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suicide-bert
vishalp23/suicide-bert
suicide-bert is a text classification model from vishalp23. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Dec 16, 2023
- Updated
- Sep 21, 2024
- SHA
- 3254cfce
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
model
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1120
- Accuracy: {'accuracy': 0.958625}
- F1: {'f1': 0.9585161047750345}
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 1280
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss |
|---|---|---|---|---|---|
| 0.6659 | 0.0 | 5 | {'accuracy': 0.7308125} | {'f1': 0.67054233917234} | 0.6003 |
| 0.5966 | 0.01 | 10 | {'accuracy': 0.795625} | {'f1': 0.8145838058516671} | 0.5072 |
| 0.4979 | 0.01 | 15 | {'accuracy': 0.8160625} | {'f1': 0.8247275326067537} | 0.4284 |
| 0.4219 | 0.02 | 20 | {'accuracy': 0.83075} | {'f1': 0.8330867850098618} | 0.3879 |
| 0.4539 | 0.02 | 25 | {'accuracy': 0.8180625} | {'f1': 0.8345176510715707} | 0.4414 |
| 0.3638 | 0.02 | 30 | {'accuracy': 0.844875} | {'f1': 0.8441542132362175} | 0.3567 |
| 0.3815 | 0.03 | 35 | {'accuracy': 0.85125} | {'f1': 0.8450117218025527} | 0.3476 |
| 0.357 | 0.03 | 40 | {'accuracy': 0.8601875} | {'f1': 0.8622960911049553} | 0.3268 |
| 0.3333 | 0.04 | 45 | {'accuracy': 0.8561875} | {'f1': 0.8624544204674517} | 0.3487 |
| 0.3411 | 0.04 | 50 | {'accuracy': 0.8599375} | {'f1': 0.8656394268241501} | 0.3357 |
| 0.327 | 0.04 | 55 | {'accuracy': 0.8639375} | {'f1': 0.8681165566123463} | 0.3156 |
| 0.3271 | 0.05 | 60 | {'accuracy': 0.8645625} | {'f1': 0.861471584734386} | 0.3182 |
| 0.3241 | 0.05 | 65 | {'accuracy': 0.8660625} | {'f1': 0.8615006786014346} | 0.3150 |
| 0.3077 | 0.06 | 70 | {'accuracy': 0.8654375} | {'f1': 0.8694122642081639} | 0.3127 |
| 0.3273 | 0.06 | 75 | {'accuracy': 0.864625} | {'f1': 0.8695023496806844} | 0.3131 |
| 0.3139 | 0.06 | 80 | {'accuracy': 0.86875} | {'f1': 0.8711340206185567} | 0.3190 |
| 0.3246 | 0.07 | 85 | {'accuracy': 0.86925} | {'f1': 0.8722052535125229} | 0.3094 |
| 0.3045 | 0.07 | 90 | {'accuracy': 0.86975} | {'f1': 0.872491434165443} | 0.3061 |
| 0.3576 | 0.08 | 95 | {'accuracy': 0.8689375} | {'f1': 0.8639636717482971} | 0.3151 |
| 0.3114 | 0.08 | 100 | {'accuracy': 0.871625} | {'f1': 0.8690885914595283} | 0.3144 |
| 0.3067 | 0.08 | 105 | {'accuracy': 0.8745} | {'f1': 0.8743743743743743} | 0.2997 |
| 0.3591 | 0.09 | 110 | {'accuracy': 0.87375} | {'f1': 0.8728760226557583} | 0.2996 |
| 0.3465 | 0.09 | 115 | {'accuracy': 0.855875} | {'f1': 0.8430865541643985} | 0.3411 |
| 0.3377 | 0.1 | 120 | {'accuracy': 0.8741875} | {'f1': 0.8719547102601616} | 0.2971 |
| 0.3248 | 0.1 | 125 | {'accuracy': 0.8771875} | {'f1': 0.8765005342216077} | 0.3003 |
| 0.3209 | 0.11 | 130 | {'accuracy': 0.8794375} | {'f1': 0.8771728748806114} | 0.2900 |
| 0.3129 | 0.11 | 135 | {'accuracy': 0.8749375} | {'f1': 0.8713431492316596} | 0.3018 |
| 0.2986 | 0.11 | 140 | {'accuracy': 0.8784375} | {'f1': 0.878657433401959} | 0.2876 |
| 0.3027 | 0.12 | 145 | {'accuracy': 0.8795} | {'f1': 0.879920279023418} | 0.2911 |
| 0.3193 | 0.12 | 150 | {'accuracy': 0.8776875} | {'f1': 0.8753264955086958} | 0.2925 |
| 0.3231 | 0.13 | 155 | {'accuracy': 0.8770625} | {'f1': 0.874176421672104} | 0.2865 |
| 0.3213 | 0.13 | 160 | {'accuracy': 0.8764375} | {'f1': 0.8721794788905413} | 0.3075 |
| 0.3125 | 0.13 | 165 | {'accuracy': 0.8759375} | {'f1': 0.8709446719979196} | 0.2953 |
| 0.3118 | 0.14 | 170 | {'accuracy': 0.8745625} | {'f1': 0.869208211143695} | 0.2963 |
| 0.3167 | 0.14 | 175 | {'accuracy': 0.8830625} | {'f1': 0.8847551586079458} | 0.2897 |
| 0.3307 | 0.15 | 180 | {'accuracy': 0.878375} | {'f1': 0.8825304841241096} | 0.2940 |
| 0.2777 | 0.15 | 185 | {'accuracy': 0.8809375} | {'f1': 0.8832076512782784} | 0.2924 |
| 0.3242 | 0.15 | 190 | {'accuracy': 0.878875} | {'f1': 0.8798512089274643} | 0.2871 |
| 0.3225 | 0.16 | 195 | {'accuracy': 0.8790625} | {'f1': 0.8799851144327979} | 0.3024 |
| 0.307 | 0.16 | 200 | {'accuracy': 0.8799375} | {'f1': 0.8786558019076496} | 0.2849 |
| 0.2912 | 0.17 | 205 | {'accuracy': 0.8778125} | {'f1': 0.8762893121559197} | 0.2923 |
| 0.3066 | 0.17 | 210 | {'accuracy': 0.8789375} | {'f1': 0.8825989453906297} | 0.2947 |
| 0.328 | 0.17 | 215 | {'accuracy': 0.877625} | {'f1': 0.8810015801628784} | 0.2883 |
| 0.3049 | 0.18 | 220 | {'accuracy': 0.880375} | {'f1': 0.8813244047619048} | 0.2880 |
| 0.3119 | 0.18 | 225 | {'accuracy': 0.8811875} | {'f1': 0.881269127474861} | 0.2794 |
| 0.2887 | 0.19 | 230 | {'accuracy': 0.8799375} | {'f1': 0.8828158360275729} | 0.2902 |
| 0.2952 | 0.19 | 235 | {'accuracy': 0.8789375} | {'f1': 0.8788390567335961} | 0.2837 |
| 0.3062 | 0.19 | 240 | {'accuracy': 0.881375} | {'f1': 0.8833435771358329} | 0.2812 |
| 0.3038 | 0.2 | 245 | {'accuracy': 0.88225} | {'f1': 0.8831700359667617} | 0.2795 |
| 0.299 | 0.2 | 250 | {'accuracy': 0.8786875} | {'f1': 0.8812335556507372} | 0.2982 |
| 0.3154 | 0.21 | 255 | {'accuracy': 0.8815625} | {'f1': 0.8824222870261215} | 0.2799 |
| 0.2816 | 0.21 | 260 | {'accuracy': 0.884125} | {'f1': 0.884557907845579} | 0.2991 |
| 0.2943 | 0.21 | 265 | {'accuracy': 0.8835625} | {'f1': 0.8823492263972214} | 0.2780 |
| 0.3108 | 0.22 | 270 | {'accuracy': 0.8815} | {'f1': 0.883623864473361} | 0.2938 |
| 0.3061 | 0.22 | 275 | {'accuracy': 0.878625} | {'f1': 0.8827436299963773} | 0.2874 |
| 0.2806 | 0.23 | 280 | {'accuracy': 0.8823125} | {'f1': 0.8805581985410719} | 0.2807 |
| 0.2952 | 0.23 | 285 | {'accuracy': 0.8776875} | {'f1': 0.8730457346740188} | 0.2867 |
| 0.2857 | 0.23 | 290 | {'accuracy': 0.8825} | {'f1': 0.8843219296086636} | 0.2814 |
| 0.2888 | 0.24 | 295 | {'accuracy': 0.874875} | {'f1': 0.8817763080193693} | 0.2987 |
| 0.3296 | 0.24 | 300 | {'accuracy': 0.884875} | {'f1': 0.8869244935543277} | 0.2775 |
| 0.2984 | 0.25 | 305 | {'accuracy': 0.8835} | {'f1': 0.8817408958254028} | 0.2772 |
| 0.3105 | 0.25 | 310 | {'accuracy': 0.8818125} | {'f1': 0.879392818419542} | 0.2759 |
| 0.2772 | 0.25 | 315 | {'accuracy': 0.8815} | {'f1': 0.87964961279675} | 0.2830 |
| 0.2942 | 0.26 | 320 | {'accuracy': 0.88425} | {'f1': 0.8841196345889125} | 0.2738 |
| 0.3287 | 0.26 | 325 | {'accuracy': 0.8830625} | {'f1': 0.8811686249603048} | 0.2826 |
| 0.3223 | 0.27 | 330 | {'accuracy': 0.886875} | {'f1': 0.886875} | 0.2720 |
| 0.2953 | 0.27 | 335 | {'accuracy': 0.88425} | {'f1': 0.8867139711279667} | 0.2814 |
| 0.2898 | 0.27 | 340 | {'accuracy': 0.88175} | {'f1': 0.8863254025474645} | 0.2827 |
| 0.2863 | 0.28 | 345 | {'accuracy': 0.8808125} | {'f1': 0.8842348084744733} | 0.2833 |
| 0.3093 | 0.28 | 350 | {'accuracy': 0.885375} | {'f1': 0.8845378997733568} | 0.2788 |
| 0.3161 | 0.29 | 355 | {'accuracy': 0.8855625} | {'f1': 0.8850668507940493} | 0.2706 |
| 0.2902 | 0.29 | 360 | {'accuracy': 0.8875} | {'f1': 0.8862487360970678} | 0.2784 |
| 0.3136 | 0.29 | 365 | {'accuracy': 0.8856875} | {'f1': 0.8891313572164636} | 0.2760 |
| 0.2949 | 0.3 | 370 | {'accuracy': 0.8861875} | {'f1': 0.8886306647911443} | 0.2762 |
| 0.3019 | 0.3 | 375 | {'accuracy': 0.8838125} | {'f1': 0.8867499238501371} | 0.2839 |
| 0.295 | 0.31 | 380 | {'accuracy': 0.888125} | {'f1': 0.89004914004914} | 0.2690 |
| 0.2989 | 0.31 | 385 | {'accuracy': 0.8865} | {'f1': 0.8865992256775321} | 0.2697 |
| 0.2558 | 0.32 | 390 | {'accuracy': 0.886125} | {'f1': 0.8840819442677186} | 0.2802 |
| 0.2901 | 0.32 | 395 | {'accuracy': 0.88525} | {'f1': 0.8833396873808615} | 0.2743 |
| 0.2923 | 0.32 | 400 | {'accuracy': 0.887} | {'f1': 0.8855406432008103} | 0.2811 |
| 0.2834 | 0.33 | 405 | {'accuracy': 0.885375} | {'f1': 0.8824810970139689} | 0.2713 |
| 0.3008 | 0.33 | 410 | {'accuracy': 0.8875} | {'f1': 0.8881848676854267} | 0.2707 |
| 0.2724 | 0.34 | 415 | {'accuracy': 0.885875} | {'f1': 0.8856606136505948} | 0.2767 |
| 0.2631 | 0.34 | 420 | {'accuracy': 0.8855625} | {'f1': 0.8843116193845959} | 0.2745 |
| 0.2952 | 0.34 | 425 | {'accuracy': 0.8863125} | {'f1': 0.8868147595046979} | 0.2739 |
| 0.3061 | 0.35 | 430 | {'accuracy': 0.8849375} | {'f1': 0.8889693022133768} | 0.2742 |
| 0.2853 | 0.35 | 435 | {'accuracy': 0.8870625} | {'f1': 0.8889571683156148} | 0.2746 |
| 0.3031 | 0.36 | 440 | {'accuracy': 0.88875} | {'f1': 0.8888194878201124} | 0.2669 |
| 0.2877 | 0.36 | 445 | {'accuracy': 0.88825} | {'f1': 0.888012025554303} | 0.2712 |
| 0.2949 | 0.36 | 450 | {'accuracy': 0.8876875} | {'f1': 0.886945580371186} | 0.2688 |
| 0.2869 | 0.37 | 455 | {'accuracy': 0.88175} | {'f1': 0.8785466683784825} | 0.2736 |
| 0.2878 | 0.37 | 460 | {'accuracy': 0.8854375} | {'f1': 0.8828529430561769} | 0.2733 |
| 0.3179 | 0.38 | 465 | {'accuracy': 0.8856875} | {'f1': 0.8833620304827497} | 0.2698 |
| 0.3093 | 0.38 | 470 | {'accuracy': 0.8849375} | {'f1': 0.887338596169145} | 0.2767 |
| 0.3056 | 0.38 | 475 | {'accuracy': 0.8854375} | {'f1': 0.8889158232834374} | 0.2741 |
| 0.2886 | 0.39 | 480 | {'accuracy': 0.889625} | {'f1': 0.8908798813643104} | 0.2789 |
| 0.2909 | 0.39 | 485 | {'accuracy': 0.8895} | {'f1': 0.8890840652446675} | 0.2669 |
| 0.322 | 0.4 | 490 | {'accuracy': 0.8858125} | {'f1': 0.8832960715426381} | 0.2796 |
| 0.2886 | 0.4 | 495 | {'accuracy': 0.888875} | {'f1': 0.8881198087087844} | 0.2671 |
| 0.3097 | 0.4 | 500 | {'accuracy': 0.8895625} | {'f1': 0.8891537544696066} | 0.2705 |
