 Training results  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| | 0.5792        | 0.04  | 500   | 0.5164          | 0.7290   | 0.6761 | | 0.5106        | 0.09  | 1000  | 0.4848          | 0.7490   | 0.7008 | | 0.4974        | 0.13  | 1500  | 0.4907          | 0.7414   | 0.7142 | | 0.4818        | 0.18  | 2000  | 0.4670          | 0.7555   | 0.7216 | | 0.4734        | 0.22  | 2500  | 0.4576          | 0.7624   | 0.7274 | | 0.4564        | 0.26  | 3000  | 0.4486          | 0.7675   | 0.7329 | | 0.4578        | 0.31  | 3500  | 0.4455          | 0.7688   | 0.7361 | | 0.451         | 0.35  | 4000  | 0.4490          | 0.7672   | 0.7383 | | 0.4511        | 0.4   | 4500  | 0.4401          | 0.7720   | 0.7426 | | 0.4419        | 0.44  | 5000  | 0.4201          | 0.7888   | 0.7491 | | 0.4308        | 0.48  | 5500  | 0.4266          | 0.7843   | 0.7507 | | 0.4308        | 0.53  | 6000  | 0.4077          | 0.8005   | 0.7566 | | 0.4249        | 0.57  | 6500  | 0.4182          | 0.7913   | 0.7558 | | 0.4256        | 0.62  | 7000  | 0.4051          | 0.8008   | 0.7582 | | 0.4179        | 0.66  | 7500  | 0.4064          | 0.8037   | 0.7630 | | 0.4314        | 0.7   | 8000  | 0.4105          | 0.7963   | 0.7607 | | 0.4202        | 0.75  | 8500  | 0.3970          | 0.8064   | 0.7656 | | 0.4152        | 0.79  | 9000  | 0.4204          | 0.7894   | 0.7615 | | 0.4121        | 0.84  | 9500  | 0.3908          | 0.8099   | 0.7667 | | 0.4135        | 0.88  | 10000 | 0.3863          | 0.8151   | 0.7707 | | 0.4091        | 0.92  | 10500 | 0.3839          | 0.8149   | 0.7702 | | 0.4084        | 0.97  | 11000 | 0.3837          | 0.8179   | 0.7719 | | 0.4068        | 1.01  | 11500 | 0.3990          | 0.8048   | 0.7712 | | 0.3861        | 1.06  | 12000 | 0.3821          | 0.8173   | 0.7743 | | 0.3955        | 1.1   | 12500 | 0.3868          | 0.8128   | 0.7756 |   