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@@ -73,24 +73,23 @@ The following hyperparameters were used during training:
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  ### Training results
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- Step|Training Loss |Validation Loss| Precision|Recall F1| Accuracy
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- |:-------------:|:-------------:|:-------------:|:-------------:|:-------------:|
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- 250|No log| 0.435449 | 0.854588| 0.902136| 0.877719 |0.835968
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- 500|0.505800| 0.611310| 0.869822| 0.876304| 0.873051| 0.839177
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- 750| 0.505800| 0.635022| 0.879886| 0.917039| 0.898078| 0.853085
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- 1000| 0.097000| 0.765935| 0.900818| 0.929459| 0.914914| 0.860097
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- 1250| 0.097000| 0.887739| 0.885533| 0.903130| 0.894245| 0.842625
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- 1500| 0.029900| 0.948754| 0.898018| 0.923000| 0.910338| 0.843575
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- 1750| 0.029900| 1.102811| 0.900433| 0.929955| 0.914956| 0.840128
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- 2000| 0.009700| 1.039040| 0.901415| 0.917536| 0.909404| 0.852728
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- 2250| 0.009700| 1.044235| 0.904716| 0.924491| 0.914496| 0.849519
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- 2500| 0.002500| 1.013194| 0.913086| 0.918530| 0.915800| 0.849637
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- 2750| 0.002500| 1.017520| 0.908605| 0.928465| 0.918428| 0.854986
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- 3000| 0.000900| 1.029559| 0.914216| 0.926478| 0.920306| 0.859384
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- 3250| 0.000900| 1.038318| 0.918177| 0.930949| 0.924519| 0.859979
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- 3500| 0.000800| 1.045578| 0.914216| 0.926478| 0.920306| 0.858552
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- 3750| 0.000800| 1.040568| 0.913894| 0.927968| 0.920877| 0.858433
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- 4000| 0.000700| 1.041146| 0.913894| 0.927968| 0.920877| 0.858552
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  ### Framework versions
 
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  ### Training results
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+ Step TrainLoss Valid Loss Precision Recall F1 Accuracy
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+ 250 No log 0.435449 0.854588 0.902136 0.877719 0.835968
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+ 500 0.505800 0.611310 0.869822 0.876304 0.873051 0.839177
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+ 750 0.505800 0.635022 0.879886 0.917039 0.898078 0.853085
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+ 1000 0.097000 0.765935 0.900818 0.929459 0.914914 0.860097
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+ 1250 0.097000 0.887739 0.885533 0.903130 0.894245 0.842625
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+ 1500 0.029900 0.948754 0.898018 0.923000 0.910338 0.843575
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+ 1750 0.029900 1.102811 0.900433 0.929955 0.914956 0.840128
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+ 2000 0.009700 1.039040 0.901415 0.917536 0.909404 0.852728
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+ 2250 0.009700 1.044235 0.904716 0.924491 0.914496 0.849519
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+ 2500 0.002500 1.013194 0.913086 0.918530 0.915800 0.849637
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+ 2750 0.002500 1.017520 0.908605 0.928465 0.918428 0.854986
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+ 3000 0.000900 1.029559 0.914216 0.926478 0.920306 0.859384
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+ 3250 0.000900 1.038318 0.918177 0.930949 0.924519 0.859979
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+ 3500 0.000800 1.045578 0.914216 0.926478 0.920306 0.858552
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+ 3750 0.000800 1.040568 0.913894 0.927968 0.920877 0.858433
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+ 4000 0.000700 1.041146 0.913894 0.927968 0.920877 0.8585528552
 
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  ### Framework versions