| 0.2827 | 0.41 | 505 | {'accuracy': 0.886625} | {'f1': 0.8888616591104032} | 0.2736 |
| 0.2869 | 0.41 | 510 | {'accuracy': 0.88875} | {'f1': 0.8910915320606951} | 0.2729 |
| 0.2738 | 0.42 | 515 | {'accuracy': 0.8895} | {'f1': 0.8922476840565577} | 0.2734 |
| 0.2761 | 0.42 | 520 | {'accuracy': 0.8885625} | {'f1': 0.8910745922169956} | 0.2806 |
| 0.2799 | 0.42 | 525 | {'accuracy': 0.887125} | {'f1': 0.8902394554515619} | 0.2737 |
| 0.2715 | 0.43 | 530 | {'accuracy': 0.887375} | {'f1': 0.8908275778504786} | 0.2832 |
| 0.2916 | 0.43 | 535 | {'accuracy': 0.8883125} | {'f1': 0.8874330708661419} | 0.2678 |
| 0.3006 | 0.44 | 540 | {'accuracy': 0.8865625} | {'f1': 0.8856548856548856} | 0.2805 |
| 0.3071 | 0.44 | 545 | {'accuracy': 0.8886875} | {'f1': 0.8871141535146099} | 0.2661 |
| 0.2785 | 0.44 | 550 | {'accuracy': 0.8895625} | {'f1': 0.8904865199876045} | 0.2718 |
| 0.2876 | 0.45 | 555 | {'accuracy': 0.890125} | {'f1': 0.8912935938659411} | 0.2697 |
| 0.2713 | 0.45 | 560 | {'accuracy': 0.8879375} | {'f1': 0.8907573265094741} | 0.2729 |
| 0.268 | 0.46 | 565 | {'accuracy': 0.8875} | {'f1': 0.889651790093183} | 0.2716 |
| 0.2672 | 0.46 | 570 | {'accuracy': 0.884625} | {'f1': 0.8837385061090818} | 0.2699 |
| 0.2863 | 0.46 | 575 | {'accuracy': 0.8838125} | {'f1': 0.8803501319431035} | 0.2787 |
| 0.2882 | 0.47 | 580 | {'accuracy': 0.889125} | {'f1': 0.8897588864031818} | 0.2730 |
| 0.296 | 0.47 | 585 | {'accuracy': 0.887625} | {'f1': 0.8862745098039215} | 0.2688 |
| 0.2941 | 0.48 | 590 | {'accuracy': 0.8888125} | {'f1': 0.889303714765727} | 0.2733 |
| 0.2811 | 0.48 | 595 | {'accuracy': 0.8895625} | {'f1': 0.8909595803764271} | 0.2712 |
| 0.2843 | 0.48 | 600 | {'accuracy': 0.88675} | {'f1': 0.8838163631700436} | 0.2829 |
| 0.2878 | 0.49 | 605 | {'accuracy': 0.8881875} | {'f1': 0.88924657958274} | 0.2681 |
| 0.2885 | 0.49 | 610 | {'accuracy': 0.8854375} | {'f1': 0.8897973907292731} | 0.2845 |
| 0.2929 | 0.5 | 615 | {'accuracy': 0.8864375} | {'f1': 0.8887119495314509} | 0.2728 |
| 0.2822 | 0.5 | 620 | {'accuracy': 0.88825} | {'f1': 0.887433895744145} | 0.2707 |
| 0.2869 | 0.51 | 625 | {'accuracy': 0.8871875} | {'f1': 0.8850245238550226} | 0.2704 |
| 0.3071 | 0.51 | 630 | {'accuracy': 0.8851875} | {'f1': 0.8883757671507564} | 0.2815 |
| 0.2655 | 0.51 | 635 | {'accuracy': 0.887875} | {'f1': 0.8896814659943426} | 0.2701 |
| 0.2833 | 0.52 | 640 | {'accuracy': 0.88925} | {'f1': 0.8893468215311602} | 0.2672 |
| 0.279 | 0.52 | 645 | {'accuracy': 0.8900625} | {'f1': 0.8901380301043033} | 0.2638 |
| 0.2966 | 0.53 | 650 | {'accuracy': 0.8893125} | {'f1': 0.8885252092906151} | 0.2644 |
| 0.2683 | 0.53 | 655 | {'accuracy': 0.8888125} | {'f1': 0.8904084272777675} | 0.2770 |
| 0.299 | 0.53 | 660 | {'accuracy': 0.887875} | {'f1': 0.8888062476757159} | 0.2661 |
| 0.2592 | 0.54 | 665 | {'accuracy': 0.8898125} | {'f1': 0.8908156313866354} | 0.2766 |
| 0.3133 | 0.54 | 670 | {'accuracy': 0.88725} | {'f1': 0.8887518500246671} | 0.2667 |
| 0.3205 | 0.55 | 675 | {'accuracy': 0.8895625} | {'f1': 0.8912146770916702} | 0.2786 |
| 0.2799 | 0.55 | 680 | {'accuracy': 0.88825} | {'f1': 0.8873061893356865} | 0.2675 |
| 0.2677 | 0.55 | 685 | {'accuracy': 0.88975} | {'f1': 0.8892098982539882} | 0.2775 |
| 0.258 | 0.56 | 690 | {'accuracy': 0.8906875} | {'f1': 0.8913192071086808} | 0.2649 |
| 0.2746 | 0.56 | 695 | {'accuracy': 0.8896875} | {'f1': 0.89093493171847} | 0.2729 |
| 0.2525 | 0.57 | 700 | {'accuracy': 0.88775} | {'f1': 0.8904878048780488} | 0.2693 |
| 0.274 | 0.57 | 705 | {'accuracy': 0.88425} | {'f1': 0.8840616001001628} | 0.2703 |
| 0.2831 | 0.57 | 710 | {'accuracy': 0.8889375} | {'f1': 0.8912284997245516} | 0.2672 |
| 0.2827 | 0.58 | 715 | {'accuracy': 0.8895625} | {'f1': 0.8908652955345562} | 0.2707 |
| 0.2877 | 0.58 | 720 | {'accuracy': 0.8890625} | {'f1': 0.8902356069507142} | 0.2699 |
| 0.2911 | 0.59 | 725 | {'accuracy': 0.88825} | {'f1': 0.890400882677455} | 0.2699 |
| 0.31 | 0.59 | 730 | {'accuracy': 0.8890625} | {'f1': 0.8916030534351145} | 0.2676 |
| 0.3165 | 0.59 | 735 | {'accuracy': 0.8905625} | {'f1': 0.8906103579683889} | 0.2635 |
| 0.2335 | 0.6 | 740 | {'accuracy': 0.891125} | {'f1': 0.8915317559153175} | 0.2650 |
| 0.2433 | 0.6 | 745 | {'accuracy': 0.8900625} | {'f1': 0.8933874780289714} | 0.2695 |
| 0.2713 | 0.61 | 750 | {'accuracy': 0.889375} | {'f1': 0.8925970873786407} | 0.2676 |
| 0.2886 | 0.61 | 755 | {'accuracy': 0.88975} | {'f1': 0.8901071517567904} | 0.2647 |
| 0.2688 | 0.61 | 760 | {'accuracy': 0.8920625} | {'f1': 0.8928460631631197} | 0.2634 |
| 0.2465 | 0.62 | 765 | {'accuracy': 0.8925} | {'f1': 0.8924462231115559} | 0.2627 |
| 0.2947 | 0.62 | 770 | {'accuracy': 0.891875} | {'f1': 0.8941766576951309} | 0.2649 |
| 0.3034 | 0.63 | 775 | {'accuracy': 0.8880625} | {'f1': 0.8916449875975557} | 0.2679 |
| 0.2957 | 0.63 | 780 | {'accuracy': 0.8906875} | {'f1': 0.8924552665559861} | 0.2745 |
| 0.2627 | 0.63 | 785 | {'accuracy': 0.8875} | {'f1': 0.8843038951021982} | 0.2658 |
| 0.2822 | 0.64 | 790 | {'accuracy': 0.8879375} | {'f1': 0.8907972470917839} | 0.2777 |
| 0.3063 | 0.64 | 795 | {'accuracy': 0.8905625} | {'f1': 0.8926491324872785} | 0.2605 |
| 0.2943 | 0.65 | 800 | {'accuracy': 0.8910625} | {'f1': 0.890080090811629} | 0.2726 |
| 0.2507 | 0.65 | 805 | {'accuracy': 0.8905625} | {'f1': 0.8929248455940806} | 0.2668 |
| 0.2985 | 0.65 | 810 | {'accuracy': 0.8898125} | {'f1': 0.8918869197277244} | 0.2688 |
| 0.296 | 0.66 | 815 | {'accuracy': 0.89025} | {'f1': 0.8889451049835567} | 0.2630 |
| 0.2581 | 0.66 | 820 | {'accuracy': 0.8905625} | {'f1': 0.8912354804646253} | 0.2744 |
| 0.2719 | 0.67 | 825 | {'accuracy': 0.8891875} | {'f1': 0.8927339826970779} | 0.2665 |
| 0.2666 | 0.67 | 830 | {'accuracy': 0.8931875} | {'f1': 0.8938443381576495} | 0.2671 |
| 0.2746 | 0.67 | 835 | {'accuracy': 0.8911875} | {'f1': 0.8924976844705157} | 0.2648 |
| 0.266 | 0.68 | 840 | {'accuracy': 0.89025} | {'f1': 0.8902774306423393} | 0.2636 |
| 0.2725 | 0.68 | 845 | {'accuracy': 0.8914375} | {'f1': 0.8913084287591516} | 0.2631 |
| 0.2567 | 0.69 | 850 | {'accuracy': 0.8894375} | {'f1': 0.8909572828699993} | 0.2652 |
| 0.2333 | 0.69 | 855 | {'accuracy': 0.891125} | {'f1': 0.8936248168050805} | 0.2667 |
| 0.2733 | 0.69 | 860 | {'accuracy': 0.8925} | {'f1': 0.8935906953724326} | 0.2649 |
| 0.2982 | 0.7 | 865 | {'accuracy': 0.8915} | {'f1': 0.8913778000250282} | 0.2599 |
| 0.2734 | 0.7 | 870 | {'accuracy': 0.8924375} | {'f1': 0.891481177880068} | 0.2631 |
| 0.2888 | 0.71 | 875 | {'accuracy': 0.89175} | {'f1': 0.8921141148623397} | 0.2583 |
| 0.2774 | 0.71 | 880 | {'accuracy': 0.891625} | {'f1': 0.893305439330544} | 0.2628 |
| 0.26 | 0.72 | 885 | {'accuracy': 0.890125} | {'f1': 0.8933770014556042} | 0.2711 |
| 0.2916 | 0.72 | 890 | {'accuracy': 0.88725} | {'f1': 0.8838078062604664} | 0.2664 |
| 0.2859 | 0.72 | 895 | {'accuracy': 0.8915625} | {'f1': 0.892656066324321} | 0.2630 |
| 0.2943 | 0.73 | 900 | {'accuracy': 0.89125} | {'f1': 0.8945326706267427} | 0.2660 |
| 0.2769 | 0.73 | 905 | {'accuracy': 0.890875} | {'f1': 0.8904229948537717} | 0.2596 |
| 0.301 | 0.74 | 910 | {'accuracy': 0.892125} | {'f1': 0.8922327672327673} | 0.2648 |
| 0.2698 | 0.74 | 915 | {'accuracy': 0.892625} | {'f1': 0.8927858212680978} | 0.2595 |
| 0.2875 | 0.74 | 920 | {'accuracy': 0.892} | {'f1': 0.8941824862216778} | 0.2642 |
| 0.2509 | 0.75 | 925 | {'accuracy': 0.8928125} | {'f1': 0.8945329315540249} | 0.2605 |
| 0.2861 | 0.75 | 930 | {'accuracy': 0.8908125} | {'f1': 0.8919804612625981} | 0.2611 |
| 0.2797 | 0.76 | 935 | {'accuracy': 0.8916875} | {'f1': 0.8944000974955821} | 0.2626 |
| 0.3331 | 0.76 | 940 | {'accuracy': 0.891} | {'f1': 0.8931372549019608} | 0.2659 |
| 0.2752 | 0.76 | 945 | {'accuracy': 0.8916875} | {'f1': 0.8920047360877422} | 0.2580 |
| 0.2962 | 0.77 | 950 | {'accuracy': 0.892875} | {'f1': 0.8959825221507464} | 0.2646 |
| 0.2889 | 0.77 | 955 | {'accuracy': 0.8930625} | {'f1': 0.895434822465318} | 0.2614 |
| 0.2783 | 0.78 | 960 | {'accuracy': 0.8896875} | {'f1': 0.8873715780741497} | 0.2646 |
| 0.2747 | 0.78 | 965 | {'accuracy': 0.8933125} | {'f1': 0.8941001302810347} | 0.2604 |
| 0.2801 | 0.78 | 970 | {'accuracy': 0.893125} | {'f1': 0.8923851478917558} | 0.2599 |
| 0.2498 | 0.79 | 975 | {'accuracy': 0.8928125} | {'f1': 0.8929262658425423} | 0.2637 |
| 0.2704 | 0.79 | 980 | {'accuracy': 0.8910625} | {'f1': 0.8931919848029904} | 0.2646 |
| 0.2875 | 0.8 | 985 | {'accuracy': 0.89225} | {'f1': 0.8936852491366551} | 0.2655 |
| 0.2451 | 0.8 | 990 | {'accuracy': 0.89375} | {'f1': 0.8954746679783571} | 0.2586 |
| 0.287 | 0.8 | 995 | {'accuracy': 0.891875} | {'f1': 0.8900470319054278} | 0.2621 |
| 0.2942 | 0.81 | 1000 | {'accuracy': 0.8919375} | {'f1': 0.8934491896222346} | 0.2597 |
| 0.284 | 0.81 | 1005 | {'accuracy': 0.8915} | {'f1': 0.8929188255613126} | 0.2627 |
| 0.2629 | 0.82 | 1010 | {'accuracy': 0.8923125} | {'f1': 0.8931472868217055} | 0.2582 |
| 0.2459 | 0.82 | 1015 | {'accuracy': 0.8895} | {'f1': 0.8890144381669806} | 0.2605 |
| 0.2554 | 0.82 | 1020 | {'accuracy': 0.890125} | {'f1': 0.8891271442986882} | 0.2564 |
| 0.2696 | 0.83 | 1025 | {'accuracy': 0.8938125} | {'f1': 0.894399900553173} | 0.2543 |
| 0.265 | 0.83 | 1030 | {'accuracy': 0.8935} | {'f1': 0.895690499510284} | 0.2576 |
