model dump
Browse files- README.md +348 -0
- config.json +67 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- train.args +1 -0
README.md
ADDED
@@ -0,0 +1,348 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
|
2 |
+
---
|
3 |
+
language:
|
4 |
+
- nl
|
5 |
+
license: apache-2.0
|
6 |
+
library_name: transformers
|
7 |
+
tags:
|
8 |
+
- part-of-speech
|
9 |
+
- token-classification
|
10 |
+
datasets:
|
11 |
+
- universal_dependencies
|
12 |
+
metrics:
|
13 |
+
- accuracy
|
14 |
+
|
15 |
+
model-index:
|
16 |
+
- name: xlm-roberta-base-ft-udpos28-nl
|
17 |
+
results:
|
18 |
+
- task:
|
19 |
+
type: token-classification
|
20 |
+
name: Part-of-Speech Tagging
|
21 |
+
dataset:
|
22 |
+
type: universal_dependencies
|
23 |
+
name: Universal Dependencies v2.8
|
24 |
+
metrics:
|
25 |
+
- type: accuracy
|
26 |
+
name: English Test accuracy
|
27 |
+
value: 88.8
|
28 |
+
- type: accuracy
|
29 |
+
name: Dutch Test accuracy
|
30 |
+
value: 97.0
|
31 |
+
- type: accuracy
|
32 |
+
name: German Test accuracy
|
33 |
+
value: 89.0
|
34 |
+
- type: accuracy
|
35 |
+
name: Italian Test accuracy
|
36 |
+
value: 89.9
|
37 |
+
- type: accuracy
|
38 |
+
name: French Test accuracy
|
39 |
+
value: 88.1
|
40 |
+
- type: accuracy
|
41 |
+
name: Spanish Test accuracy
|
42 |
+
value: 90.5
|
43 |
+
- type: accuracy
|
44 |
+
name: Russian Test accuracy
|
45 |
+
value: 89.2
|
46 |
+
- type: accuracy
|
47 |
+
name: Swedish Test accuracy
|
48 |
+
value: 90.7
|
49 |
+
- type: accuracy
|
50 |
+
name: Norwegian Test accuracy
|
51 |
+
value: 87.6
|
52 |
+
- type: accuracy
|
53 |
+
name: Danish Test accuracy
|
54 |
+
value: 89.0
|
55 |
+
- type: accuracy
|
56 |
+
name: Low Saxon Test accuracy
|
57 |
+
value: 58.3
|
58 |
+
- type: accuracy
|
59 |
+
name: Akkadian Test accuracy
|
60 |
+
value: 22.9
|
61 |
+
- type: accuracy
|
62 |
+
name: Armenian Test accuracy
|
63 |
+
value: 86.7
|
64 |
+
- type: accuracy
|
65 |
+
name: Welsh Test accuracy
|
66 |
+
value: 70.2
|
67 |
+
- type: accuracy
|
68 |
+
name: Old East Slavic Test accuracy
|
69 |
+
value: 73.5
|
70 |
+
- type: accuracy
|
71 |
+
name: Albanian Test accuracy
|
72 |
+
value: 78.9
|
73 |
+
- type: accuracy
|
74 |
+
name: Slovenian Test accuracy
|
75 |
+
value: 76.3
|
76 |
+
- type: accuracy
|
77 |
+
name: Guajajara Test accuracy
|
78 |
+
value: 22.1
|
79 |
+
- type: accuracy
|
80 |
+
name: Kurmanji Test accuracy
|
81 |
+
value: 78.3
|
82 |
+
- type: accuracy
|
83 |
+
name: Turkish Test accuracy
|
84 |
+
value: 78.3
|
85 |
+
- type: accuracy
|
86 |
+
name: Finnish Test accuracy
|
87 |
+
value: 86.2
|
88 |
+
- type: accuracy
|
89 |
+
name: Indonesian Test accuracy
|
90 |
+
value: 85.4
|
91 |
+
- type: accuracy
|
92 |
+
name: Ukrainian Test accuracy
|
93 |
+
value: 85.8
|
94 |
+
- type: accuracy
|
95 |
+
name: Polish Test accuracy
|
96 |
+
value: 86.3
|
97 |
+
- type: accuracy
|
98 |
+
name: Portuguese Test accuracy
|
99 |
+
value: 90.0
|
100 |
+
- type: accuracy
|
101 |
+
name: Kazakh Test accuracy
|
102 |
+
value: 83.0
|
103 |
+
- type: accuracy
|
104 |
+
name: Latin Test accuracy
|
105 |
+
value: 79.0
|
106 |
+
- type: accuracy
|
107 |
+
name: Old French Test accuracy
|
108 |
+
value: 53.1
|
109 |
+
- type: accuracy
|
110 |
+
name: Buryat Test accuracy
|
111 |
+
value: 58.4
|
112 |
+
- type: accuracy
|
113 |
+
name: Kaapor Test accuracy
|
114 |
+
value: 13.8
|
115 |
+
- type: accuracy
|
116 |
+
name: Korean Test accuracy
|
117 |
+
value: 62.2
|
