# BERT-base for news genre classification

This is a fine-tuned version of NlpHUST/vibert4news-base-cased model for news genre classification. The training data is 3864 vietnamese news summaries in WikiMulti dataset.

<b>Labels</b>: 

0-> Agriculture, food, and drink

1-> Albums

2-> Architecture

3-> Art

4-> Biology and medicine

5-> Chemistry and materials science

6-> Classical compositions

7-> Computing and engineering

8-> Earth science

9-> Film

10-> Geography

11-> Language and literature

12-> Mathematics and mathematicians

13-> Media and drama

14-> Other music articles

15-> Philosophy

16-> Physics and astronomy

17-> Places

18-> Religion

19-> Royalty, nobility, and heraldry

20-> Songs

21-> Television

22-> Transport

23-> World history

24->Armies and military units

25->Baseball

26->Basketball

27->Battles, exercises, and conflicts

28->Culture, sociology, and psychology

29->Economics and business

30->Education

31->Football

32->Hockey

33->Law

34->Magazines and print journalism

35->Military aircraft

36->Military decorations and memorials

37->Military people

38->Motorsport

39->Multi-sport event

40->Other sports

41->Politics and government

42->Pro wrestling

43->Recreation

44->Video games

45->Warships and naval units

46->Weapons, equipment, and buildings
{"language": ["vi"], "tags": ["news classification"], "datasets": ["wikimulti"], "widget": [{"text": "Tuy nhi\u00ean, s\u1ef1 th\u1ecfa m\u00e3n l\u1ea1i ch\u1eb3ng th\u1ec3 k\u00e9o d\u00e0i. H\u1ecd nhanh ch\u00f3ng r\u01a1i v\u00e0o hoang mang khi nh\u1eadn ra \u0111\u00e3 m\u1ea5t m\u1ed9t kho\u1ea3n ti\u1ec1n l\u1edbn cho c\u00e1c m\u00f3n \u0111\u1ed3 kh\u00f4ng th\u1ef1c s\u1ef1 c\u1ea7n thi\u1ebft, ho\u1eb7c ph\u1ee5c v\u1ee5 m\u1ee5c \u0111\u00edch v\u00f4 ngh\u0129a.", "example_title": "Example 1"}, {"text": "Nh\u1eefng ng\u01b0\u1eddi b\u1ecb b\u1ec7nh gan nh\u01b0 c\u1ea5p t\u00ednh, m\u1ea1n t\u00ednh, x\u01a1 gan, vi\u00eam gan tuy\u1ec7t \u0111\u1ed1i kh\u00f4ng n\u00ean \u0103n g\u1eebng. ", "example_title": "Example 2"}]}
transformers pytorch bert text-classification news classification vi dataset:wikimulti autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #news classification #vi #dataset-wikimulti #autotrain_compatible #endpoints_compatible #region-us 

# BERT-base for news genre classification

This is a fine-tuned version of NlpHUST/vibert4news-base-cased model for news genre classification. The training data is 3864 vietnamese news summaries in WikiMulti dataset.

<b>Labels</b>: 

0-> Agriculture, food, and drink

1-> Albums

2-> Architecture

3-> Art

4-> Biology and medicine

5-> Chemistry and materials science

6-> Classical compositions

7-> Computing and engineering

8-> Earth science

9-> Film

10-> Geography

11-> Language and literature

12-> Mathematics and mathematicians

13-> Media and drama

14-> Other music articles

15-> Philosophy

16-> Physics and astronomy

17-> Places

18-> Religion

19-> Royalty, nobility, and heraldry

20-> Songs

21-> Television

22-> Transport

23-> World history

24->Armies and military units

25->Baseball

26->Basketball

27->Battles, exercises, and conflicts

28->Culture, sociology, and psychology

29->Economics and business

30->Education

31->Football

32->Hockey

33->Law

34->Magazines and print journalism

35->Military aircraft

36->Military decorations and memorials

37->Military people

38->Motorsport

39->Multi-sport event

40->Other sports

41->Politics and government

42->Pro wrestling

43->Recreation

44->Video games

45->Warships and naval units

46->Weapons, equipment, and buildings
# BERT-base for news genre classification

This is a fine-tuned version of NlpHUST/vibert4news-base-cased model for news genre classification. The training data is 3864 vietnamese news summaries in WikiMulti dataset.

