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3068
[ "Division", "three" ]
[ 20, 10 ]
[ 5, 16 ]
[ 8, 8 ]
[ [ 9.15625, -1.9521484375, -0.2142333984375, -1.58203125, -0.1903076171875, -2.046875, 0.58837890625, -2.158203125, -0.52734375 ], [ 10.5390625, -0.269775390625, -2.16015625, -1.578125, -1.7373046875, -1.5341796875, -1.5712890625, -1.111328125, ...
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 ]
[ [ 10.1328125, -4.609375, -0.7041015625, -1.578125, 4.4375, -3.439453125, 0.2216796875, -3.83203125, -0.58544921875 ], [ 0.350830078125, -1.830078125, -3.982421875, 10.5859375, 0.8974609375, 0.62646484375, -3.76171875, -0.50634765625, -2.791...
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 ]
[ [ 7.68359375, -4.90625, -1.9638671875, -1.0322265625, 4.4296875, -4.0078125, -0.35107421875, -2.720703125, 3.533203125 ], [ 0.1610107421875, -1.3232421875, -4.83203125, 6.64453125, -0.70068359375, 0.19775390625, -4.37890625, 5.546875, -1.60...
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 ]
[[9.0234375,-2.279296875,-1.4267578125,-1.6259765625,-1.052734375,-1.4951171875,0.955078125,-2.28710(...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 ]
[[10.3125,-3.109375,-0.8037109375,-2.177734375,-0.1634521484375,-2.18359375,1.60546875,-2.63671875,-(...TRUNCATED)
3358
[ "SATURDAY", ",", "DECEMBER", "7", "SCHEDULE" ]
[ 21, 6, 20, 10, 21 ]
[ 5, 22, 5, 16, 16 ]
[ 8, 8, 8, 8, 8 ]
[[8.796875,-2.0859375,0.1329345703125,-1.9306640625,-0.18994140625,-1.9912109375,0.51708984375,-2.47(...TRUNCATED)
768
[ "against", ",", "points", ")", ":" ]
[ 14, 6, 41, 5, 8 ]
[ 6, 22, 10, 22, 22 ]
[ 8, 8, 8, 8, 8 ]
[[8.34375,-1.828125,0.3017578125,-1.5029296875,-0.1668701171875,-2.025390625,0.5107421875,-2.2578125(...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 ]
[[11.1640625,-2.0390625,-1.52734375,-1.8544921875,-1.564453125,-1.9697265625,0.06512451171875,-1.958(...TRUNCATED)
2522
[ "4.", "Italy", "887" ]
[ 10, 21, 10 ]
[ 5, 16, 16 ]
[ 8, 0, 8 ]
[[9.09375,-2.63671875,-1.5517578125,-1.6884765625,-0.880859375,-0.8359375,0.99853515625,-2.025390625(...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 ]
[[6.95703125,-0.99462890625,3.0859375,-2.150390625,-0.65771484375,-2.41796875,0.67333984375,-2.75,-0(...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: mariolinml/roberta_large-ner-conll2003_0818_v0
  • Dataset: conll2003
  • Config: conll2003
  • Split: test

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

Contributions

Thanks to @lewtun for evaluating this model.

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