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3068
[ "Division", "three" ]
[ 20, 10 ]
[ 5, 16 ]
[ 8, 8 ]
[ [ 6.671875, 0.05902099609375, -0.92333984375, -0.9833984375, -0.8876953125, -0.748046875, -0.37646484375, -1.2392578125, 0.024383544921875 ], [ 10.4375, 0.1636962890625, -0.4736328125, -1.494140625, -2.64453125, -0.716796875, -0.83544921875, -0...
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 ]
[ [ 8.2109375, -0.74169921875, -1.83203125, -1.4111328125, -1.3056640625, -0.3984375, 0.2034912109375, -1.7392578125, 0.1314697265625 ], [ 0.0465087890625, -0.377685546875, -2.390625, -0.81298828125, -2.7265625, 9.1796875, -0.92919921875, -0.5083...
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 ]
[ [ 4.23046875, 0.064208984375, -0.162109375, -1.6201171875, -1.6630859375, 0.7177734375, 0.58056640625, -1.97265625, -0.80908203125 ], [ 0.53955078125, 5.05859375, -2.5234375, -1.2734375, -3.046875, 4.671875, -3.013671875, 1.73828125, -2.783...
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 ]
[[6.88671875,-0.998046875,-2.2578125,0.1685791015625,0.71240234375,-0.9560546875,-1.068359375,-1.380(...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 ]
[[7.62890625,-0.0034122467041015625,-1.2841796875,-1.3515625,-0.89306640625,-0.79248046875,-0.770019(...TRUNCATED)
3358
[ "SATURDAY", ",", "DECEMBER", "7", "SCHEDULE" ]
[ 21, 6, 20, 10, 21 ]
[ 5, 22, 5, 16, 16 ]
[ 8, 8, 8, 8, 8 ]
[[7.046875,0.0232391357421875,-1.1884765625,-1.478515625,-0.62060546875,-0.54736328125,-0.7387695312(...TRUNCATED)
768
[ "against", ",", "points", ")", ":" ]
[ 14, 6, 41, 5, 8 ]
[ 6, 22, 10, 22, 22 ]
[ 8, 8, 8, 8, 8 ]
[[7.63671875,-0.50439453125,-0.7626953125,-1.2802734375,-0.6279296875,-0.469970703125,-0.640625,-1.4(...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 ]
[[8.1640625,-0.014312744140625,-1.3173828125,-1.2578125,-1.033203125,-0.4775390625,-0.50390625,-1.47(...TRUNCATED)
2522
[ "4.", "Italy", "887" ]
[ 10, 21, 10 ]
[ 5, 16, 16 ]
[ 8, 0, 8 ]
[[6.83984375,-0.4609375,-1.58984375,-1.3603515625,-0.7529296875,-0.513671875,-0.161865234375,-1.4462(...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 ]
[[3.84375,-1.693359375,-2.189453125,1.306640625,2.740234375,-0.64404296875,-1.337890625,-1.47265625,(...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: 51la5/bert-large-NER
  • Dataset: conll2003
  • Config: conll2003
  • Split: test

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

Contributions

Thanks to @aniketrawat97 for evaluating this model.

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