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3068
[ "Division", "three" ]
[ 20, 10 ]
[ 5, 16 ]
[ 8, 8 ]
[ [ 7.80859375, -1.83984375, -2.650390625, -0.400390625, -1.2412109375, -1.1396484375, -2.1796875, -0.1256103515625, -1.3662109375 ], [ 8.8046875, -2.171875, -2.72265625, -1.048828125, -1.646484375, -1.4560546875, -2.412109375, 0.38134765625, ...
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 ]
[ [ 7.50390625, -1.236328125, -1.970703125, -0.384521484375, -1.3291015625, -1.201171875, -2.21875, 0.0195770263671875, -1.748046875 ], [ -0.254638671875, -0.34521484375, -2.44921875, 8.515625, -0.25146484375, -0.53173828125, -2.03125, -0.6982421...
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 ]
[ [ 4.71484375, -1.07421875, -1.984375, 1.01171875, -0.440185546875, -0.63037109375, -2.025390625, -0.54052734375, -1.654296875 ], [ 0.97802734375, -0.9443359375, -2.6328125, 5.08203125, -2.34765625, 0.8564453125, -2.935546875, 5.5703125, -1....
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 ]
[[7.18359375,-0.0797119140625,-1.5498046875,-0.62353515625,-1.732421875,-1.5478515625,-1.9580078125,(...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 ]
[[7.2734375,-1.22265625,-2.07421875,-0.1773681640625,-1.3037109375,-1.103515625,-1.96484375,-0.19262(...TRUNCATED)
3358
[ "SATURDAY", ",", "DECEMBER", "7", "SCHEDULE" ]
[ 21, 6, 20, 10, 21 ]
[ 5, 22, 5, 16, 16 ]
[ 8, 8, 8, 8, 8 ]
[[7.25,-1.076171875,-2.36328125,-0.1944580078125,-1.5,-1.3623046875,-2.2890625,-0.2298583984375,-1.4(...TRUNCATED)
768
[ "against", ",", "points", ")", ":" ]
[ 14, 6, 41, 5, 8 ]
[ 6, 22, 10, 22, 22 ]
[ 8, 8, 8, 8, 8 ]
[[7.9765625,-1.3720703125,-2.056640625,-0.40234375,-1.5107421875,-1.064453125,-2.04296875,-0.4130859(...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 ]
[[6.40234375,-0.98486328125,-2.083984375,-0.1763916015625,-1.2333984375,-0.9765625,-2.138671875,0.25(...TRUNCATED)
2522
[ "4.", "Italy", "887" ]
[ 10, 21, 10 ]
[ 5, 16, 16 ]
[ 8, 0, 8 ]
[[6.9609375,-0.818359375,-1.8837890625,-0.22607421875,-1.1708984375,-1.212890625,-2.04296875,-0.3347(...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 ]
[[8.6953125,-0.7783203125,-1.2685546875,-1.0400390625,-1.611328125,-1.4013671875,-2.1953125,-0.92285(...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: kamalkraj/bert-base-cased-ner-conll2003
  • Dataset: conll2003
  • Config: conll2003
  • Split: test

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

Contributions

Thanks to @akdeniz27 for evaluating this model.

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