| 0.2588 | 0.84 | 1035 | {'accuracy': 0.89375} | {'f1': 0.8945409429280397} | 0.2605 |
| 0.2631 | 0.84 | 1040 | {'accuracy': 0.891125} | {'f1': 0.8938969423803143} | 0.2614 |
| 0.2774 | 0.84 | 1045 | {'accuracy': 0.8928125} | {'f1': 0.8935245545415038} | 0.2595 |
| 0.2581 | 0.85 | 1050 | {'accuracy': 0.8925625} | {'f1': 0.8923808927565267} | 0.2608 |
| 0.2706 | 0.85 | 1055 | {'accuracy': 0.8934375} | {'f1': 0.895147899883156} | 0.2590 |
| 0.3022 | 0.86 | 1060 | {'accuracy': 0.8954375} | {'f1': 0.8949714357461234} | 0.2558 |
| 0.2988 | 0.86 | 1065 | {'accuracy': 0.8944375} | {'f1': 0.8938470240713972} | 0.2621 |
| 0.2775 | 0.86 | 1070 | {'accuracy': 0.8931875} | {'f1': 0.8938179558869215} | 0.2589 |
| 0.2571 | 0.87 | 1075 | {'accuracy': 0.8943125} | {'f1': 0.8950276243093922} | 0.2568 |
| 0.2679 | 0.87 | 1080 | {'accuracy': 0.8920625} | {'f1': 0.8911303032213326} | 0.2551 |
| 0.2729 | 0.88 | 1085 | {'accuracy': 0.8935} | {'f1': 0.8946196660482375} | 0.2632 |
| 0.2833 | 0.88 | 1090 | {'accuracy': 0.8945625} | {'f1': 0.8961398756387368} | 0.2579 |
| 0.2895 | 0.88 | 1095 | {'accuracy': 0.8938125} | {'f1': 0.8941762690750545} | 0.2593 |
| 0.2941 | 0.89 | 1100 | {'accuracy': 0.89425} | {'f1': 0.8938785750125439} | 0.2576 |
| 0.2902 | 0.89 | 1105 | {'accuracy': 0.8925625} | {'f1': 0.8932497050239085} | 0.2563 |
| 0.2491 | 0.9 | 1110 | {'accuracy': 0.8905} | {'f1': 0.8902668169860953} | 0.2608 |
| 0.297 | 0.9 | 1115 | {'accuracy': 0.8888125} | {'f1': 0.8883169062715801} | 0.2569 |
| 0.2431 | 0.91 | 1120 | {'accuracy': 0.891375} | {'f1': 0.8939726695949244} | 0.2655 |
| 0.2581 | 0.91 | 1125 | {'accuracy': 0.8909375} | {'f1': 0.8903825617187009} | 0.2594 |
| 0.2593 | 0.91 | 1130 | {'accuracy': 0.890875} | {'f1': 0.8887331124139689} | 0.2633 |
| 0.2551 | 0.92 | 1135 | {'accuracy': 0.8924375} | {'f1': 0.8948236875878506} | 0.2667 |
| 0.2633 | 0.92 | 1140 | {'accuracy': 0.8919375} | {'f1': 0.8952819332566168} | 0.2599 |
| 0.2596 | 0.93 | 1145 | {'accuracy': 0.8934375} | {'f1': 0.8947855600123419} | 0.2547 |
| 0.2613 | 0.93 | 1150 | {'accuracy': 0.893875} | {'f1': 0.8946911436368147} | 0.2524 |
| 0.2694 | 0.93 | 1155 | {'accuracy': 0.8935625} | {'f1': 0.894295822729812} | 0.2579 |
| 0.2483 | 0.94 | 1160 | {'accuracy': 0.89075} | {'f1': 0.892510146353462} | 0.2604 |
| 0.2636 | 0.94 | 1165 | {'accuracy': 0.8924375} | {'f1': 0.8941379098234606} | 0.2565 |
| 0.2451 | 0.95 | 1170 | {'accuracy': 0.8934375} | {'f1': 0.8941585449127817} | 0.2614 |
| 0.2702 | 0.95 | 1175 | {'accuracy': 0.891875} | {'f1': 0.8897386870618229} | 0.2596 |
| 0.2581 | 0.95 | 1180 | {'accuracy': 0.895} | {'f1': 0.8947368421052632} | 0.2529 |
| 0.2686 | 0.96 | 1185 | {'accuracy': 0.8950625} | {'f1': 0.8966196662767072} | 0.2594 |
| 0.2591 | 0.96 | 1190 | {'accuracy': 0.8933125} | {'f1': 0.8917908082408875} | 0.2534 |
| 0.2442 | 0.97 | 1195 | {'accuracy': 0.8940625} | {'f1': 0.8957115609425952} | 0.2705 |
| 0.3009 | 0.97 | 1200 | {'accuracy': 0.895} | {'f1': 0.8958074919374845} | 0.2525 |
| 0.2773 | 0.97 | 1205 | {'accuracy': 0.89475} | {'f1': 0.8945522855353789} | 0.2539 |
| 0.2613 | 0.98 | 1210 | {'accuracy': 0.894375} | {'f1': 0.8957047642557393} | 0.2571 |
| 0.2746 | 0.98 | 1215 | {'accuracy': 0.894625} | {'f1': 0.8950578862193452} | 0.2544 |
| 0.2616 | 0.99 | 1220 | {'accuracy': 0.893875} | {'f1': 0.8933685003767897} | 0.2565 |
| 0.2444 | 0.99 | 1225 | {'accuracy': 0.894875} | {'f1': 0.8942936148818502} | 0.2556 |
| 0.2583 | 0.99 | 1230 | {'accuracy': 0.893875} | {'f1': 0.8957642725598527} | 0.2563 |
| 0.2639 | 1.0 | 1235 | {'accuracy': 0.894625} | {'f1': 0.8963609540201622} | 0.2577 |
| 0.2581 | 1.0 | 1240 | {'accuracy': 0.8945625} | {'f1': 0.895431723795946} | 0.2559 |
| 0.2438 | 1.01 | 1245 | {'accuracy': 0.8935625} | {'f1': 0.8917974458351865} | 0.2657 |
| 0.2432 | 1.01 | 1250 | {'accuracy': 0.897125} | {'f1': 0.8974454828660435} | 0.2554 |
| 0.2441 | 1.01 | 1255 | {'accuracy': 0.892625} | {'f1': 0.8958030082484231} | 0.2704 |
| 0.2339 | 1.02 | 1260 | {'accuracy': 0.8963125} | {'f1': 0.8966677047648708} | 0.2543 |
| 0.2645 | 1.02 | 1265 | {'accuracy': 0.894125} | {'f1': 0.8945336819823185} | 0.2606 |
| 0.2435 | 1.03 | 1270 | {'accuracy': 0.894} | {'f1': 0.8960784313725491} | 0.2607 |
| 0.2049 | 1.03 | 1275 | {'accuracy': 0.8948125} | {'f1': 0.8963606133382598} | 0.2625 |
| 0.261 | 1.03 | 1280 | {'accuracy': 0.895625} | {'f1': 0.8958463265560684} | 0.2678 |
| 0.2447 | 1.04 | 1285 | {'accuracy': 0.8921875} | {'f1': 0.8898115618013416} | 0.2541 |
| 0.2647 | 1.04 | 1290 | {'accuracy': 0.892375} | {'f1': 0.8967006598680263} | 0.2693 |
| 0.2464 | 1.05 | 1295 | {'accuracy': 0.894} | {'f1': 0.8929022480424349} | 0.2640 |
| 0.2345 | 1.05 | 1300 | {'accuracy': 0.895125} | {'f1': 0.894544997486174} | 0.2545 |
| 0.2168 | 1.05 | 1305 | {'accuracy': 0.895625} | {'f1': 0.8981707317073172} | 0.2687 |
| 0.2499 | 1.06 | 1310 | {'accuracy': 0.8951875} | {'f1': 0.8944552835294858} | 0.2571 |
| 0.2605 | 1.06 | 1315 | {'accuracy': 0.895875} | {'f1': 0.8972366148531952} | 0.2523 |
| 0.2483 | 1.07 | 1320 | {'accuracy': 0.895875} | {'f1': 0.8964831614266188} | 0.2626 |
| 0.2602 | 1.07 | 1325 | {'accuracy': 0.89575} | {'f1': 0.8942027147025244} | 0.2574 |
| 0.2129 | 1.07 | 1330 | {'accuracy': 0.8960625} | {'f1': 0.8962764298634067} | 0.2602 |
| 0.2545 | 1.08 | 1335 | {'accuracy': 0.8961875} | {'f1': 0.8967232481502208} | 0.2599 |
| 0.2481 | 1.08 | 1340 | {'accuracy': 0.8945625} | {'f1': 0.8973032203080294} | 0.2610 |
| 0.272 | 1.09 | 1345 | {'accuracy': 0.896} | {'f1': 0.8952800503461298} | 0.2558 |
| 0.2462 | 1.09 | 1350 | {'accuracy': 0.8954375} | {'f1': 0.8946407204483909} | 0.2602 |
| 0.2538 | 1.09 | 1355 | {'accuracy': 0.89475} | {'f1': 0.8976416241186483} | 0.2646 |
| 0.2124 | 1.1 | 1360 | {'accuracy': 0.895375} | {'f1': 0.8954142196676246} | 0.2573 |
| 0.2058 | 1.1 | 1365 | {'accuracy': 0.895875} | {'f1': 0.8953254586579542} | 0.2621 |
| 0.2283 | 1.11 | 1370 | {'accuracy': 0.8943125} | {'f1': 0.8966697219676137} | 0.2587 |
| 0.2252 | 1.11 | 1375 | {'accuracy': 0.89475} | {'f1': 0.895856524427953} | 0.2632 |
| 0.2476 | 1.12 | 1380 | {'accuracy': 0.895625} | {'f1': 0.8955858446917595} | 0.2586 |
| 0.2404 | 1.12 | 1385 | {'accuracy': 0.8940625} | {'f1': 0.8956473557840301} | 0.2586 |
| 0.247 | 1.12 | 1390 | {'accuracy': 0.8979375} | {'f1': 0.8978033669190812} | 0.2541 |
| 0.2379 | 1.13 | 1395 | {'accuracy': 0.8959375} | {'f1': 0.8961775893246867} | 0.2628 |
| 0.2323 | 1.13 | 1400 | {'accuracy': 0.8945625} | {'f1': 0.896964514749893} | 0.2556 |
| 0.1995 | 1.14 | 1405 | {'accuracy': 0.89475} | {'f1': 0.8959594711479055} | 0.2669 |
| 0.2198 | 1.14 | 1410 | {'accuracy': 0.8929375} | {'f1': 0.8922031338493488} | 0.2643 |
| 0.232 | 1.14 | 1415 | {'accuracy': 0.8946875} | {'f1': 0.8957624497370863} | 0.2551 |
| 0.2386 | 1.15 | 1420 | {'accuracy': 0.8928125} | {'f1': 0.8961298528253892} | 0.2904 |
| 0.2487 | 1.15 | 1425 | {'accuracy': 0.895} | {'f1': 0.8943396226415095} | 0.2574 |
| 0.2417 | 1.16 | 1430 | {'accuracy': 0.8960625} | {'f1': 0.8966759863311586} | 0.2603 |
| 0.2667 | 1.16 | 1435 | {'accuracy': 0.895125} | {'f1': 0.8955168119551681} | 0.2588 |
| 0.2226 | 1.16 | 1440 | {'accuracy': 0.896} | {'f1': 0.8958568031042683} | 0.2538 |
| 0.2393 | 1.17 | 1445 | {'accuracy': 0.8951875} | {'f1': 0.8960773377951292} | 0.2582 |
| 0.2505 | 1.17 | 1450 | {'accuracy': 0.8950625} | {'f1': 0.8972523101401384} | 0.2612 |
| 0.2536 | 1.18 | 1455 | {'accuracy': 0.8958125} | {'f1': 0.8964017152445466} | 0.2588 |
| 0.2186 | 1.18 | 1460 | {'accuracy': 0.896125} | {'f1': 0.8967830083219476} | 0.2606 |
| 0.2493 | 1.18 | 1465 | {'accuracy': 0.8955625} | {'f1': 0.8962434026699783} | 0.2555 |
| 0.2357 | 1.19 | 1470 | {'accuracy': 0.8953125} | {'f1': 0.8952404778285071} | 0.2652 |
| 0.2477 | 1.19 | 1475 | {'accuracy': 0.897125} | {'f1': 0.8982443125618199} | 0.2552 |
| 0.2431 | 1.2 | 1480 | {'accuracy': 0.89475} | {'f1': 0.8948682731926582} | 0.2595 |
| 0.2347 | 1.2 | 1485 | {'accuracy': 0.89325} | {'f1': 0.8943984172128107} | 0.2624 |
| 0.2514 | 1.2 | 1490 | {'accuracy': 0.8925625} | {'f1': 0.8918935915980127} | 0.2620 |
| 0.2273 | 1.21 | 1495 | {'accuracy': 0.8905} | {'f1': 0.8938824954572987} | 0.2711 |
| 0.2264 | 1.21 | 1500 | {'accuracy': 0.8935625} | {'f1': 0.8940854530754401} | 0.2606 |
| 0.2361 | 1.22 | 1505 | {'accuracy': 0.8954375} | {'f1': 0.8959771186967606} | 0.2620 |
| 0.252 | 1.22 | 1510 | {'accuracy': 0.8955} | {'f1': 0.8949748743718592} | 0.2595 |
| 0.2239 | 1.22 | 1515 | {'accuracy': 0.8951875} | {'f1': 0.8970976253298153} | 0.2624 |
| 0.2426 | 1.23 | 1520 | {'accuracy': 0.895625} | {'f1': 0.8957683185619773} | 0.2646 |
| 0.2185 | 1.23 | 1525 | {'accuracy': 0.89625} | {'f1': 0.8957940991839297} | 0.2570 |
| 0.2302 | 1.24 | 1530 | {'accuracy': 0.8941875} | {'f1': 0.8961795547924204} | 0.2677 |
| 0.239 | 1.24 | 1535 | {'accuracy': 0.8950625} | {'f1': 0.8957337142147426} | 0.2561 |
| 0.2526 | 1.24 | 1540 | {'accuracy': 0.895625} | {'f1': 0.8951663527934715} | 0.2587 |
| 0.2366 | 1.25 | 1545 | {'accuracy': 0.89425} | {'f1': 0.8961963190184048} | 0.2615 |
| 0.2575 | 1.25 | 1550 | {'accuracy': 0.896125} | {'f1': 0.89705153617443} | 0.2567 |
| 0.246 | 1.26 | 1555 | {'accuracy': 0.8964375} | {'f1': 0.8967408238299993} | 0.2573 |