<b>Labels</b>: 

0-> Agriculture, food, and drink

1-> Albums

2-> Architecture

3-> Art

4-> Biology and medicine

5-> Chemistry and materials science

6-> Classical compositions

7-> Computing and engineering

8-> Earth science

9-> Film

10-> Geography

11-> Language and literature

12-> Mathematics and mathematicians

13-> Media and drama

14-> Other music articles

15-> Philosophy

16-> Physics and astronomy

17-> Places

18-> Religion

19-> Royalty, nobility, and heraldry

20-> Songs

21-> Television

22-> Transport

23-> World history

24->Armies and military units

25->Baseball

26->Basketball

27->Battles, exercises, and conflicts

28->Culture, sociology, and psychology

29->Economics and business

30->Education

31->Football

32->Hockey

33->Law

34->Magazines and print journalism

35->Military aircraft

36->Military decorations and memorials

37->Military people

38->Motorsport

39->Multi-sport event

40->Other sports

41->Politics and government

42->Pro wrestling

43->Recreation

44->Video games

45->Warships and naval units

46->Weapons, equipment, and buildings
TAGS
#transformers #pytorch #bert #text-classification #news classification #vi #dataset-wikimulti #autotrain_compatible #endpoints_compatible #region-us 
 # BERT-base for news genre classification

This is a fine-tuned version of NlpHUST/vibert4news-base-cased model for news genre classification. The training data is 3864 vietnamese news summaries in WikiMulti dataset.

<b>Labels</b>: 

0-> Agriculture, food, and drink

1-> Albums

2-> Architecture

3-> Art

4-> Biology and medicine

5-> Chemistry and materials science

6-> Classical compositions

7-> Computing and engineering

8-> Earth science

9-> Film

10-> Geography

11-> Language and literature

12-> Mathematics and mathematicians

13-> Media and drama

14-> Other music articles

15-> Philosophy

16-> Physics and astronomy

17-> Places

18-> Religion

19-> Royalty, nobility, and heraldry

20-> Songs

21-> Television

22-> Transport

23-> World history

24->Armies and military units

25->Baseball

26->Basketball

27->Battles, exercises, and conflicts

28->Culture, sociology, and psychology

29->Economics and business

30->Education

31->Football

32->Hockey

33->Law

34->Magazines and print journalism

35->Military aircraft

36->Military decorations and memorials

37->Military people

38->Motorsport

39->Multi-sport event

40->Other sports

41->Politics and government

42->Pro wrestling

43->Recreation

44->Video games

45->Warships and naval units

46->Weapons, equipment, and buildings
TAGS
#transformers #pytorch #bert #text-classification #news classification #vi #dataset-wikimulti #autotrain_compatible #endpoints_compatible #region-us 
# BERT-base for news genre classification

This is a fine-tuned version of NlpHUST/vibert4news-base-cased model for news genre classification. The training data is 3864 vietnamese news summaries in WikiMulti dataset.

<b>Labels</b>: 

0-> Agriculture, food, and drink

1-> Albums

2-> Architecture

3-> Art

4-> Biology and medicine

5-> Chemistry and materials science

6-> Classical compositions

7-> Computing and engineering

8-> Earth science

9-> Film

10-> Geography

11-> Language and literature

12-> Mathematics and mathematicians

13-> Media and drama

14-> Other music articles

15-> Philosophy

16-> Physics and astronomy

17-> Places

18-> Religion

19-> Royalty, nobility, and heraldry

20-> Songs

21-> Television

22-> Transport

23-> World history

24->Armies and military units

25->Baseball

26->Basketball

27->Battles, exercises, and conflicts

28->Culture, sociology, and psychology

29->Economics and business

30->Education

31->Football

32->Hockey

33->Law

34->Magazines and print journalism

35->Military aircraft

36->Military decorations and memorials

37->Military people

38->Motorsport

39->Multi-sport event

40->Other sports

41->Politics and government

42->Pro wrestling

43->Recreation

44->Video games

45->Warships and naval units

46->Weapons, equipment, and buildings