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PredictionOutput(predictions=(array([[ -1.838, -6.902, -8.28 , ..., -11.086, -11.086, -11.086],
[ -1.648, -7.723, -8.21 , ..., -11.266, -11.266, -11.266],
[ -1.85 , -5.914, -8.08 , ..., -11.5 , -11.5 , -11.5 ],
...,
[ -1.966, -6.51 , -8.234, ..., -11.16 , -11.16 , -11.16 ],
[ -1.468, -6.234, -6.203, ..., -11.25 , -11.25 , -11.25 ],
[ -1.754, -5.9 , -6.375, ..., -11.23 , -11.23 , -11.23 ]],
dtype=float16), array([[ -2.355, -9.36 , -10.234, ..., -12.19 , -12.19 , -12.19 ],
[ -2.098, -10.016, -10.29 , ..., -12.336, -12.336, -12.336],
[ -2.047, -9.016, -9.97 , ..., -12.38 , -12.38 , -12.38 ],
...,
[ -2.234, -9.15 , -10.12 , ..., -12.11 , -12.11 , -12.11 ],
[ -2.041, -8.586, -8.52 , ..., -12.15 , -12.15 , -12.15 ],
[ -2.43 , -8.45 , -7.73 , ..., -12.266, -12.266, -12.266]],
dtype=float16)), label_ids=(array([56, 40, 84, ..., 20, 16, 13]), array([56, 46, 88, ..., 19, 15, 12])), metrics={'test_loss': 0.8084036111831665, 'test_exact_match': 70.75102108860548, 'test_f1': 80.5972481285274, 'test_runtime': 342.9516, 'test_samples_per_second': 34.982, 'test_steps_per_second': 17.492})