| 0.2357 | 1.26 | 1560 | {'accuracy': 0.8965} | {'f1': 0.8983550208691382} | 0.2608 |
| 0.2196 | 1.26 | 1565 | {'accuracy': 0.895375} | {'f1': 0.8942246935422723} | 0.2539 |
| 0.2432 | 1.27 | 1570 | {'accuracy': 0.895125} | {'f1': 0.8954126153079033} | 0.2648 |
| 0.2324 | 1.27 | 1575 | {'accuracy': 0.8945} | {'f1': 0.8961869618696188} | 0.2615 |
| 0.2321 | 1.28 | 1580 | {'accuracy': 0.895125} | {'f1': 0.896355775169858} | 0.2554 |
| 0.2328 | 1.28 | 1585 | {'accuracy': 0.8946875} | {'f1': 0.8954130718142884} | 0.2635 |
| 0.2448 | 1.28 | 1590 | {'accuracy': 0.8963125} | {'f1': 0.8980018444512757} | 0.2534 |
| 0.256 | 1.29 | 1595 | {'accuracy': 0.89575} | {'f1': 0.8983174835405998} | 0.2565 |
| 0.2366 | 1.29 | 1600 | {'accuracy': 0.8940625} | {'f1': 0.8932552427734743} | 0.2567 |
| 0.2524 | 1.3 | 1605 | {'accuracy': 0.8950625} | {'f1': 0.8933087627883333} | 0.2590 |
| 0.2322 | 1.3 | 1610 | {'accuracy': 0.89025} | {'f1': 0.8942550885222209} | 0.2691 |
| 0.238 | 1.31 | 1615 | {'accuracy': 0.89275} | {'f1': 0.8901689708141322} | 0.2596 |
| 0.2457 | 1.31 | 1620 | {'accuracy': 0.89625} | {'f1': 0.8980093389039076} | 0.2602 |
| 0.2636 | 1.31 | 1625 | {'accuracy': 0.89525} | {'f1': 0.894710390752607} | 0.2538 |
| 0.2525 | 1.32 | 1630 | {'accuracy': 0.8959375} | {'f1': 0.896306906645077} | 0.2552 |
| 0.238 | 1.32 | 1635 | {'accuracy': 0.8953125} | {'f1': 0.8966750971562519} | 0.2599 |
| 0.2412 | 1.33 | 1640 | {'accuracy': 0.8975} | {'f1': 0.8965560741768639} | 0.2523 |
| 0.2241 | 1.33 | 1645 | {'accuracy': 0.89625} | {'f1': 0.8981969827057524} | 0.2591 |
| 0.248 | 1.33 | 1650 | {'accuracy': 0.8963125} | {'f1': 0.898835294835051} | 0.2648 |
| 0.235 | 1.34 | 1655 | {'accuracy': 0.895625} | {'f1': 0.896066716455066} | 0.2524 |
| 0.2544 | 1.34 | 1660 | {'accuracy': 0.8963125} | {'f1': 0.8965517241379309} | 0.2600 |
| 0.2436 | 1.35 | 1665 | {'accuracy': 0.892} | {'f1': 0.8957780458383594} | 0.2650 |
| 0.2365 | 1.35 | 1670 | {'accuracy': 0.8949375} | {'f1': 0.8930593549207966} | 0.2662 |
| 0.2404 | 1.35 | 1675 | {'accuracy': 0.8950625} | {'f1': 0.8968609865470851} | 0.2632 |
| 0.2424 | 1.36 | 1680 | {'accuracy': 0.8958125} | {'f1': 0.8967610082368241} | 0.2569 |
| 0.2525 | 1.36 | 1685 | {'accuracy': 0.89675} | {'f1': 0.8972125435540069} | 0.2554 |
| 0.2395 | 1.37 | 1690 | {'accuracy': 0.8955625} | {'f1': 0.8974783729063133} | 0.2582 |
| 0.2178 | 1.37 | 1695 | {'accuracy': 0.8981875} | {'f1': 0.8987003295814937} | 0.2549 |
| 0.2156 | 1.37 | 1700 | {'accuracy': 0.89675} | {'f1': 0.8967112667250219} | 0.2613 |
| 0.2378 | 1.38 | 1705 | {'accuracy': 0.8956875} | {'f1': 0.8966371462191118} | 0.2550 |
| 0.2253 | 1.38 | 1710 | {'accuracy': 0.8945} | {'f1': 0.8936759889140842} | 0.2583 |
| 0.2391 | 1.39 | 1715 | {'accuracy': 0.894875} | {'f1': 0.8968224757698442} | 0.2595 |
| 0.2353 | 1.39 | 1720 | {'accuracy': 0.8956875} | {'f1': 0.8966883317858247} | 0.2565 |
| 0.2338 | 1.39 | 1725 | {'accuracy': 0.89575} | {'f1': 0.8956717538153616} | 0.2559 |
| 0.2387 | 1.4 | 1730 | {'accuracy': 0.8954375} | {'f1': 0.8976946126093072} | 0.2582 |
| 0.266 | 1.4 | 1735 | {'accuracy': 0.8948125} | {'f1': 0.8966025680407937} | 0.2557 |
| 0.2259 | 1.41 | 1740 | {'accuracy': 0.89675} | {'f1': 0.8978733926805142} | 0.2539 |
| 0.2592 | 1.41 | 1745 | {'accuracy': 0.897375} | {'f1': 0.8982021078735276} | 0.2587 |
| 0.2504 | 1.41 | 1750 | {'accuracy': 0.8969375} | {'f1': 0.8983416558781826} | 0.2548 |
| 0.2252 | 1.42 | 1755 | {'accuracy': 0.895875} | {'f1': 0.8948497854077253} | 0.2584 |
| 0.249 | 1.42 | 1760 | {'accuracy': 0.8950625} | {'f1': 0.8965814598090546} | 0.2573 |
| 0.2343 | 1.43 | 1765 | {'accuracy': 0.8965} | {'f1': 0.8964741185296323} | 0.2583 |
| 0.2371 | 1.43 | 1770 | {'accuracy': 0.89675} | {'f1': 0.8967629046369203} | 0.2504 |
| 0.2397 | 1.43 | 1775 | {'accuracy': 0.89875} | {'f1': 0.8984071240436474} | 0.2528 |
| 0.2396 | 1.44 | 1780 | {'accuracy': 0.8984375} | {'f1': 0.8991998015011475} | 0.2527 |
| 0.2402 | 1.44 | 1785 | {'accuracy': 0.8970625} | {'f1': 0.8961865742199812} | 0.2488 |
| 0.2364 | 1.45 | 1790 | {'accuracy': 0.89675} | {'f1': 0.8972125435540069} | 0.2673 |
| 0.2475 | 1.45 | 1795 | {'accuracy': 0.8930625} | {'f1': 0.8952427600563276} | 0.2529 |
| 0.2415 | 1.45 | 1800 | {'accuracy': 0.895625} | {'f1': 0.8942100595464335} | 0.2556 |
| 0.275 | 1.46 | 1805 | {'accuracy': 0.89625} | {'f1': 0.8974422340294081} | 0.2575 |
| 0.2461 | 1.46 | 1810 | {'accuracy': 0.8951875} | {'f1': 0.895780249829097} | 0.2554 |
| 0.2233 | 1.47 | 1815 | {'accuracy': 0.8965625} | {'f1': 0.8970579088138334} | 0.2568 |
| 0.246 | 1.47 | 1820 | {'accuracy': 0.8964375} | {'f1': 0.897671833508306} | 0.2492 |
| 0.2345 | 1.47 | 1825 | {'accuracy': 0.8975625} | {'f1': 0.897041271436648} | 0.2543 |
| 0.2587 | 1.48 | 1830 | {'accuracy': 0.8973125} | {'f1': 0.8975238570448449} | 0.2544 |
| 0.2278 | 1.48 | 1835 | {'accuracy': 0.8959375} | {'f1': 0.8983330280271112} | 0.2540 |
| 0.2559 | 1.49 | 1840 | {'accuracy': 0.896125} | {'f1': 0.8956292388847023} | 0.2522 |
| 0.2388 | 1.49 | 1845 | {'accuracy': 0.8959375} | {'f1': 0.897519542069305} | 0.2601 |
| 0.2701 | 1.49 | 1850 | {'accuracy': 0.896875} | {'f1': 0.8961611076148521} | 0.2553 |
| 0.2292 | 1.5 | 1855 | {'accuracy': 0.895875} | {'f1': 0.8959660297239915} | 0.2544 |
| 0.2772 | 1.5 | 1860 | {'accuracy': 0.896625} | {'f1': 0.8983030004918839} | 0.2527 |
| 0.2279 | 1.51 | 1865 | {'accuracy': 0.8973125} | {'f1': 0.8971904136161694} | 0.2518 |
| 0.2192 | 1.51 | 1870 | {'accuracy': 0.89675} | {'f1': 0.8968917738110098} | 0.2564 |
| 0.248 | 1.52 | 1875 | {'accuracy': 0.8958125} | {'f1': 0.8968376755987375} | 0.2518 |
| 0.2304 | 1.52 | 1880 | {'accuracy': 0.8956875} | {'f1': 0.8976889597253724} | 0.2554 |
| 0.2517 | 1.52 | 1885 | {'accuracy': 0.8965625} | {'f1': 0.8977069040113728} | 0.2576 |
| 0.2438 | 1.53 | 1890 | {'accuracy': 0.8975} | {'f1': 0.8987029030265596} | 0.2529 |
| 0.2226 | 1.53 | 1895 | {'accuracy': 0.89525} | {'f1': 0.8980163076548618} | 0.2609 |
| 0.2441 | 1.54 | 1900 | {'accuracy': 0.8964375} | {'f1': 0.8958843857995601} | 0.2547 |
| 0.2526 | 1.54 | 1905 | {'accuracy': 0.898125} | {'f1': 0.89987714987715} | 0.2533 |
| 0.2382 | 1.54 | 1910 | {'accuracy': 0.8984375} | {'f1': 0.898709717633859} | 0.2544 |
| 0.2336 | 1.55 | 1915 | {'accuracy': 0.8979375} | {'f1': 0.8982998069377841} | 0.2571 |
| 0.2448 | 1.55 | 1920 | {'accuracy': 0.8971875} | {'f1': 0.8976671850699844} | 0.2522 |
| 0.2392 | 1.56 | 1925 | {'accuracy': 0.898125} | {'f1': 0.8985940027373397} | 0.2558 |
| 0.2589 | 1.56 | 1930 | {'accuracy': 0.899125} | {'f1': 0.9008721287311141} | 0.2557 |
| 0.2181 | 1.56 | 1935 | {'accuracy': 0.89775} | {'f1': 0.8967171717171718} | 0.2537 |
| 0.2653 | 1.57 | 1940 | {'accuracy': 0.8965} | {'f1': 0.897891231964484} | 0.2557 |
| 0.235 | 1.57 | 1945 | {'accuracy': 0.8971875} | {'f1': 0.8981108702384639} | 0.2548 |
| 0.2663 | 1.58 | 1950 | {'accuracy': 0.8980625} | {'f1': 0.898437013512672} | 0.2550 |
| 0.2476 | 1.58 | 1955 | {'accuracy': 0.899875} | {'f1': 0.9009398961167451} | 0.2486 |
| 0.2655 | 1.58 | 1960 | {'accuracy': 0.8983125} | {'f1': 0.8994996602631415} | 0.2572 |
| 0.2278 | 1.59 | 1965 | {'accuracy': 0.89675} | {'f1': 0.8969560878243513} | 0.2511 |
| 0.2125 | 1.59 | 1970 | {'accuracy': 0.8965625} | {'f1': 0.8961666352970701} | 0.2527 |
| 0.2389 | 1.6 | 1975 | {'accuracy': 0.894125} | {'f1': 0.8973457762695431} | 0.2617 |
| 0.264 | 1.6 | 1980 | {'accuracy': 0.897125} | {'f1': 0.8965820557929128} | 0.2504 |
| 0.226 | 1.6 | 1985 | {'accuracy': 0.8975} | {'f1': 0.9001461276181199} | 0.2559 |
| 0.2381 | 1.61 | 1990 | {'accuracy': 0.8971875} | {'f1': 0.8976544515647359} | 0.2532 |
| 0.2675 | 1.61 | 1995 | {'accuracy': 0.8975625} | {'f1': 0.8990577077046252} | 0.2565 |
| 0.2397 | 1.62 | 2000 | {'accuracy': 0.8984375} | {'f1': 0.8983167511419813} | 0.2531 |
| 0.2459 | 1.62 | 2005 | {'accuracy': 0.896375} | {'f1': 0.8989763587618816} | 0.2579 |
| 0.2365 | 1.62 | 2010 | {'accuracy': 0.897875} | {'f1': 0.8993222427603204} | 0.2526 |
| 0.2127 | 1.63 | 2015 | {'accuracy': 0.8984375} | {'f1': 0.8980871746629038} | 0.2501 |
| 0.2365 | 1.63 | 2020 | {'accuracy': 0.897875} | {'f1': 0.8986855158730159} | 0.2587 |
| 0.226 | 1.64 | 2025 | {'accuracy': 0.895625} | {'f1': 0.8940892947742263} | 0.2499 |
| 0.2411 | 1.64 | 2030 | {'accuracy': 0.8958125} | {'f1': 0.897623288091875} | 0.2568 |
| 0.249 | 1.64 | 2035 | {'accuracy': 0.8961875} | {'f1': 0.8974881194840462} | 0.2605 |
| 0.2433 | 1.65 | 2040 | {'accuracy': 0.89725} | {'f1': 0.8983176645225136} | 0.2497 |
| 0.2222 | 1.65 | 2045 | {'accuracy': 0.897375} | {'f1': 0.8971693386773548} | 0.2541 |
| 0.2207 | 1.66 | 2050 | {'accuracy': 0.8969375} | {'f1': 0.8962697364282569} | 0.2594 |
| 0.2465 | 1.66 | 2055 | {'accuracy': 0.8978125} | {'f1': 0.8991301129002405} | 0.2512 |
| 0.2308 | 1.66 | 2060 | {'accuracy': 0.896875} | {'f1': 0.8969522857856608} | 0.2551 |
| 0.2264 | 1.67 | 2065 | {'accuracy': 0.8971875} | {'f1': 0.8990487879717705} | 0.2562 |
| 0.244 | 1.67 | 2070 | {'accuracy': 0.898875} | {'f1': 0.8983412917818547} | 0.2532 |
| 0.2242 | 1.68 | 2075 | {'accuracy': 0.89925} | {'f1': 0.9005061103567461} | 0.2540 |
| 0.2385 | 1.68 | 2080 | {'accuracy': 0.8990625} | {'f1': 0.9002039176914046} | 0.2535 |