118 |
+
- type: accuracy
|
119 |
+
name: Estonian Test accuracy
|
120 |
+
value: 87.6
|
121 |
+
- type: accuracy
|
122 |
+
name: Croatian Test accuracy
|
123 |
+
value: 87.6
|
124 |
+
- type: accuracy
|
125 |
+
name: Gothic Test accuracy
|
126 |
+
value: 16.5
|
127 |
+
- type: accuracy
|
128 |
+
name: Swiss German Test accuracy
|
129 |
+
value: 48.3
|
130 |
+
- type: accuracy
|
131 |
+
name: Assyrian Test accuracy
|
132 |
+
value: 14.6
|
133 |
+
- type: accuracy
|
134 |
+
name: North Sami Test accuracy
|
135 |
+
value: 36.5
|
136 |
+
- type: accuracy
|
137 |
+
name: Naija Test accuracy
|
138 |
+
value: 36.0
|
139 |
+
- type: accuracy
|
140 |
+
name: Latvian Test accuracy
|
141 |
+
value: 86.6
|
142 |
+
- type: accuracy
|
143 |
+
name: Chinese Test accuracy
|
144 |
+
value: 47.9
|
145 |
+
- type: accuracy
|
146 |
+
name: Tagalog Test accuracy
|
147 |
+
value: 73.9
|
148 |
+
- type: accuracy
|
149 |
+
name: Bambara Test accuracy
|
150 |
+
value: 29.7
|
151 |
+
- type: accuracy
|
152 |
+
name: Lithuanian Test accuracy
|
153 |
+
value: 85.7
|
154 |
+
- type: accuracy
|
155 |
+
name: Galician Test accuracy
|
156 |
+
value: 87.4
|
157 |
+
- type: accuracy
|
158 |
+
name: Vietnamese Test accuracy
|
159 |
+
value: 65.1
|
160 |
+
- type: accuracy
|
161 |
+
name: Greek Test accuracy
|
162 |
+
value: 86.3
|
163 |
+
- type: accuracy
|
164 |
+
name: Catalan Test accuracy
|
165 |
+
value: 89.5
|
166 |
+
- type: accuracy
|
167 |
+
name: Czech Test accuracy
|
168 |
+
value: 87.3
|
169 |
+
- type: accuracy
|
170 |
+
name: Erzya Test accuracy
|
171 |
+
value: 43.0
|
172 |
+
- type: accuracy
|
173 |
+
name: Bhojpuri Test accuracy
|
174 |
+
value: 48.5
|
175 |
+
- type: accuracy
|
176 |
+
name: Thai Test accuracy
|
177 |
+
value: 58.1
|
178 |
+
- type: accuracy
|
179 |
+
name: Marathi Test accuracy
|
180 |
+
value: 87.7
|
181 |
+
- type: accuracy
|
182 |
+
name: Basque Test accuracy
|
183 |
+
value: 78.2
|
184 |
+
- type: accuracy
|
185 |
+
name: Slovak Test accuracy
|
186 |
+
value: 88.2
|
187 |
+
- type: accuracy
|
188 |
+
name: Kiche Test accuracy
|
189 |
+
value: 28.2
|
190 |
+
- type: accuracy
|
191 |
+
name: Yoruba Test accuracy
|
192 |
+
value: 19.5
|
193 |
+
- type: accuracy
|
194 |
+
name: Warlpiri Test accuracy
|
195 |
+
value: 27.9
|
196 |
+
- type: accuracy
|
197 |
+
name: Tamil Test accuracy
|
198 |
+
value: 84.3
|
199 |
+
- type: accuracy
|
200 |
+
name: Maltese Test accuracy
|
201 |
+
value: 19.2
|
202 |
+
- type: accuracy
|
203 |
+
name: Ancient Greek Test accuracy
|
204 |
+
value: 66.3
|
205 |
+
- type: accuracy
|
206 |
+
name: Icelandic Test accuracy
|
207 |
+
value: 84.3
|
208 |
+
- type: accuracy
|
209 |
+
name: Mbya Guarani Test accuracy
|
210 |
+
value: 25.6
|
211 |
+
- type: accuracy
|
212 |
+
name: Urdu Test accuracy
|
213 |
+
value: 68.5
|
214 |
+
- type: accuracy
|
215 |
+
name: Romanian Test accuracy
|
216 |
+
value: 83.8
|
217 |
+
- type: accuracy
|
218 |
+
name: Persian Test accuracy
|
219 |
+
value: 78.3
|
220 |
+
- type: accuracy
|
221 |
+
name: Apurina Test accuracy
|
222 |
+
value: 27.3
|
223 |
+
- type: accuracy
|
224 |
+
name: Japanese Test accuracy
|
225 |
+
value: 34.1
|
226 |
+
- type: accuracy
|
227 |
+
name: Hungarian Test accuracy
|
228 |
+
value: 87.2
|
229 |
+
- type: accuracy
|
230 |
+
name: Hindi Test accuracy
|
231 |
+
value: 73.3
|
232 |
+
- type: accuracy
|
233 |
+
name: Classical Chinese Test accuracy
|
234 |
+
value: 28.3
|
235 |
+
