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results/output/output.txt

@@ -1,28 +1,28 @@
-PredictionOutput(predictions=(array([[-6.7850056, -6.6716676, -5.9739347, ..., -8.579165 , -8.429346 ,
-        -7.1613026],
-       [-0.9918271, -4.367369 , -2.8474648, ..., -8.603483 , -8.417028 ,
-        -7.091916 ],
-       [-6.647778 , -6.672091 , -5.5766373, ..., -8.415629 , -8.537864 ,
-        -7.1834354],
+PredictionOutput(predictions=(array([[-5.6569166, -5.6026487, -5.2293024, ..., -7.714299 , -7.75922  ,
+        -7.050535 ],
+       [-4.10028  , -4.4362736, -1.4430411, ..., -7.6566777, -7.706584 ,
+        -6.8068657],
+       [-5.254589 , -5.085027 , -3.8519912, ..., -8.0982   , -7.74445  ,
+        -6.976511 ],
        ...,
-       [-5.211953 , -4.759074 , -3.9656222, ..., -8.151437 , -8.133892 ,
-        -6.8031187],
-       [-1.1324221, -3.3401337, -3.1341577, ..., -8.7514305, -8.140931 ,
-        -6.6388187],
-       [-2.0237327, -3.7011008, -4.0905695, ..., -7.7945566, -7.9525757,
-        -6.6917944]], dtype=float32), array([[-6.4557104 , -6.905714  , -7.5514183 , ..., -8.536643  ,
-        -8.706019  , -6.208824  ],
-       [-0.7032113 , -5.1519594 , -6.3273916 , ..., -8.339505  ,
-        -8.613202  , -5.752983  ],
-       [-5.72209   , -6.6753    , -7.6972995 , ..., -8.692042  ,
-        -8.544511  , -6.0626097 ],
+       [-4.8420677, -5.324687 , -4.6671324, ..., -7.9530993, -7.740043 ,
+        -7.265579 ],
+       [-1.7128483, -3.617846 , -2.9173126, ..., -8.322919 , -8.003241 ,
+        -6.6888323],
+       [-2.9863038, -4.3009934, -3.5254717, ..., -7.8710504, -7.8219476,
+        -6.7088118]], dtype=float32), array([[-4.985059  , -5.62015   , -6.585838  , ..., -8.056629  ,
+        -8.126738  , -5.9038467 ],
+       [-3.0638905 , -4.8499866 , -5.270744  , ..., -7.938978  ,
+        -8.022577  , -5.7312593 ],
+       [-5.1996045 , -5.930199  , -6.8457756 , ..., -8.02756   ,
+        -7.974593  , -6.0084224 ],
        ...,
-       [-4.4161844 , -6.122534  , -5.853463  , ..., -8.402682  ,
-        -8.602763  , -5.911165  ],
-       [ 0.14999449, -3.6059844 , -2.598619  , ..., -6.4443893 ,
-        -7.9721546 , -5.3265104 ],
-       [-0.6376608 , -4.0579967 , -3.6932316 , ..., -7.6001587 ,
-        -7.661689  , -5.450534  ]], dtype=float32)), label_ids=(array([ 41,   8,  10,   8,  39,   6,  59,   9,  14,  15,  73,   8,  51,
+       [-3.8334773 , -6.1602497 , -6.5691676 , ..., -7.966215  ,
+        -8.136274  , -5.7270074 ],
+       [-0.22586474, -3.4899747 , -2.4272456 , ..., -6.4262285 ,
+        -7.6043906 , -5.4305654 ],
+       [-1.3159301 , -4.3984494 , -3.9507654 , ..., -7.715788  ,
+        -7.7165637 , -5.4757805 ]], dtype=float32)), label_ids=(array([ 41,   8,  10,   8,  39,   6,  59,   9,  14,  15,  73,   8,  51,
          7,  10,  10,  17,  10,  76,  16,  94,  11,   6,   9,  22,   7,
          7,   8,  25,  10,  27,  14,  11,  12,  11,  16,   8,  71,  10,
        102,  10,  66,  10,  50,   7,  32,   9,  10,   7,  12,   8, 179,
@@ -152,4 +152,4 @@ PredictionOutput(predictions=(array([[-6.7850056, -6.6716676, -5.9739347, ..., -
          8,  32,  10,  12,  20,  15,  14,  18,  15,  14,  14,  19,   9,
         48,   8,   9,   8,  55,  12, 120,  17,  29,   9,  54,  11,  78,
         29, 116,  28,   6,   8,  48,   9,  33,   7, 206,  79,   8, 124,
-        12,  46,  16])), metrics={'test_loss': 1.0334758758544922, 'test_exact_match': 67.09905660377359, 'test_f1': 72.63956856431777, 'test_runtime': 44.1265, 'test_samples_per_second': 19.217, 'test_steps_per_second': 2.402})
+        12,  46,  16])), metrics={'test_loss': 1.0607749223709106, 'test_exact_match': 65.80188679245283, 'test_f1': 72.46319500072799, 'test_runtime': 42.8941, 'test_samples_per_second': 19.77, 'test_steps_per_second': 2.471})