| 0.2271 | 1.68 | 2085 | {'accuracy': 0.900125} | {'f1': 0.9005352919208266} | 0.2492 |
| 0.1976 | 1.69 | 2090 | {'accuracy': 0.898375} | {'f1': 0.8996791707798617} | 0.2617 |
| 0.2139 | 1.69 | 2095 | {'accuracy': 0.897625} | {'f1': 0.8977400424522411} | 0.2484 |
| 0.2637 | 1.7 | 2100 | {'accuracy': 0.89775} | {'f1': 0.8969383898198311} | 0.2473 |
| 0.2372 | 1.7 | 2105 | {'accuracy': 0.897375} | {'f1': 0.8988293284041897} | 0.2553 |
| 0.2197 | 1.71 | 2110 | {'accuracy': 0.898125} | {'f1': 0.8972386836464505} | 0.2569 |
| 0.2418 | 1.71 | 2115 | {'accuracy': 0.8984375} | {'f1': 0.8989490703314471} | 0.2469 |
| 0.2435 | 1.71 | 2120 | {'accuracy': 0.896875} | {'f1': 0.8995372625426206} | 0.2552 |
| 0.2232 | 1.72 | 2125 | {'accuracy': 0.897875} | {'f1': 0.8967652261814506} | 0.2555 |
| 0.245 | 1.72 | 2130 | {'accuracy': 0.898125} | {'f1': 0.8996923076923077} | 0.2487 |
| 0.2598 | 1.73 | 2135 | {'accuracy': 0.8985625} | {'f1': 0.8977122329362829} | 0.2546 |
| 0.2378 | 1.73 | 2140 | {'accuracy': 0.898875} | {'f1': 0.9002957850628542} | 0.2564 |
| 0.2261 | 1.73 | 2145 | {'accuracy': 0.8986875} | {'f1': 0.9000554904741354} | 0.2516 |
| 0.2385 | 1.74 | 2150 | {'accuracy': 0.899875} | {'f1': 0.9007803790412486} | 0.2587 |
| 0.2692 | 1.74 | 2155 | {'accuracy': 0.8983125} | {'f1': 0.8996112790769422} | 0.2516 |
| 0.2509 | 1.75 | 2160 | {'accuracy': 0.899125} | {'f1': 0.8992383568485454} | 0.2495 |
| 0.2365 | 1.75 | 2165 | {'accuracy': 0.9001875} | {'f1': 0.9010103514535425} | 0.2557 |
| 0.2324 | 1.75 | 2170 | {'accuracy': 0.89975} | {'f1': 0.9005579665220088} | 0.2499 |
| 0.2198 | 1.76 | 2175 | {'accuracy': 0.8958125} | {'f1': 0.8988163884673749} | 0.2567 |
| 0.2367 | 1.76 | 2180 | {'accuracy': 0.898625} | {'f1': 0.8976785263689123} | 0.2609 |
| 0.2637 | 1.77 | 2185 | {'accuracy': 0.8970625} | {'f1': 0.8999453253143794} | 0.2534 |
| 0.2262 | 1.77 | 2190 | {'accuracy': 0.9003125} | {'f1': 0.9004183055503527} | 0.2542 |
| 0.2633 | 1.77 | 2195 | {'accuracy': 0.9000625} | {'f1': 0.9013754394621599} | 0.2531 |
| 0.2412 | 1.78 | 2200 | {'accuracy': 0.89925} | {'f1': 0.8999999999999999} | 0.2485 |
| 0.2454 | 1.78 | 2205 | {'accuracy': 0.8975625} | {'f1': 0.8974021909233176} | 0.2545 |
| 0.2394 | 1.79 | 2210 | {'accuracy': 0.8978125} | {'f1': 0.899477405471872} | 0.2624 |
| 0.2377 | 1.79 | 2215 | {'accuracy': 0.899375} | {'f1': 0.8996634675308488} | 0.2502 |
| 0.269 | 1.79 | 2220 | {'accuracy': 0.899} | {'f1': 0.899} | 0.2520 |
| 0.2416 | 1.8 | 2225 | {'accuracy': 0.896875} | {'f1': 0.8997691653505042} | 0.2573 |
| 0.2205 | 1.8 | 2230 | {'accuracy': 0.899125} | {'f1': 0.8980803233139681} | 0.2510 |
| 0.2378 | 1.81 | 2235 | {'accuracy': 0.8984375} | {'f1': 0.8998088661446451} | 0.2558 |
| 0.2417 | 1.81 | 2240 | {'accuracy': 0.89925} | {'f1': 0.8996264009962639} | 0.2508 |
| 0.2253 | 1.81 | 2245 | {'accuracy': 0.89825} | {'f1': 0.8974940183855938} | 0.2528 |
| 0.2072 | 1.82 | 2250 | {'accuracy': 0.8984375} | {'f1': 0.9001658782330897} | 0.2567 |
| 0.2222 | 1.82 | 2255 | {'accuracy': 0.900125} | {'f1': 0.90101585728444} | 0.2469 |
| 0.2418 | 1.83 | 2260 | {'accuracy': 0.8991875} | {'f1': 0.8987762786319422} | 0.2545 |
| 0.2162 | 1.83 | 2265 | {'accuracy': 0.897625} | {'f1': 0.8989886531820426} | 0.2563 |
| 0.2398 | 1.83 | 2270 | {'accuracy': 0.8970625} | {'f1': 0.8947939955285851} | 0.2537 |
| 0.2566 | 1.84 | 2275 | {'accuracy': 0.8939375} | {'f1': 0.8974188478510549} | 0.2566 |
| 0.2573 | 1.84 | 2280 | {'accuracy': 0.8958125} | {'f1': 0.8932983421878001} | 0.2560 |
| 0.2578 | 1.85 | 2285 | {'accuracy': 0.8951875} | {'f1': 0.8988723391424953} | 0.2585 |
| 0.252 | 1.85 | 2290 | {'accuracy': 0.898125} | {'f1': 0.8975487115022} | 0.2471 |
| 0.2162 | 1.85 | 2295 | {'accuracy': 0.8971875} | {'f1': 0.8983375563933008} | 0.2525 |
| 0.2324 | 1.86 | 2300 | {'accuracy': 0.8981875} | {'f1': 0.8990893885894815} | 0.2545 |
| 0.2675 | 1.86 | 2305 | {'accuracy': 0.89825} | {'f1': 0.899605328071041} | 0.2470 |
| 0.208 | 1.87 | 2310 | {'accuracy': 0.9003125} | {'f1': 0.9001189805247668} | 0.2494 |
| 0.2457 | 1.87 | 2315 | {'accuracy': 0.9003125} | {'f1': 0.901342240366178} | 0.2516 |
| 0.2215 | 1.87 | 2320 | {'accuracy': 0.899125} | {'f1': 0.9004441154700222} | 0.2478 |
| 0.2591 | 1.88 | 2325 | {'accuracy': 0.8993125} | {'f1': 0.8989905323217756} | 0.2498 |
| 0.2401 | 1.88 | 2330 | {'accuracy': 0.897375} | {'f1': 0.8991772074174137} | 0.2493 |
| 0.242 | 1.89 | 2335 | {'accuracy': 0.899625} | {'f1': 0.8999252243270189} | 0.2539 |
| 0.2181 | 1.89 | 2340 | {'accuracy': 0.8998125} | {'f1': 0.9009454365692393} | 0.2491 |
| 0.2312 | 1.89 | 2345 | {'accuracy': 0.9011875} | {'f1': 0.9020142547257515} | 0.2483 |
| 0.2335 | 1.9 | 2350 | {'accuracy': 0.900375} | {'f1': 0.90151983195354} | 0.2486 |
| 0.2183 | 1.9 | 2355 | {'accuracy': 0.898625} | {'f1': 0.8981923173487322} | 0.2522 |
| 0.244 | 1.91 | 2360 | {'accuracy': 0.898875} | {'f1': 0.8998142414860681} | 0.2521 |
| 0.2228 | 1.91 | 2365 | {'accuracy': 0.8981875} | {'f1': 0.8977721995607154} | 0.2474 |
| 0.2396 | 1.92 | 2370 | {'accuracy': 0.8993125} | {'f1': 0.9010381473063456} | 0.2567 |
| 0.2142 | 1.92 | 2375 | {'accuracy': 0.8998125} | {'f1': 0.9002799377916019} | 0.2494 |
| 0.2383 | 1.92 | 2380 | {'accuracy': 0.9005} | {'f1': 0.9014851485148515} | 0.2484 |
| 0.2403 | 1.93 | 2385 | {'accuracy': 0.899125} | {'f1': 0.8985671191553545} | 0.2521 |
| 0.2309 | 1.93 | 2390 | {'accuracy': 0.8986875} | {'f1': 0.8994479250666831} | 0.2520 |
| 0.2487 | 1.94 | 2395 | {'accuracy': 0.8978125} | {'f1': 0.8979082110521386} | 0.2510 |
| 0.2554 | 1.94 | 2400 | {'accuracy': 0.898875} | {'f1': 0.900012359411692} | 0.2478 |
| 0.2541 | 1.94 | 2405 | {'accuracy': 0.8989375} | {'f1': 0.8992335015890821} | 0.2504 |
| 0.2245 | 1.95 | 2410 | {'accuracy': 0.9} | {'f1': 0.9008059516429014} | 0.2544 |
| 0.2847 | 1.95 | 2415 | {'accuracy': 0.9005625} | {'f1': 0.9014799677998638} | 0.2519 |
| 0.2187 | 1.96 | 2420 | {'accuracy': 0.9000625} | {'f1': 0.9013145713756712} | 0.2528 |
| 0.2397 | 1.96 | 2425 | {'accuracy': 0.901} | {'f1': 0.9018708957997771} | 0.2503 |
| 0.2181 | 1.96 | 2430 | {'accuracy': 0.900375} | {'f1': 0.9002752752752752} | 0.2475 |
| 0.2289 | 1.97 | 2435 | {'accuracy': 0.9004375} | {'f1': 0.9012582904605467} | 0.2491 |
| 0.2352 | 1.97 | 2440 | {'accuracy': 0.900625} | {'f1': 0.901694076913565} | 0.2572 |
| 0.2339 | 1.98 | 2445 | {'accuracy': 0.8995} | {'f1': 0.90050736295013} | 0.2486 |
| 0.2298 | 1.98 | 2450 | {'accuracy': 0.89925} | {'f1': 0.899801093983093} | 0.2499 |
| 0.2428 | 1.98 | 2455 | {'accuracy': 0.90075} | {'f1': 0.9020841040818843} | 0.2518 |
| 0.245 | 1.99 | 2460 | {'accuracy': 0.9004375} | {'f1': 0.9009513150531617} | 0.2473 |
| 0.2193 | 1.99 | 2465 | {'accuracy': 0.8993125} | {'f1': 0.8981990521327013} | 0.2508 |
| 0.239 | 2.0 | 2470 | {'accuracy': 0.899625} | {'f1': 0.8992092381071922} | 0.2523 |
| 0.2759 | 2.0 | 2475 | {'accuracy': 0.9000625} | {'f1': 0.9012902030989567} | 0.2480 |
| 0.2067 | 2.0 | 2480 | {'accuracy': 0.8993125} | {'f1': 0.9004879856692816} | 0.2604 |
| 0.2109 | 2.01 | 2485 | {'accuracy': 0.8999375} | {'f1': 0.9001434541258654} | 0.2639 |
| 0.2046 | 2.01 | 2490 | {'accuracy': 0.8975625} | {'f1': 0.8983313690217729} | 0.2531 |
| 0.1903 | 2.02 | 2495 | {'accuracy': 0.89925} | {'f1': 0.8997512437810946} | 0.2658 |
| 0.1953 | 2.02 | 2500 | {'accuracy': 0.8991875} | {'f1': 0.8994451717473972} | 0.2667 |
| 0.1998 | 2.02 | 2505 | {'accuracy': 0.8990625} | {'f1': 0.9006826148453354} | 0.2544 |
| 0.2042 | 2.03 | 2510 | {'accuracy': 0.900125} | {'f1': 0.9008561856309717} | 0.2605 |
| 0.196 | 2.03 | 2515 | {'accuracy': 0.89975} | {'f1': 0.899712392147055} | 0.2592 |
| 0.2198 | 2.04 | 2520 | {'accuracy': 0.8995} | {'f1': 0.9007774898185856} | 0.2558 |
| 0.2187 | 2.04 | 2525 | {'accuracy': 0.8988125} | {'f1': 0.8993096585608559} | 0.2607 |
| 0.2271 | 2.04 | 2530 | {'accuracy': 0.9003125} | {'f1': 0.9004183055503527} | 0.2661 |
| 0.2181 | 2.05 | 2535 | {'accuracy': 0.8999375} | {'f1': 0.9001060710051787} | 0.2565 |
| 0.2093 | 2.05 | 2540 | {'accuracy': 0.8998125} | {'f1': 0.9008596697383883} | 0.2621 |
| 0.1977 | 2.06 | 2545 | {'accuracy': 0.8985} | {'f1': 0.8992180712423979} | 0.2671 |
| 0.1849 | 2.06 | 2550 | {'accuracy': 0.8980625} | {'f1': 0.8987773847204121} | 0.2618 |
| 0.2084 | 2.06 | 2555 | {'accuracy': 0.8978125} | {'f1': 0.898592073435465} | 0.2608 |
| 0.1953 | 2.07 | 2560 | {'accuracy': 0.8988125} | {'f1': 0.8994097545821683} | 0.2619 |
| 0.2135 | 2.07 | 2565 | {'accuracy': 0.89925} | {'f1': 0.9003831417624522} | 0.2635 |
| 0.1939 | 2.08 | 2570 | {'accuracy': 0.90025} | {'f1': 0.9003745318352059} | 0.2568 |
| 0.1852 | 2.08 | 2575 | {'accuracy': 0.899625} | {'f1': 0.9007293855853629} | 0.2651 |
| 0.2126 | 2.08 | 2580 | {'accuracy': 0.899125} | {'f1': 0.900049541738915} | 0.2681 |
| 0.1933 | 2.09 | 2585 | {'accuracy': 0.8996875} | {'f1': 0.900130670151204} | 0.2555 |
| 0.2086 | 2.09 | 2590 | {'accuracy': 0.89975} | {'f1': 0.9006565093521616} | 0.2633 |
| 0.2139 | 2.1 | 2595 | {'accuracy': 0.9003125} | {'f1': 0.9020330446532767} | 0.2625 |
| 0.195 | 2.1 | 2600 | {'accuracy': 0.8995625} | {'f1': 0.9008330762110459} | 0.2627 |
| 0.1816 | 2.11 | 2605 | {'accuracy': 0.899875} | {'f1': 0.901208682782437} | 0.2646 |
| 0.2067 | 2.11 | 2610 | {'accuracy': 0.8988125} | {'f1': 0.9000925640234496} | 0.2588 |