- type: accuracy
|
236 |
+
name: Komi Permyak Test accuracy
|
237 |
+
value: 45.1
|
238 |
+
- type: accuracy
|
239 |
+
name: Faroese Test accuracy
|
240 |
+
value: 78.3
|
241 |
+
- type: accuracy
|
242 |
+
name: Sanskrit Test accuracy
|
243 |
+
value: 30.3
|
244 |
+
- type: accuracy
|
245 |
+
name: Livvi Test accuracy
|
246 |
+
value: 63.1
|
247 |
+
- type: accuracy
|
248 |
+
name: Arabic Test accuracy
|
249 |
+
value: 80.0
|
250 |
+
- type: accuracy
|
251 |
+
name: Wolof Test accuracy
|
252 |
+
value: 27.7
|
253 |
+
- type: accuracy
|
254 |
+
name: Bulgarian Test accuracy
|
255 |
+
value: 89.2
|
256 |
+
- type: accuracy
|
257 |
+
name: Akuntsu Test accuracy
|
258 |
+
value: 28.0
|
259 |
+
- type: accuracy
|
260 |
+
name: Makurap Test accuracy
|
261 |
+
value: 7.5
|
262 |
+
- type: accuracy
|
263 |
+
name: Kangri Test accuracy
|
264 |
+
value: 44.9
|
265 |
+
- type: accuracy
|
266 |
+
name: Breton Test accuracy
|
267 |
+
value: 65.8
|
268 |
+
- type: accuracy
|
269 |
+
name: Telugu Test accuracy
|
270 |
+
value: 85.7
|
271 |
+
- type: accuracy
|
272 |
+
name: Cantonese Test accuracy
|
273 |
+
value: 50.7
|
274 |
+
- type: accuracy
|
275 |
+
name: Old Church Slavonic Test accuracy
|
276 |
+
value: 49.4
|
277 |
+
- type: accuracy
|
278 |
+
name: Karelian Test accuracy
|
279 |
+
value: 73.5
|
280 |
+
- type: accuracy
|
281 |
+
name: Upper Sorbian Test accuracy
|
282 |
+
value: 70.9
|
283 |
+
- type: accuracy
|
284 |
+
name: South Levantine Arabic Test accuracy
|
285 |
+
value: 64.8
|
286 |
+
- type: accuracy
|
287 |
+
name: Komi Zyrian Test accuracy
|
288 |
+
value: 37.1
|
289 |
+
- type: accuracy
|
290 |
+
name: Irish Test accuracy
|
291 |
+
value: 68.9
|
292 |
+
- type: accuracy
|
293 |
+
name: Nayini Test accuracy
|
294 |
+
value: 46.2
|
295 |
+
- type: accuracy
|
296 |
+
name: Munduruku Test accuracy
|
297 |
+
value: 12.3
|
298 |
+
- type: accuracy
|
299 |
+
name: Manx Test accuracy
|
300 |
+
value: 35.7
|
301 |
+
- type: accuracy
|
302 |
+
name: Skolt Sami Test accuracy
|
303 |
+
value: 30.1
|
304 |
+
- type: accuracy
|
305 |
+
name: Afrikaans Test accuracy
|
306 |
+
value: 88.4
|
307 |
+
- type: accuracy
|
308 |
+
name: Old Turkish Test accuracy
|
309 |
+
value: 37.1
|
310 |
+
- type: accuracy
|
311 |
+
name: Tupinamba Test accuracy
|
312 |
+
value: 24.9
|
313 |
+
- type: accuracy
|
314 |
+
name: Belarusian Test accuracy
|
315 |
+
value: 87.2
|
316 |
+
- type: accuracy
|
317 |
+
name: Serbian Test accuracy
|
318 |
+
value: 89.0
|
319 |
+
- type: accuracy
|
320 |
+
name: Moksha Test accuracy
|
321 |
+
value: 41.5
|
322 |
+
- type: accuracy
|
323 |
+
name: Western Armenian Test accuracy
|
324 |
+
value: 79.0
|
325 |
+
- type: accuracy
|
326 |
+
name: Scottish Gaelic Test accuracy
|
327 |
+
value: 59.5
|
328 |
+
- type: accuracy
|
329 |
+
name: Khunsari Test accuracy
|
330 |
+
value: 40.5
|
331 |
+
- type: accuracy
|
332 |
+
name: Hebrew Test accuracy
|
333 |
+
value: 94.8
|
334 |
+
- type: accuracy
|
335 |
+
name: Uyghur Test accuracy
|
336 |
+
value: 77.2
|
337 |
+
- type: accuracy
|
338 |
+
name: Chukchi Test accuracy
|
339 |
+
value: 30.5
|
340 |
+
---
|
341 |
+
|
342 |
+
# XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Dutch
|
343 |
+
|
344 |
+
This model is part of our paper called:
|
345 |
+
|
346 |
+
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
|
347 |
+
|
348 |
+
Check the [Space]([Space](https://huggingface.co/spaces/wietsedv/xpos)) for more details.
