 28343
|
15 |
+
est-por flores200-devtest 0.55070 27.3 1012 26519
|
16 |
+
est-spa flores200-devtest 0.50188 21.5 1012 29199
|
17 |
+
fin-deu flores200-devtest 0.54281 24.0 1012 25094
|
18 |
+
fin-eng flores200-devtest 0.60642 33.1 1012 24721
|
19 |
+
fin-fra flores200-devtest 0.57540 30.5 1012 28343
|
20 |
+
fin-por flores200-devtest 0.55497 27.4 1012 26519
|
21 |
+
fin-spa flores200-devtest 0.49847 21.4 1012 29199
|
22 |
+
hun-deu flores200-devtest 0.55180 25.1 1012 25094
|
23 |
+
hun-eng flores200-devtest 0.61466 34.0 1012 24721
|
24 |
+
hun-fra flores200-devtest 0.57670 30.6 1012 28343
|
25 |
+
hun-por flores200-devtest 0.56510 28.9 1012 26519
|
26 |
+
hun-spa flores200-devtest 0.49681 21.3 1012 29199
|
27 |
+
hun-deu newssyscomb2009 0.49819 17.9 502 11271
|
28 |
+
hun-eng newssyscomb2009 0.52063 24.4 502 11818
|
29 |
+
hun-fra newssyscomb2009 0.51589 22.0 502 12331
|
30 |
+
hun-spa newssyscomb2009 0.51508 22.7 502 12503
|
31 |
+
hun-deu newstest2008 0.50164 19.0 2051 47447
|
32 |
+
hun-eng newstest2008 0.49802 20.4 2051 49380
|
33 |
+
hun-fra newstest2008 0.51012 21.6 2051 52685
|
34 |
+
hun-spa newstest2008 0.50719 22.3 2051 52586
|
35 |
+
hun-deu newstest2009 0.49902 18.6 2525 62816
|
36 |
+
hun-eng newstest2009 0.50950 22.3 2525 65399
|
37 |
+
hun-fra newstest2009 0.50742 21.6 2525 69263
|
38 |
+
hun-spa newstest2009 0.50788 22.2 2525 68111
|
39 |
+
fin-eng newstest2015 0.55249 27.0 1370 27270
|
40 |
+
fin-eng newstest2016 0.57961 30.7 3000 62945
|
41 |
+
fin-eng newstest2017 0.59973 33.2 3002 61846
|
42 |
+
est-eng newstest2018 0.59190 31.5 2000 45405
|
43 |
+
fin-eng newstest2018 0.52373 24.4 3000 62325
|
44 |
+
fin-eng newstest2019 0.57079 30.3 1996 36215
|
45 |
+
fin-eng newstestB2017 0.56420 28.9 3002 61846
|
46 |
+
est-deu ntrex128 0.51377 21.4 1997 48761
|
47 |
+
est-eng ntrex128 0.58358 29.9 1997 47673
|
48 |
+
est-fra ntrex128 0.52713 24.9 1997 53481
|
49 |
+
est-por ntrex128 0.50745 22.2 1997 51631
|
50 |
+
est-spa ntrex128 0.54304 27.5 1997 54107
|
51 |
+
fin-deu ntrex128 0.50282 19.8 1997 48761
|
52 |
+
fin-eng ntrex128 0.55545 26.3 1997 47673
|
53 |
+
fin-fra ntrex128 0.50946 22.9 1997 53481
|
54 |
+
fin-por ntrex128 0.50404 21.3 1997 51631
|
55 |
+
fin-spa ntrex128 0.52641 25.5 1997 54107
|
56 |
+
hun-deu ntrex128 0.49322 18.5 1997 48761
|
57 |
+
hun-eng ntrex128 0.52964 23.3 1997 47673
|
58 |
+
hun-fra ntrex128 0.49800 21.8 1997 53481
|
59 |
+
hun-por ntrex128 0.48941 20.5 1997 51631
|
60 |
+
hun-spa ntrex128 0.51123 24.2 1997 54107
|
61 |
+
est-deu tatoeba-test-v2020-07-28 0.67936 51.8 217 1390
|
62 |
+
fin-eng tatoeba-test-v2020-07-28 0.69200 53.1 10000 74651
|
63 |
+
fin-fra tatoeba-test-v2020-07-28 0.65899 48.2 1930 12229
|
64 |
+
fin-spa tatoeba-test-v2020-07-28 0.69327 51.4 2500 16828
|
65 |
+
hun-deu tatoeba-test-v2020-07-28 0.62890 41.9 10000 81699
|
66 |
+
hun-eng tatoeba-test-v2020-07-28 0.67153 51.1 10000 69326
|
67 |
+
hun-fra tatoeba-test-v2020-07-28 0.66663 49.9 2500 16940