| 0.1977 | 2.11 | 2615 | {'accuracy': 0.8989375} | {'f1': 0.8984360278876954} | 0.2642 |
| 0.2135 | 2.12 | 2620 | {'accuracy': 0.9005} | {'f1': 0.9015460729746443} | 0.2702 |
| 0.192 | 2.12 | 2625 | {'accuracy': 0.9011875} | {'f1': 0.9013293390750796} | 0.2614 |
| 0.2117 | 2.13 | 2630 | {'accuracy': 0.9018125} | {'f1': 0.9018676994190769} | 0.2563 |
| 0.1781 | 2.13 | 2635 | {'accuracy': 0.9015625} | {'f1': 0.9023255813953489} | 0.2650 |
| 0.1761 | 2.13 | 2640 | {'accuracy': 0.9005625} | {'f1': 0.9008413836086008} | 0.2683 |
| 0.221 | 2.14 | 2645 | {'accuracy': 0.8996875} | {'f1': 0.9009320412320229} | 0.2607 |
| 0.2039 | 2.14 | 2650 | {'accuracy': 0.899125} | {'f1': 0.8973413051774582} | 0.2577 |
| 0.217 | 2.15 | 2655 | {'accuracy': 0.898} | {'f1': 0.9004635276896804} | 0.2675 |
| 0.2158 | 2.15 | 2660 | {'accuracy': 0.8995} | {'f1': 0.8984720292966284} | 0.2569 |
| 0.2285 | 2.15 | 2665 | {'accuracy': 0.8961875} | {'f1': 0.8994125840247079} | 0.2628 |
| 0.2222 | 2.16 | 2670 | {'accuracy': 0.902125} | {'f1': 0.9022349856411537} | 0.2660 |
| 0.2107 | 2.16 | 2675 | {'accuracy': 0.898} | {'f1': 0.8999386879215204} | 0.2586 |
| 0.2111 | 2.17 | 2680 | {'accuracy': 0.8993125} | {'f1': 0.8986091006356599} | 0.2620 |
| 0.1845 | 2.17 | 2685 | {'accuracy': 0.9003125} | {'f1': 0.9019607843137255} | 0.2671 |
| 0.2147 | 2.17 | 2690 | {'accuracy': 0.9004375} | {'f1': 0.9008896907857897} | 0.2630 |
| 0.1928 | 2.18 | 2695 | {'accuracy': 0.899875} | {'f1': 0.9010744720266765} | 0.2580 |
| 0.1849 | 2.18 | 2700 | {'accuracy': 0.8995} | {'f1': 0.9002976190476191} | 0.2639 |
| 0.2563 | 2.19 | 2705 | {'accuracy': 0.8991875} | {'f1': 0.9003398208217485} | 0.2695 |
| 0.1927 | 2.19 | 2710 | {'accuracy': 0.899875} | {'f1': 0.8999000249937517} | 0.2582 |
| 0.1925 | 2.19 | 2715 | {'accuracy': 0.900125} | {'f1': 0.9015403573629082} | 0.2705 |
| 0.1911 | 2.2 | 2720 | {'accuracy': 0.8998125} | {'f1': 0.9000685742784115} | 0.2630 |
| 0.1983 | 2.2 | 2725 | {'accuracy': 0.8996875} | {'f1': 0.9004651162790697} | 0.2581 |
| 0.2158 | 2.21 | 2730 | {'accuracy': 0.898875} | {'f1': 0.8998762376237623} | 0.2628 |
| 0.1692 | 2.21 | 2735 | {'accuracy': 0.9006875} | {'f1': 0.9013104776100864} | 0.2672 |
| 0.2196 | 2.21 | 2740 | {'accuracy': 0.9004375} | {'f1': 0.9010743339750357} | 0.2638 |
| 0.1887 | 2.22 | 2745 | {'accuracy': 0.89975} | {'f1': 0.9006934125804853} | 0.2568 |
| 0.1866 | 2.22 | 2750 | {'accuracy': 0.898875} | {'f1': 0.8987230846269404} | 0.2689 |
| 0.1998 | 2.23 | 2755 | {'accuracy': 0.8985625} | {'f1': 0.8995233083637714} | 0.2696 |
| 0.1964 | 2.23 | 2760 | {'accuracy': 0.898625} | {'f1': 0.9003563091288858} | 0.2630 |
| 0.1952 | 2.23 | 2765 | {'accuracy': 0.8994375} | {'f1': 0.8997070373371564} | 0.2594 |
| 0.2153 | 2.24 | 2770 | {'accuracy': 0.8996875} | {'f1': 0.901176035958377} | 0.2628 |
| 0.1895 | 2.24 | 2775 | {'accuracy': 0.899625} | {'f1': 0.8994742113169755} | 0.2561 |
| 0.2151 | 2.25 | 2780 | {'accuracy': 0.899375} | {'f1': 0.9011906223149626} | 0.2630 |
| 0.1841 | 2.25 | 2785 | {'accuracy': 0.898875} | {'f1': 0.8990768463073853} | 0.2581 |
| 0.2184 | 2.25 | 2790 | {'accuracy': 0.8980625} | {'f1': 0.9002507491896521} | 0.2607 |
| 0.2145 | 2.26 | 2795 | {'accuracy': 0.897875} | {'f1': 0.898723193256477} | 0.2567 |
| 0.1932 | 2.26 | 2800 | {'accuracy': 0.8985625} | {'f1': 0.9001415123361842} | 0.2615 |
| 0.2109 | 2.27 | 2805 | {'accuracy': 0.899375} | {'f1': 0.8999378495960223} | 0.2629 |
| 0.2163 | 2.27 | 2810 | {'accuracy': 0.8986875} | {'f1': 0.8994229695352733} | 0.2676 |
| 0.2049 | 2.27 | 2815 | {'accuracy': 0.8989375} | {'f1': 0.8988046811440015} | 0.2649 |
| 0.2118 | 2.28 | 2820 | {'accuracy': 0.8989375} | {'f1': 0.8998575586796309} | 0.2545 |
| 0.201 | 2.28 | 2825 | {'accuracy': 0.899625} | {'f1': 0.8995622263914947} | 0.2673 |
| 0.2415 | 2.29 | 2830 | {'accuracy': 0.8991875} | {'f1': 0.9006712235975123} | 0.2619 |
| 0.2162 | 2.29 | 2835 | {'accuracy': 0.8974375} | {'f1': 0.8971868930518138} | 0.2580 |
| 0.1905 | 2.29 | 2840 | {'accuracy': 0.89925} | {'f1': 0.8996013951170903} | 0.2691 |
| 0.2029 | 2.3 | 2845 | {'accuracy': 0.89775} | {'f1': 0.8977883293764839} | 0.2693 |
| 0.1949 | 2.3 | 2850 | {'accuracy': 0.8993125} | {'f1': 0.89986947603953} | 0.2670 |
| 0.2274 | 2.31 | 2855 | {'accuracy': 0.9003125} | {'f1': 0.9005796920775416} | 0.2714 |
| 0.2058 | 2.31 | 2860 | {'accuracy': 0.8994375} | {'f1': 0.9002046765490294} | 0.2661 |
| 0.2255 | 2.32 | 2865 | {'accuracy': 0.898125} | {'f1': 0.9003058103975535} | 0.2625 |
| 0.2258 | 2.32 | 2870 | {'accuracy': 0.8993125} | {'f1': 0.8990411731528483} | 0.2613 |
| 0.1972 | 2.32 | 2875 | {'accuracy': 0.90125} | {'f1': 0.9019364448857994} | 0.2653 |
| 0.2109 | 2.33 | 2880 | {'accuracy': 0.8993125} | {'f1': 0.9003895381190873} | 0.2658 |
| 0.187 | 2.33 | 2885 | {'accuracy': 0.8995625} | {'f1': 0.9004028509451503} | 0.2580 |
| 0.2379 | 2.34 | 2890 | {'accuracy': 0.899625} | {'f1': 0.9000497883993029} | 0.2596 |
| 0.2201 | 2.34 | 2895 | {'accuracy': 0.8985} | {'f1': 0.8994053518334985} | 0.2593 |
| 0.1903 | 2.34 | 2900 | {'accuracy': 0.8995625} | {'f1': 0.8996064221902917} | 0.2605 |
| 0.2173 | 2.35 | 2905 | {'accuracy': 0.899375} | {'f1': 0.900629551907172} | 0.2724 |
| 0.2488 | 2.35 | 2910 | {'accuracy': 0.8999375} | {'f1': 0.9001932547846144} | 0.2631 |
| 0.1918 | 2.36 | 2915 | {'accuracy': 0.9000625} | {'f1': 0.9011315154887776} | 0.2609 |
| 0.1801 | 2.36 | 2920 | {'accuracy': 0.9008125} | {'f1': 0.9011399738366661} | 0.2761 |
| 0.2025 | 2.36 | 2925 | {'accuracy': 0.8994375} | {'f1': 0.9007708911501696} | 0.2703 |
| 0.1981 | 2.37 | 2930 | {'accuracy': 0.9003125} | {'f1': 0.9009747314832061} | 0.2548 |
| 0.1922 | 2.37 | 2935 | {'accuracy': 0.9005} | {'f1': 0.9013263914714269} | 0.2621 |
| 0.2158 | 2.38 | 2940 | {'accuracy': 0.897375} | {'f1': 0.9} | 0.2629 |
| 0.1975 | 2.38 | 2945 | {'accuracy': 0.9011875} | {'f1': 0.9000568936089511} | 0.2659 |
| 0.2039 | 2.38 | 2950 | {'accuracy': 0.90025} | {'f1': 0.9015786877158363} | 0.2612 |
| 0.1995 | 2.39 | 2955 | {'accuracy': 0.902125} | {'f1': 0.9019779669504256} | 0.2522 |
| 0.2023 | 2.39 | 2960 | {'accuracy': 0.90025} | {'f1': 0.901590825009249} | 0.2671 |
| 0.2098 | 2.4 | 2965 | {'accuracy': 0.9011875} | {'f1': 0.9022928125579385} | 0.2658 |
| 0.2158 | 2.4 | 2970 | {'accuracy': 0.9005} | {'f1': 0.9014607576132705} | 0.2536 |
| 0.2074 | 2.4 | 2975 | {'accuracy': 0.89925} | {'f1': 0.9005674808783616} | 0.2604 |
| 0.227 | 2.41 | 2980 | {'accuracy': 0.899625} | {'f1': 0.8993355898207347} | 0.2640 |
| 0.2164 | 2.41 | 2985 | {'accuracy': 0.8999375} | {'f1': 0.9010934700685737} | 0.2520 |
| 0.1945 | 2.42 | 2990 | {'accuracy': 0.90025} | {'f1': 0.9011519881085098} | 0.2609 |
| 0.232 | 2.42 | 2995 | {'accuracy': 0.899875} | {'f1': 0.9003359462486002} | 0.2668 |
| 0.1984 | 2.42 | 3000 | {'accuracy': 0.89925} | {'f1': 0.9010557328750307} | 0.2560 |
| 0.231 | 2.43 | 3005 | {'accuracy': 0.898625} | {'f1': 0.8977430336653638} | 0.2571 |
| 0.227 | 2.43 | 3010 | {'accuracy': 0.900375} | {'f1': 0.9014223871366729} | 0.2585 |
| 0.1902 | 2.44 | 3015 | {'accuracy': 0.899875} | {'f1': 0.9003235440517672} | 0.2577 |
| 0.2106 | 2.44 | 3020 | {'accuracy': 0.8995625} | {'f1': 0.9007718431614696} | 0.2571 |
| 0.2024 | 2.44 | 3025 | {'accuracy': 0.89875} | {'f1': 0.8999753025438378} | 0.2597 |
| 0.1956 | 2.45 | 3030 | {'accuracy': 0.8988125} | {'f1': 0.899509651790702} | 0.2566 |
| 0.2046 | 2.45 | 3035 | {'accuracy': 0.8989375} | {'f1': 0.899633790577866} | 0.2604 |
| 0.1962 | 2.46 | 3040 | {'accuracy': 0.9000625} | {'f1': 0.9008249085157849} | 0.2601 |
| 0.1969 | 2.46 | 3045 | {'accuracy': 0.8981875} | {'f1': 0.8996364980592694} | 0.2591 |
| 0.2069 | 2.46 | 3050 | {'accuracy': 0.898} | {'f1': 0.8989848972517951} | 0.2676 |
| 0.2052 | 2.47 | 3055 | {'accuracy': 0.899375} | {'f1': 0.8999378495960223} | 0.2634 |
| 0.2048 | 2.47 | 3060 | {'accuracy': 0.89825} | {'f1': 0.9003793905274753} | 0.2548 |
| 0.2253 | 2.48 | 3065 | {'accuracy': 0.8984375} | {'f1': 0.8992248062015504} | 0.2629 |
| 0.2144 | 2.48 | 3070 | {'accuracy': 0.89775} | {'f1': 0.8997549019607843} | 0.2666 |
| 0.204 | 2.48 | 3075 | {'accuracy': 0.8985625} | {'f1': 0.8987081070960494} | 0.2578 |
| 0.2097 | 2.49 | 3080 | {'accuracy': 0.8995625} | {'f1': 0.9012596006144393} | 0.2600 |
| 0.2035 | 2.49 | 3085 | {'accuracy': 0.899625} | {'f1': 0.9003474807644577} | 0.2597 |
| 0.2091 | 2.5 | 3090 | {'accuracy': 0.8995} | {'f1': 0.8996630475477349} | 0.2559 |
| 0.2073 | 2.5 | 3095 | {'accuracy': 0.900375} | {'f1': 0.9015927892332386} | 0.2550 |
| 0.2082 | 2.51 | 3100 | {'accuracy': 0.9003125} | {'f1': 0.9006292442838453} | 0.2591 |
| 0.182 | 2.51 | 3105 | {'accuracy': 0.9} | {'f1': 0.9011247064639722} | 0.2627 |
| 0.1948 | 2.51 | 3110 | {'accuracy': 0.899875} | {'f1': 0.900149588631264} | 0.2644 |
| 0.2118 | 2.52 | 3115 | {'accuracy': 0.8996875} | {'f1': 0.9013339890576013} | 0.2546 |
| 0.2312 | 2.52 | 3120 | {'accuracy': 0.8994375} | {'f1': 0.8988749921438} | 0.2566 |
| 0.2055 | 2.53 | 3125 | {'accuracy': 0.900375} | {'f1': 0.90151983195354} | 0.2563 |
| 0.226 | 2.53 | 3130 | {'accuracy': 0.899875} | {'f1': 0.8999125328001999} | 0.2596 |
| 0.2044 | 2.53 | 3135 | {'accuracy': 0.898375} | {'f1': 0.900269872423945} | 0.2636 |
