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3068
[ "Division", "three" ]
[ 20, 10 ]
[ 5, 16 ]
[ 8, 8 ]
[ [ 8.78125, -0.87890625, -2.298828125, -0.75634765625, -1.2041015625, -0.71337890625, -2.234375, -1.03515625, -1.2529296875 ], [ 9.09375, -1.12890625, -2.216796875, -0.58837890625, -1.5810546875, -1.0830078125, -2.345703125, -0.7626953125, -...
2369
[ "Nippon", "Telegraph", "and", "Telephone", "Corp", "(", "NTT", ")", "said", "on", "Friday", "that", "it", "hopes", "to", "move", "into", "the", "international", "telecommunications", "business", "as", "soon", "as", "possible", "following", "the", "government", ...
[ 21, 21, 9, 21, 21, 4, 21, 5, 37, 14, 21, 14, 27, 41, 34, 36, 14, 11, 15, 23, 20, 29, 29, 14, 15, 20, 11, 20, 26, 20, 34, 36, 21, 14, 10, 23, 14, 11, 38, 20, 7 ]
[ 5, 16, 16, 16, 16, 22, 5, 22, 10, 6, 5, 8, 5, 10, 21, 21, 6, 5, 16, 16, 16, 1, 12, 6, 5, 16, 5, 16, 5, 16, 10, 21, 5, 6, 5, 16, 6, 5, 16, 16, 22 ]
[ 2, 6, 6, 6, 6, 8, 2, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 2, 8, 8, 8, 8, 8, 8, 8, 8 ]
[ [ 9.9140625, -0.67578125, -2.384765625, -1.1005859375, -1.0556640625, -1.4765625, -1.9296875, -1.1787109375, -1.6923828125 ], [ -1.021484375, -0.229248046875, -2.2578125, 8.5859375, -0.65185546875, -0.92138671875, -2.71484375, -0.181884765625, ...
1103
[ "Canadian", "West", "Coast", "Vessel", "Loadings", "-", "CWB", "." ]
[ 21, 21, 21, 21, 21, 8, 21, 7 ]
[ 5, 16, 16, 16, 16, 22, 5, 22 ]
[ 1, 8, 8, 8, 8, 8, 8, 8 ]
[ [ 6.66015625, -1.0302734375, -2.203125, -0.2408447265625, -0.1685791015625, -0.83642578125, -2.169921875, -0.39453125, -0.81494140625 ], [ -0.424072265625, -1.080078125, -2.787109375, 7.19921875, -1.5625, 0.175048828125, -3.05078125, 2.24804687...
2562
[ "30.", "Alessandra", "Merlin", "(", "Italy", ")", "1:51.16" ]
[ 21, 21, 21, 4, 21, 5, 10 ]
[ 5, 16, 16, 22, 5, 22, 5 ]
[ 8, 3, 7, 8, 0, 8, 8 ]
[[9.8515625,-0.041107177734375,-2.111328125,-1.1279296875,-1.708984375,-1.0927734375,-2.44140625,-1.(...TRUNCATED)
1883
[ "Hindu", "party", "forces", "India", "parliament", "to", "adjourn", "." ]
[ 21, 20, 41, 21, 20, 34, 36, 7 ]
[ 5, 16, 10, 5, 16, 10, 21, 22 ]
[ 1, 8, 8, 0, 8, 8, 8, 8 ]
[[9.2578125,-0.900390625,-2.30078125,-0.7734375,-1.1455078125,-1.228515625,-1.9609375,-0.96923828125(...TRUNCATED)
3358
[ "SATURDAY", ",", "DECEMBER", "7", "SCHEDULE" ]
[ 21, 6, 20, 10, 21 ]
[ 5, 22, 5, 16, 16 ]
[ 8, 8, 8, 8, 8 ]
[[8.0234375,-0.355224609375,-1.951171875,-0.59912109375,-1.1806640625,-0.7314453125,-2.369140625,-1.(...TRUNCATED)
768
[ "against", ",", "points", ")", ":" ]
[ 14, 6, 41, 5, 8 ]
[ 6, 22, 10, 22, 22 ]
[ 8, 8, 8, 8, 8 ]
[[8.671875,-0.681640625,-2.197265625,-0.87060546875,-1.1328125,-0.69873046875,-2.36328125,-1.2392578(...TRUNCATED)
952
[ "It", "has", "produced", "1.5", "million", "hectolitres", "." ]
[ 27, 41, 39, 10, 10, 23, 7 ]
[ 5, 10, 21, 5, 16, 16, 22 ]
[ 8, 8, 8, 8, 8, 8, 8 ]
[[9.4921875,-0.58740234375,-2.548828125,-1.09765625,-1.357421875,-1.029296875,-2.08203125,-0.7436523(...TRUNCATED)
2522
[ "4.", "Italy", "887" ]
[ 10, 21, 10 ]
[ 5, 16, 16 ]
[ 8, 0, 8 ]
[[9.234375,-0.1529541015625,-2.490234375,-0.82763671875,-1.8369140625,-0.66552734375,-2.662109375,-0(...TRUNCATED)
318
["Australia","-","Mark","Taylor","(","captain",")",",","Mark","Waugh",",","Ricky","Ponting",",","Gre(...TRUNCATED)
[21,8,21,21,4,20,5,6,21,21,6,21,21,6,21,21,6,21,21,6,21,21,6,21,21,6,21,21,6,21,21,6,21,21,6,21,21,6(...TRUNCATED)
[5,22,5,16,22,5,22,22,5,16,22,5,16,22,5,16,22,5,16,22,5,16,22,5,16,22,5,16,22,5,16,22,5,16,22,5,16,2(...TRUNCATED)
[ 0, 8, 3, 7, 8, 8, 8, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 3, 7, 8, 8, 8 ]
[[9.5,-0.03350830078125,-1.9580078125,-1.09765625,-1.2998046875,-1.1875,-2.205078125,-1.2578125,-1.9(...TRUNCATED)
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Dataset Card for AutoTrain Evaluator

This repository contains model predictions generated by AutoTrain for the following task and dataset:

  • Task: Token Classification
  • Model: AJGP/bert-finetuned-ner
  • Dataset: conll2003
  • Config: conll2003
  • Split: test

To run new evaluation jobs, visit Hugging Face's automatic model evaluator.

Contributions

Thanks to @hrezaeim for evaluating this model.

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