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3068
[ "Division", "three" ]
[ 20, 10 ]
[ 5, 16 ]
[ 8, 8 ]
[ [ 9.96875, -2.439453125, -1.947265625, -1.955078125, 0.56005859375, -1.7236328125, -0.6943359375, -2.62109375, -1.2646484375 ], [ 10.9921875, -1.3857421875, -2.65625, -1.3671875, -0.59765625, -0.552734375, -1.9189453125, -1.4248046875, -1.2...
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 ]
[ [ 10.5859375, -2.5859375, -1.4833984375, -2.478515625, 1.375, -2.43359375, -0.45458984375, -3.4765625, -1.162109375 ], [ 1.185546875, 0.323486328125, -3.296875, 10.4765625, 0.388427734375, 0.0284576416015625, -3.482421875, -0.416748046875, ...
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 ]
[ [ 9.5390625, -2.828125, -1.9921875, -1.45703125, 2.171875, -2.134765625, -1.22265625, -2.828125, -1.0927734375 ], [ 0.375732421875, -0.1456298828125, -3.55859375, 9.5625, -0.18701171875, 0.27783203125, -3.27734375, 2.07421875, -2.2578125 ...
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 ]
[[10.0,-2.216796875,-1.107421875,-2.5234375,0.1431884765625,-1.9052734375,-0.708984375,-3.12890625,-(...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 ]
[[10.703125,-2.359375,-1.21875,-2.5546875,0.362548828125,-2.462890625,-0.319580078125,-3.279296875,-(...TRUNCATED)
3358
[ "SATURDAY", ",", "DECEMBER", "7", "SCHEDULE" ]
[ 21, 6, 20, 10, 21 ]
[ 5, 22, 5, 16, 16 ]
[ 8, 8, 8, 8, 8 ]
[[9.8515625,-2.37109375,-1.1875,-2.63671875,0.3759765625,-1.990234375,-0.2301025390625,-3.2578125,-1(...TRUNCATED)
768
[ "against", ",", "points", ")", ":" ]
[ 14, 6, 41, 5, 8 ]
[ 6, 22, 10, 22, 22 ]
[ 8, 8, 8, 8, 8 ]
[[11.5390625,-2.712890625,-1.1220703125,-3.06640625,-0.060089111328125,-2.505859375,-0.3447265625,-3(...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 ]
[[10.9921875,-2.7890625,-1.34765625,-2.767578125,0.488525390625,-2.53125,-0.4287109375,-3.271484375,(...TRUNCATED)
2522
[ "4.", "Italy", "887" ]
[ 10, 21, 10 ]
[ 5, 16, 16 ]
[ 8, 0, 8 ]
[[9.5,-2.50390625,-1.28125,-2.498046875,0.04736328125,-1.962890625,-0.376220703125,-3.015625,-1.0029(...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 ]
[[11.234375,-2.220703125,-1.4091796875,-2.619140625,-0.09759521484375,-2.2578125,-0.60498046875,-3.0(...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: baptiste/deberta-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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