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3068
[ "Division", "three" ]
[ 20, 10 ]
[ 5, 16 ]
[ 8, 8 ]
[ [ 8.0859375, -1.51953125, -2.52734375, -1.0634765625, -1.3857421875, -0.69580078125, -1.9921875, -0.36669921875, -1.10546875 ], [ 8.9453125, -1.23046875, -2.943359375, -0.7666015625, -1.806640625, -0.9345703125, -2.306640625, -0.2491455078125, ...
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 ]
[ [ 9.7265625, -1.31640625, -2.494140625, -1.2197265625, -1.173828125, -1.4609375, -1.822265625, -1.3740234375, -1.99609375 ], [ -0.3212890625, 0.125244140625, -2.638671875, 9.015625, -0.2578125, -0.6787109375, -2.2890625, -1.1298828125, -2.6...
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 ]
[ [ 6.09375, -1.873046875, -1.9541015625, -0.113037109375, 0.1583251953125, -1.166015625, -1.8681640625, -1.31640625, -0.83935546875 ], [ -0.498291015625, -1.333984375, -3.18359375, 5.01953125, -2.63671875, 1.20703125, -3.169921875, 5.2734375, ...
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 ]
[[9.28125,-0.73046875,-2.2109375,-1.2421875,-1.8701171875,-1.28125,-2.1796875,-0.93701171875,-1.7138(...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 ]
[[9.234375,-1.404296875,-2.43359375,-1.1962890625,-1.1982421875,-1.3271484375,-1.8740234375,-1.51757(...TRUNCATED)
3358
[ "SATURDAY", ",", "DECEMBER", "7", "SCHEDULE" ]
[ 21, 6, 20, 10, 21 ]
[ 5, 22, 5, 16, 16 ]
[ 8, 8, 8, 8, 8 ]
[[8.0625,-0.96826171875,-1.673828125,-1.1796875,-0.7998046875,-1.216796875,-1.6796875,-1.5185546875,(...TRUNCATED)
768
[ "against", ",", "points", ")", ":" ]
[ 14, 6, 41, 5, 8 ]
[ 6, 22, 10, 22, 22 ]
[ 8, 8, 8, 8, 8 ]
[[8.5,-0.87109375,-2.396484375,-0.77294921875,-1.474609375,-0.7119140625,-2.283203125,-1.0859375,-1.(...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 ]
[[9.203125,-1.35546875,-2.556640625,-1.4609375,-1.4404296875,-1.4755859375,-1.87109375,-1.087890625,(...TRUNCATED)
2522
[ "4.", "Italy", "887" ]
[ 10, 21, 10 ]
[ 5, 16, 16 ]
[ 8, 0, 8 ]
[[9.4140625,-1.13671875,-2.427734375,-1.134765625,-1.6494140625,-1.4609375,-2.205078125,-0.952148437(...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 ]
[[9.71875,-1.0400390625,-1.9609375,-1.1201171875,-1.6044921875,-1.3466796875,-2.033203125,-1.5527343(...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: chandrasutrisnotjhong/bert-finetuned-ner
  • 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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