| 0.2141 | 2.54 | 3140 | {'accuracy': 0.89975} | {'f1': 0.9002487562189055} | 0.2577 |
| 0.1802 | 2.54 | 3145 | {'accuracy': 0.899375} | {'f1': 0.9005313233658718} | 0.2594 |
| 0.204 | 2.55 | 3150 | {'accuracy': 0.8988125} | {'f1': 0.8997461143104837} | 0.2656 |
| 0.1937 | 2.55 | 3155 | {'accuracy': 0.89925} | {'f1': 0.9008853910477127} | 0.2611 |
| 0.1968 | 2.55 | 3160 | {'accuracy': 0.900875} | {'f1': 0.900899775056236} | 0.2555 |
| 0.2046 | 2.56 | 3165 | {'accuracy': 0.900375} | {'f1': 0.9013369645951969} | 0.2537 |
| 0.2041 | 2.56 | 3170 | {'accuracy': 0.902375} | {'f1': 0.9030656571925034} | 0.2582 |
| 0.215 | 2.57 | 3175 | {'accuracy': 0.9015} | {'f1': 0.9027040375354981} | 0.2622 |
| 0.1944 | 2.57 | 3180 | {'accuracy': 0.901375} | {'f1': 0.9014612214312476} | 0.2598 |
| 0.1984 | 2.57 | 3185 | {'accuracy': 0.901875} | {'f1': 0.9024723568145111} | 0.2537 |
| 0.2098 | 2.58 | 3190 | {'accuracy': 0.90025} | {'f1': 0.9008202833706189} | 0.2588 |
| 0.1894 | 2.58 | 3195 | {'accuracy': 0.9006875} | {'f1': 0.9017984055373586} | 0.2611 |
| 0.2277 | 2.59 | 3200 | {'accuracy': 0.9025625} | {'f1': 0.9031737159182659} | 0.2562 |
| 0.1832 | 2.59 | 3205 | {'accuracy': 0.9029375} | {'f1': 0.9042599099932187} | 0.2524 |
| 0.1918 | 2.59 | 3210 | {'accuracy': 0.902875} | {'f1': 0.9026193758616368} | 0.2613 |
| 0.2231 | 2.6 | 3215 | {'accuracy': 0.90125} | {'f1': 0.9016679113766493} | 0.2609 |
| 0.2147 | 2.6 | 3220 | {'accuracy': 0.9001875} | {'f1': 0.9002436129677057} | 0.2599 |
| 0.2062 | 2.61 | 3225 | {'accuracy': 0.9011875} | {'f1': 0.902689727334277} | 0.2613 |
| 0.1936 | 2.61 | 3230 | {'accuracy': 0.90175} | {'f1': 0.902553930076866} | 0.2561 |
| 0.2184 | 2.61 | 3235 | {'accuracy': 0.901375} | {'f1': 0.9024239426168686} | 0.2536 |
| 0.2001 | 2.62 | 3240 | {'accuracy': 0.900875} | {'f1': 0.9007136596970076} | 0.2610 |
| 0.2204 | 2.62 | 3245 | {'accuracy': 0.9003125} | {'f1': 0.9007899483734527} | 0.2549 |
| 0.2141 | 2.63 | 3250 | {'accuracy': 0.900125} | {'f1': 0.9018186286556893} | 0.2570 |
| 0.2025 | 2.63 | 3255 | {'accuracy': 0.90075} | {'f1': 0.9007996001999001} | 0.2658 |
| 0.1843 | 2.63 | 3260 | {'accuracy': 0.90025} | {'f1': 0.9017241379310345} | 0.2557 |
| 0.1912 | 2.64 | 3265 | {'accuracy': 0.8999375} | {'f1': 0.8999562582015872} | 0.2537 |
| 0.2224 | 2.64 | 3270 | {'accuracy': 0.8994375} | {'f1': 0.8998942325639271} | 0.2617 |
| 0.224 | 2.65 | 3275 | {'accuracy': 0.8990625} | {'f1': 0.8998573820301358} | 0.2602 |
| 0.2154 | 2.65 | 3280 | {'accuracy': 0.8998125} | {'f1': 0.9000187114077216} | 0.2545 |
| 0.2119 | 2.65 | 3285 | {'accuracy': 0.9015} | {'f1': 0.903122694861077} | 0.2603 |
| 0.2511 | 2.66 | 3290 | {'accuracy': 0.899875} | {'f1': 0.900620347394541} | 0.2648 |
| 0.2143 | 2.66 | 3295 | {'accuracy': 0.90025} | {'f1': 0.9012498453161738} | 0.2539 |
| 0.1977 | 2.67 | 3300 | {'accuracy': 0.900125} | {'f1': 0.8999624389633154} | 0.2540 |
| 0.1722 | 2.67 | 3305 | {'accuracy': 0.9015} | {'f1': 0.9027160493827161} | 0.2593 |
| 0.2061 | 2.67 | 3310 | {'accuracy': 0.8999375} | {'f1': 0.9011911374436833} | 0.2569 |
| 0.1914 | 2.68 | 3315 | {'accuracy': 0.8998125} | {'f1': 0.9001557147306135} | 0.2608 |
| 0.2382 | 2.68 | 3320 | {'accuracy': 0.899375} | {'f1': 0.9005190311418685} | 0.2607 |
| 0.1926 | 2.69 | 3325 | {'accuracy': 0.901875} | {'f1': 0.9021806853582556} | 0.2517 |
| 0.2303 | 2.69 | 3330 | {'accuracy': 0.9019375} | {'f1': 0.9025163094128611} | 0.2569 |
| 0.1782 | 2.69 | 3335 | {'accuracy': 0.9015625} | {'f1': 0.9025190319985146} | 0.2611 |
| 0.2266 | 2.7 | 3340 | {'accuracy': 0.900625} | {'f1': 0.9013402829486225} | 0.2558 |
| 0.1954 | 2.7 | 3345 | {'accuracy': 0.9011875} | {'f1': 0.9019899572252185} | 0.2520 |
| 0.1798 | 2.71 | 3350 | {'accuracy': 0.9018125} | {'f1': 0.9021732361915438} | 0.2615 |
| 0.1999 | 2.71 | 3355 | {'accuracy': 0.9011875} | {'f1': 0.902365219539307} | 0.2581 |
| 0.209 | 2.72 | 3360 | {'accuracy': 0.902} | {'f1': 0.9019754938734683} | 0.2539 |
| 0.2079 | 2.72 | 3365 | {'accuracy': 0.902} | {'f1': 0.9035907525823906} | 0.2659 |
| 0.1943 | 2.72 | 3370 | {'accuracy': 0.9016875} | {'f1': 0.9019143231277672} | 0.2658 |
| 0.2 | 2.73 | 3375 | {'accuracy': 0.90325} | {'f1': 0.9038628741771209} | 0.2498 |
| 0.2233 | 2.73 | 3380 | {'accuracy': 0.90275} | {'f1': 0.9040690505548706} | 0.2544 |
| 0.1787 | 2.74 | 3385 | {'accuracy': 0.9035} | {'f1': 0.9030637870416877} | 0.2585 |
| 0.2063 | 2.74 | 3390 | {'accuracy': 0.902} | {'f1': 0.9034958148695225} | 0.2608 |
| 0.2215 | 2.74 | 3395 | {'accuracy': 0.901875} | {'f1': 0.9026175412479841} | 0.2518 |
| 0.1945 | 2.75 | 3400 | {'accuracy': 0.900875} | {'f1': 0.9019898652824125} | 0.2596 |
| 0.2038 | 2.75 | 3405 | {'accuracy': 0.900875} | {'f1': 0.9009369144284822} | 0.2649 |
| 0.2055 | 2.76 | 3410 | {'accuracy': 0.90075} | {'f1': 0.9020961775585697} | 0.2579 |
| 0.2083 | 2.76 | 3415 | {'accuracy': 0.901} | {'f1': 0.9011482775836246} | 0.2515 |
| 0.1892 | 2.76 | 3420 | {'accuracy': 0.901} | {'f1': 0.9020286986640278} | 0.2574 |
| 0.2221 | 2.77 | 3425 | {'accuracy': 0.9011875} | {'f1': 0.9016240433078214} | 0.2593 |
| 0.1966 | 2.77 | 3430 | {'accuracy': 0.8985625} | {'f1': 0.9003377341111453} | 0.2536 |
| 0.1838 | 2.78 | 3435 | {'accuracy': 0.900375} | {'f1': 0.9004372267332916} | 0.2568 |
| 0.2102 | 2.78 | 3440 | {'accuracy': 0.8985625} | {'f1': 0.9008249312557286} | 0.2597 |
| 0.2429 | 2.78 | 3445 | {'accuracy': 0.90075} | {'f1': 0.9006133433471022} | 0.2535 |
| 0.2054 | 2.79 | 3450 | {'accuracy': 0.8993125} | {'f1': 0.9011717072572234} | 0.2604 |
| 0.1889 | 2.79 | 3455 | {'accuracy': 0.9005} | {'f1': 0.9015217122355561} | 0.2626 |
| 0.2159 | 2.8 | 3460 | {'accuracy': 0.9006875} | {'f1': 0.9022695122701272} | 0.2576 |
| 0.2044 | 2.8 | 3465 | {'accuracy': 0.90175} | {'f1': 0.9008827238335435} | 0.2509 |
| 0.2174 | 2.8 | 3470 | {'accuracy': 0.9018125} | {'f1': 0.9026702186977263} | 0.2563 |
| 0.1981 | 2.81 | 3475 | {'accuracy': 0.9023125} | {'f1': 0.902147373693107} | 0.2551 |
| 0.1921 | 2.81 | 3480 | {'accuracy': 0.9019375} | {'f1': 0.9029264369238383} | 0.2568 |
| 0.1968 | 2.82 | 3485 | {'accuracy': 0.901625} | {'f1': 0.9022481679294497} | 0.2625 |
| 0.1697 | 2.82 | 3490 | {'accuracy': 0.90025} | {'f1': 0.9000125297581757} | 0.2613 |
| 0.1859 | 2.82 | 3495 | {'accuracy': 0.9011875} | {'f1': 0.9019169923692536} | 0.2626 |
| 0.2016 | 2.83 | 3500 | {'accuracy': 0.90075} | {'f1': 0.9012192087583977} | 0.2546 |
| 0.1893 | 2.83 | 3505 | {'accuracy': 0.9436875} | {'f1': 0.9439920432647478} | 0.1479 |
| 0.1691 | 2.84 | 3510 | {'accuracy': 0.9446875} | {'f1': 0.9445245408387136} | 0.1482 |
| 0.1814 | 2.84 | 3515 | {'accuracy': 0.9433125} | {'f1': 0.9439327440192866} | 0.1487 |
| 0.1611 | 2.85 | 3520 | {'accuracy': 0.9448125} | {'f1': 0.9446082428956778} | 0.1467 |
| 0.1987 | 2.85 | 3525 | {'accuracy': 0.9425} | {'f1': 0.9431115508285927} | 0.1506 |
| 0.174 | 2.85 | 3530 | {'accuracy': 0.943625} | {'f1': 0.9430771172535656} | 0.1465 |
| 0.1716 | 2.86 | 3535 | {'accuracy': 0.9434375} | {'f1': 0.9437992920573807} | 0.1461 |
| 0.166 | 2.86 | 3540 | {'accuracy': 0.944625} | {'f1': 0.9446665001249063} | 0.1456 |
| 0.1614 | 2.87 | 3545 | {'accuracy': 0.9436875} | {'f1': 0.9434790791041967} | 0.1462 |
| 0.1798 | 2.87 | 3550 | {'accuracy': 0.940875} | {'f1': 0.9421618977745169} | 0.1525 |
| 0.1806 | 2.87 | 3555 | {'accuracy': 0.9435625} | {'f1': 0.9427647841795018} | 0.1487 |
| 0.1837 | 2.88 | 3560 | {'accuracy': 0.9406875} | {'f1': 0.9419607363464009} | 0.1533 |
| 0.1737 | 2.88 | 3565 | {'accuracy': 0.9439375} | {'f1': 0.9437652811735942} | 0.1455 |
| 0.2097 | 2.89 | 3570 | {'accuracy': 0.94475} | {'f1': 0.9449838187702265} | 0.1455 |
| 0.1794 | 2.89 | 3575 | {'accuracy': 0.944875} | {'f1': 0.9448612153038259} | 0.1454 |
| 0.1748 | 2.89 | 3580 | {'accuracy': 0.9448125} | {'f1': 0.9447192136730732} | 0.1452 |
| 0.175 | 2.9 | 3585 | {'accuracy': 0.94475} | {'f1': 0.9450453810767128} | 0.1459 |
| 0.1752 | 2.9 | 3590 | {'accuracy': 0.945} | {'f1': 0.9449656035021889} | 0.1451 |
| 0.1558 | 2.91 | 3595 | {'accuracy': 0.9440625} | {'f1': 0.9444478927440878} | 0.1451 |
| 0.1553 | 2.91 | 3600 | {'accuracy': 0.945375} | {'f1': 0.9452380952380952} | 0.1444 |
| 0.1831 | 2.91 | 3605 | {'accuracy': 0.943375} | {'f1': 0.9441085749537323} | 0.1476 |
| 0.1785 | 2.92 | 3610 | {'accuracy': 0.944875} | {'f1': 0.9448060075093867} | 0.1475 |
| 0.1635 | 2.92 | 3615 | {'accuracy': 0.943875} | {'f1': 0.9444444444444445} | 0.1472 |
| 0.1774 | 2.93 | 3620 | {'accuracy': 0.945} | {'f1': 0.9453144419587373} | 0.1456 |
| 0.184 | 2.93 | 3625 | {'accuracy': 0.9445625} | {'f1': 0.9449581135587962} | 0.1456 |
| 0.1906 | 2.93 | 3630 | {'accuracy': 0.9444375} | {'f1': 0.9445449441706693} | 0.1454 |
| 0.1769 | 2.94 | 3635 | {'accuracy': 0.9435} | {'f1': 0.9440663284246998} | 0.1476 |
| 0.1595 | 2.94 | 3640 | {'accuracy': 0.944875} | {'f1': 0.9452241957520805} | 0.1464 |
| 0.1691 | 2.95 | 3645 | {'accuracy': 0.9425625} | {'f1': 0.9433659949466936} | 0.1480 |
| 0.1837 | 2.95 | 3650 | {'accuracy': 0.944375} | {'f1': 0.9445482866043614} | 0.1473 |
| 0.1896 | 2.95 | 3655 | {'accuracy': 0.9436875} | {'f1': 0.944227793252863} | 0.1478 |
| 0.1481 | 2.96 | 3660 | {'accuracy': 0.94375} | {'f1': 0.9439461883408071} | 0.1470 |
