 Training results  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.068         | 1.0   | 3914  | nan             | 0.6196    | 0.8604 | 0.7204 | 0.9568   | | 0.0767        | 2.0   | 7828  | nan             | 0.8270    | 0.8710 | 0.8484 | 0.9693   | | 0.0257        | 3.0   | 11742 | nan             | 0.7243    | 0.9005 | 0.8029 | 0.9639   | | 0.0193        | 4.0   | 15656 | nan             | 0.9010    | 0.8984 | 0.8997 | 0.9821   | | 0.0156        | 5.0   | 19570 | nan             | 0.7150    | 0.9121 | 0.8016 | 0.9641   | | 0.0165        | 6.0   | 23484 | nan             | 0.7640    | 0.8796 | 0.8177 | 0.9691   | | 0.0225        | 7.0   | 27398 | nan             | 0.8851    | 0.9098 | 0.8973 | 0.9803   | | 0.016         | 8.0   | 31312 | nan             | 0.9081    | 0.9015 | 0.9048 | 0.9792   | | 0.0078        | 9.0   | 35226 | nan             | 0.8941    | 0.8863 | 0.8902 | 0.9788   | | 0.0061        | 10.0  | 39140 | nan             | 0.9026    | 0.9002 | 0.9014 | 0.9804   | | 0.0057        | 11.0  | 43054 | nan             | 0.8793    | 0.9018 | 0.8904 | 0.9769   | | 0.0044        | 12.0  | 46968 | nan             | 0.8790    | 0.9033 | 0.8910 | 0.9785   | | 0.0043        | 13.0  | 50882 | nan             | 0.9122    | 0.9163 | 0.9142 | 0.9826   | | 0.0003        | 14.0  | 54796 | nan             | 0.9032    | 0.9070 | 0.9051 | 0.9807   | | 0.0025        | 15.0  | 58710 | nan             | 0.8903    | 0.9085 | 0.8993 | 0.9798   |   