|
config.json
ADDED
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "output/xlm-roberta-base_ft_udpos28-nl/1d6ca3e8",
|
3 |
+
"architectures": [
|
4 |
+
"XLMRobertaForTokenClassification"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.1,
|
7 |
+
"bos_token_id": 0,
|
8 |
+
"classifier_dropout": null,
|
9 |
+
"eos_token_id": 2,
|
10 |
+
"gradient_checkpointing": false,
|
11 |
+
"hidden_act": "gelu",
|
12 |
+
"hidden_dropout_prob": 0.1,
|
13 |
+
"hidden_size": 768,
|
14 |
+
"id2label": {
|
15 |
+
"0": "ADJ",
|
16 |
+
"1": "ADP",
|
17 |
+
"2": "ADV",
|
18 |
+
"3": "AUX",
|
19 |
+
"4": "CCONJ",
|
20 |
+
"5": "DET",
|
21 |
+
"6": "INTJ",
|
22 |
+
"7": "NOUN",
|
23 |
+
"8": "NUM",
|
24 |
+
"9": "PART",
|
25 |
+
"10": "PRON",
|
26 |
+
"11": "PROPN",
|
27 |
+
"12": "PUNCT",
|
28 |
+
"13": "SCONJ",
|
29 |
+
"14": "SYM",
|
30 |
+
"15": "VERB",
|
31 |
+
"16": "X"
|
32 |
+
},
|
33 |
+
"initializer_range": 0.02,
|
34 |
+
"intermediate_size": 3072,
|
35 |
+
"label2id": {
|
36 |
+
"ADJ": 0,
|
37 |
+
"ADP": 1,
|
38 |
+
"ADV": 2,
|
39 |
+
"AUX": 3,
|
40 |
+
"CCONJ": 4,
|
41 |
+
"DET": 5,
|
42 |
+
"INTJ": 6,
|
43 |
+
"NOUN": 7,
|
44 |
+
"NUM": 8,
|
45 |
+
"PART": 9,
|
46 |
+
"PRON": 10,
|
47 |
+
"PROPN": 11,
|
48 |
+
"PUNCT": 12,
|
49 |
+
"SCONJ": 13,
|
50 |
+
"SYM": 14,
|
51 |
+
"VERB": 15,
|
52 |
+
"X": 16
|
53 |
+
},
|
54 |
+
"layer_norm_eps": 1e-05,
|
55 |
+
"max_position_embeddings": 514,
|
56 |
+
"model_type": "xlm-roberta",
|
57 |
+
"num_attention_heads": 12,
|
58 |
+
"num_hidden_layers": 12,
|
59 |
+
"output_past": true,
|
60 |
+
"pad_token_id": 1,
|
61 |
+
"position_embedding_type": "absolute",
|
62 |
+
"torch_dtype": "float32",
|
63 |
+
"transformers_version": "4.10.2",
|
64 |
+
"type_vocab_size": 1,
|
65 |
+
"use_cache": true,
|
66 |
+
"vocab_size": 250002
|
67 |
+
}
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f9e84e355d77dede2fd7750890020c3d12570be2f1734c1e415abcd20a423c37
|
3 |
+
size 1109946481
|
special_tokens_map.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": true, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "output/xlm-roberta-base_ft_udpos28-nl/1d6ca3e8", "tokenizer_class": "XLMRobertaTokenizer"}
|
train.args
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
udpos -tt=token-classification -tn=udpos28 -mi=xlm-roberta-base -mt=ft --learning_rate=5e-5 --eval_steps=1000 --eval_batch_size=10 --train_batch_size=10 --multi --max_steps=8000
|