|
68 |
+
fin-deu tatoeba-test-v2021-03-30 0.65542 46.9 4984 36070
|
69 |
+
fin-eng tatoeba-test-v2021-03-30 0.69200 53.1 10186 76206
|
70 |
+
fin-spa tatoeba-test-v2021-03-30 0.69377 51.5 4999 33655
|
71 |
+
hun-deu tatoeba-test-v2021-03-30 0.62256 40.9 12232 101962
|
72 |
+
hun-eng tatoeba-test-v2021-03-30 0.65658 49.0 11904 85120
|
73 |
+
hun-fra tatoeba-test-v2021-03-30 0.66663 49.9 2500 16940
|
74 |
+
est-deu tatoeba-test-v2021-08-07 0.69451 53.9 244 1611
|
75 |
+
est-eng tatoeba-test-v2021-08-07 0.72437 58.2 1359 8811
|
76 |
+
fin-deu tatoeba-test-v2021-08-07 0.66025 47.3 2647 19163
|
77 |
+
fin-eng tatoeba-test-v2021-08-07 0.69685 53.7 10690 80552
|
78 |
+
fin-fra tatoeba-test-v2021-08-07 0.65900 48.3 1920 12193
|
79 |
+
fin-por tatoeba-test-v2021-08-07 0.72250 54.0 477 3021
|
80 |
+
fin-spa tatoeba-test-v2021-08-07 0.69600 52.1 2513 16912
|
81 |
+
hun-deu tatoeba-test-v2021-08-07 0.62418 41.1 15342 127344
|
82 |
+
hun-eng tatoeba-test-v2021-08-07 0.65626 48.7 13037 94699
|
83 |
+
hun-fra tatoeba-test-v2021-08-07 0.66840 50.3 2494 16914
|
84 |
+
hun-por tatoeba-test-v2021-08-07 0.65281 43.1 2500 16563
|
85 |
+
hun-spa tatoeba-test-v2021-08-07 0.67467 48.7 2500 16670
|
benchmark_translations.zip
ADDED
File without changes
|
config.json
ADDED
@@ -0,0 +1,41 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "pytorch-models/opus-mt-tc-bible-big-fiu-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": 59381,
|
17 |
+
"decoder_vocab_size": 59382,
|
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": 618,
|
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": 59381,
|
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": 59382
|
41 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_from_model_config": true,
|
3 |
+
"bad_words_ids": [
|
4 |
+
[
|
5 |
+
59381
|
6 |
+
]
|
7 |
+
],
|
8 |
+
"bos_token_id": 0,
|
9 |
+
"decoder_start_token_id": 59381,
|
10 |
+
"eos_token_id": 618,
|
11 |
+
"forced_eos_token_id": 618,
|
12 |
+
"max_length": 512,
|
13 |
+
"num_beams": 4,
|
14 |
+
"pad_token_id": 59381,
|
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:b23ffb5221b498df0eaab1c7046ed101a43b7e97966229500e39681ac5c38617
|
3 |
+
size 948925320
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:cffc6805a38de06c3222152598bb2532ef9064fc5a8be3f2e4f4ef57d1dde00d
|
3 |
+
size 948976581
|
source.spm
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4a365d3ea133001d011349c9b6b9a6afb40ff7653f94459588498632e10430b2
|
3 |
+
size 822563
|
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:de58b541da4a4e79c0f5fd576ad934f66a33c36161f00499cd852eb122ab8ac3
|
3 |
+
size 811921
|
tokenizer_config.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"source_lang": "fiu", "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_2024-05-30/fiu-deu+eng+fra+por+spa", "tokenizer_class": "MarianTokenizer"}
|
vocab.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|