| 0.1957 | 2.96 | 3665 | {'accuracy': 0.9419375} | {'f1': 0.9428061318721911} | 0.1513 |
| 0.1972 | 2.97 | 3670 | {'accuracy': 0.9425} | {'f1': 0.9422690763052209} | 0.1483 |
| 0.1833 | 2.97 | 3675 | {'accuracy': 0.9425625} | {'f1': 0.94319095011436} | 0.1482 |
| 0.1897 | 2.97 | 3680 | {'accuracy': 0.9445625} | {'f1': 0.9448348777909074} | 0.1476 |
| 0.1712 | 2.98 | 3685 | {'accuracy': 0.9439375} | {'f1': 0.9443582904286335} | 0.1478 |
| 0.1808 | 2.98 | 3690 | {'accuracy': 0.9433125} | {'f1': 0.94374496061527} | 0.1475 |
| 0.174 | 2.99 | 3695 | {'accuracy': 0.9431875} | {'f1': 0.9435999255444562} | 0.1473 |
| 0.1891 | 2.99 | 3700 | {'accuracy': 0.942625} | {'f1': 0.943101524730383} | 0.1479 |
| 0.1987 | 2.99 | 3705 | {'accuracy': 0.9444375} | {'f1': 0.9447242429894921} | 0.1468 |
| 0.1853 | 3.0 | 3710 | {'accuracy': 0.9399375} | {'f1': 0.9411980664504682} | 0.1516 |
| 0.1736 | 3.0 | 3715 | {'accuracy': 0.943125} | {'f1': 0.9428248303593869} | 0.1471 |
| 0.1708 | 3.01 | 3720 | {'accuracy': 0.942625} | {'f1': 0.9434520142909942} | 0.1487 |
| 0.1609 | 3.01 | 3725 | {'accuracy': 0.943125} | {'f1': 0.9432456030934264} | 0.1477 |
| 0.1699 | 3.01 | 3730 | {'accuracy': 0.941625} | {'f1': 0.9423314398616943} | 0.1506 |
| 0.1821 | 3.02 | 3735 | {'accuracy': 0.9435} | {'f1': 0.943485871467867} | 0.1466 |
| 0.1691 | 3.02 | 3740 | {'accuracy': 0.9433125} | {'f1': 0.9435629394561633} | 0.1478 |
| 0.2098 | 3.03 | 3745 | {'accuracy': 0.9436875} | {'f1': 0.9436417088884719} | 0.1476 |
| 0.1485 | 3.03 | 3750 | {'accuracy': 0.943875} | {'f1': 0.9436778725539388} | 0.1469 |
| 0.169 | 3.04 | 3755 | {'accuracy': 0.942} | {'f1': 0.9428430647942843} | 0.1501 |
| 0.1785 | 3.04 | 3760 | {'accuracy': 0.944125} | {'f1': 0.9441319835020623} | 0.1469 |
| 0.1466 | 3.04 | 3765 | {'accuracy': 0.943375} | {'f1': 0.9438661710037175} | 0.1476 |
| 0.1943 | 3.05 | 3770 | {'accuracy': 0.9431875} | {'f1': 0.9435929258454855} | 0.1475 |
| 0.1868 | 3.05 | 3775 | {'accuracy': 0.9443125} | {'f1': 0.9443785504713154} | 0.1465 |
| 0.1731 | 3.06 | 3780 | {'accuracy': 0.9450625} | {'f1': 0.9448245558973072} | 0.1463 |
| 0.1952 | 3.06 | 3785 | {'accuracy': 0.9434375} | {'f1': 0.9439037996652824} | 0.1469 |
| 0.1699 | 3.06 | 3790 | {'accuracy': 0.9435625} | {'f1': 0.9437698486829814} | 0.1460 |
| 0.1749 | 3.07 | 3795 | {'accuracy': 0.94325} | {'f1': 0.9437003968253969} | 0.1463 |
| 0.17 | 3.07 | 3800 | {'accuracy': 0.9428125} | {'f1': 0.9432206019236736} | 0.1463 |
| 0.2013 | 3.08 | 3805 | {'accuracy': 0.9425} | {'f1': 0.9431607562090696} | 0.1490 |
| 0.171 | 3.08 | 3810 | {'accuracy': 0.943375} | {'f1': 0.9432686286787727} | 0.1464 |
| 0.1632 | 3.08 | 3815 | {'accuracy': 0.9428125} | {'f1': 0.9432839521477717} | 0.1469 |
| 0.1539 | 3.09 | 3820 | {'accuracy': 0.94175} | {'f1': 0.9427025697774498} | 0.1511 |
| 0.156 | 3.09 | 3825 | {'accuracy': 0.94225} | {'f1': 0.9416593004167193} | 0.1507 |
| 0.1985 | 3.1 | 3830 | {'accuracy': 0.94275} | {'f1': 0.9434008897676717} | 0.1481 |
| 0.168 | 3.1 | 3835 | {'accuracy': 0.9423125} | {'f1': 0.9423593330419034} | 0.1464 |
| 0.1726 | 3.1 | 3840 | {'accuracy': 0.9434375} | {'f1': 0.9435398340507829} | 0.1464 |
| 0.1528 | 3.11 | 3845 | {'accuracy': 0.94175} | {'f1': 0.9425613213361271} | 0.1494 |
| 0.1878 | 3.11 | 3850 | {'accuracy': 0.9413125} | {'f1': 0.9414916817247181} | 0.1471 |
| 0.1768 | 3.12 | 3855 | {'accuracy': 0.9414375} | {'f1': 0.9420782592569696} | 0.1489 |
| 0.174 | 3.12 | 3860 | {'accuracy': 0.942875} | {'f1': 0.9432720953326713} | 0.1492 |
| 0.1759 | 3.12 | 3865 | {'accuracy': 0.944625} | {'f1': 0.9448730711796913} | 0.1465 |
| 0.1714 | 3.13 | 3870 | {'accuracy': 0.94375} | {'f1': 0.9438972696671237} | 0.1463 |
| 0.1642 | 3.13 | 3875 | {'accuracy': 0.9424375} | {'f1': 0.9428624604504} | 0.1475 |
| 0.1983 | 3.14 | 3880 | {'accuracy': 0.9435} | {'f1': 0.9438160348042263} | 0.1484 |
| 0.1512 | 3.14 | 3885 | {'accuracy': 0.943125} | {'f1': 0.9434642147117296} | 0.1492 |
| 0.1588 | 3.14 | 3890 | {'accuracy': 0.9425} | {'f1': 0.9427931849272478} | 0.1476 |
| 0.1825 | 3.15 | 3895 | {'accuracy': 0.9423125} | {'f1': 0.9427241700279242} | 0.1481 |
| 0.1554 | 3.15 | 3900 | {'accuracy': 0.9421875} | {'f1': 0.9422560709157876} | 0.1497 |
| 0.1668 | 3.16 | 3905 | {'accuracy': 0.942875} | {'f1': 0.943067148374237} | 0.1503 |
| 0.17 | 3.16 | 3910 | {'accuracy': 0.9436875} | {'f1': 0.9439223252629614} | 0.1468 |
| 0.1834 | 3.16 | 3915 | {'accuracy': 0.9430625} | {'f1': 0.942944823698879} | 0.1472 |
| 0.1814 | 3.17 | 3920 | {'accuracy': 0.94275} | {'f1': 0.9434498086183479} | 0.1484 |
| 0.1858 | 3.17 | 3925 | {'accuracy': 0.9429375} | {'f1': 0.9427550316634271} | 0.1475 |
| 0.188 | 3.18 | 3930 | {'accuracy': 0.94225} | {'f1': 0.9426443202979518} | 0.1469 |
| 0.1832 | 3.18 | 3935 | {'accuracy': 0.9429375} | {'f1': 0.9432884030063979} | 0.1471 |
| 0.1389 | 3.18 | 3940 | {'accuracy': 0.9435} | {'f1': 0.9438648782911078} | 0.1478 |
| 0.1858 | 3.19 | 3945 | {'accuracy': 0.943125} | {'f1': 0.9433233682112605} | 0.1484 |
| 0.1639 | 3.19 | 3950 | {'accuracy': 0.9430625} | {'f1': 0.9434196633749456} | 0.1476 |
| 0.1852 | 3.2 | 3955 | {'accuracy': 0.9435} | {'f1': 0.9437601094935921} | 0.1461 |
| 0.1723 | 3.2 | 3960 | {'accuracy': 0.9430625} | {'f1': 0.9436645847504793} | 0.1471 |
| 0.1728 | 3.2 | 3965 | {'accuracy': 0.94325} | {'f1': 0.9436304941643905} | 0.1456 |
| 0.1714 | 3.21 | 3970 | {'accuracy': 0.9428125} | {'f1': 0.943262851119241} | 0.1465 |
| 0.1941 | 3.21 | 3975 | {'accuracy': 0.9441875} | {'f1': 0.9438964629013005} | 0.1454 |
| 0.1839 | 3.22 | 3980 | {'accuracy': 0.942125} | {'f1': 0.9428536163910146} | 0.1483 |
| 0.1799 | 3.22 | 3985 | {'accuracy': 0.9434375} | {'f1': 0.943518691880422} | 0.1460 |
| 0.1718 | 3.23 | 3990 | {'accuracy': 0.943} | {'f1': 0.9431634052100212} | 0.1470 |
| 0.1657 | 3.23 | 3995 | {'accuracy': 0.941375} | {'f1': 0.9419051158181593} | 0.1480 |
| 0.1577 | 3.23 | 4000 | {'accuracy': 0.9431875} | {'f1': 0.94330443460363} | 0.1476 |
| 0.1738 | 3.24 | 4005 | {'accuracy': 0.94325} | {'f1': 0.9436724565756823} | 0.1487 |
| 0.1995 | 3.24 | 4010 | {'accuracy': 0.9448125} | {'f1': 0.9449123463722005} | 0.1476 |
| 0.1568 | 3.25 | 4015 | {'accuracy': 0.9440625} | {'f1': 0.9441706693281767} | 0.1471 |
| 0.1715 | 3.25 | 4020 | {'accuracy': 0.9430625} | {'f1': 0.9433069886116124} | 0.1470 |
| 0.1852 | 3.25 | 4025 | {'accuracy': 0.94325} | {'f1': 0.9437770897832819} | 0.1478 |
| 0.1607 | 3.26 | 4030 | {'accuracy': 0.9433125} | {'f1': 0.9437379815147943} | 0.1489 |
| 0.2045 | 3.26 | 4035 | {'accuracy': 0.941} | {'f1': 0.941699604743083} | 0.1509 |
| 0.175 | 3.27 | 4040 | {'accuracy': 0.94325} | {'f1': 0.9431718613093003} | 0.1471 |
| 0.1579 | 3.27 | 4045 | {'accuracy': 0.94225} | {'f1': 0.9430613754005422} | 0.1498 |
| 0.1965 | 3.27 | 4050 | {'accuracy': 0.9431875} | {'f1': 0.9431341883015326} | 0.1469 |
| 0.186 | 3.28 | 4055 | {'accuracy': 0.942375} | {'f1': 0.9429172857850422} | 0.1478 |
| 0.1673 | 3.28 | 4060 | {'accuracy': 0.9434375} | {'f1': 0.9436663554310613} | 0.1475 |
| 0.1742 | 3.29 | 4065 | {'accuracy': 0.943125} | {'f1': 0.9433938790743968} | 0.1478 |
| 0.1634 | 3.29 | 4070 | {'accuracy': 0.9425625} | {'f1': 0.9428873283201791} | 0.1473 |
| 0.174 | 3.29 | 4075 | {'accuracy': 0.942125} | {'f1': 0.9423196711100037} | 0.1470 |
| 0.1703 | 3.3 | 4080 | {'accuracy': 0.9421875} | {'f1': 0.9423208829581592} | 0.1476 |
| 0.1718 | 3.3 | 4085 | {'accuracy': 0.9416875} | {'f1': 0.942232679091078} | 0.1491 |
| 0.1839 | 3.31 | 4090 | {'accuracy': 0.943} | {'f1': 0.9431988041853512} | 0.1469 |
| 0.1527 | 3.31 | 4095 | {'accuracy': 0.9438125} | {'f1': 0.9439001560062403} | 0.1465 |
| 0.1753 | 3.31 | 4100 | {'accuracy': 0.9435625} | {'f1': 0.9436224011987263} | 0.1467 |
| 0.1613 | 3.32 | 4105 | {'accuracy': 0.9423125} | {'f1': 0.9428022556856913} | 0.1483 |
| 0.1701 | 3.32 | 4110 | {'accuracy': 0.943} | {'f1': 0.9430995757424506} | 0.1477 |
| 0.1674 | 3.33 | 4115 | {'accuracy': 0.941625} | {'f1': 0.9423599111330536} | 0.1513 |
| 0.1889 | 3.33 | 4120 | {'accuracy': 0.9434375} | {'f1': 0.9434127430750954} | 0.1483 |
| 0.1693 | 3.33 | 4125 | {'accuracy': 0.9411875} | {'f1': 0.9417806100352657} | 0.1490 |
| 0.1819 | 3.34 | 4130 | {'accuracy': 0.942375} | {'f1': 0.9427186878727635} | 0.1470 |
| 0.1964 | 3.34 | 4135 | {'accuracy': 0.9423125} | {'f1': 0.942702836923459} | 0.1471 |
| 0.1678 | 3.35 | 4140 | {'accuracy': 0.9419375} | {'f1': 0.9423017203900379} | 0.1470 |
| 0.1817 | 3.35 | 4145 | {'accuracy': 0.9420625} | {'f1': 0.9424759540800498} | 0.1476 |
| 0.1541 | 3.35 | 4150 | {'accuracy': 0.9425} | {'f1': 0.9428571428571428} | 0.1474 |
| 0.2019 | 3.36 | 4155 | {'accuracy': 0.942875} | {'f1': 0.9430387635547801} | 0.1470 |
| 0.186 | 3.36 | 4160 | {'accuracy': 0.9425625} | {'f1': 0.9430289504680429} | 0.1471 |
| 0.1764 | 3.37 | 4165 | {'accuracy': 0.9415} | {'f1': 0.9421221864951769} | 0.1478 |
| 0.1601 | 3.37 | 4170 | {'accuracy': 0.9421875} | {'f1': 0.9423352658811794} | 0.1475 |
| 0.1719 | 3.37 | 4175 | {'accuracy': 0.9415625} | {'f1': 0.9420514409668423} | 0.1478 |
| 0.1658 | 3.38 | 4180 | {'accuracy': 0.9403125} | {'f1': 0.9410893837517735} | 0.1491 |
| 0.1577 | 3.38 | 4185 | {'accuracy': 0.94125} | {'f1': 0.9416583912611719} | 0.1473 |
| 0.1678 | 3.39 | 4190 | {'accuracy': 0.942} | {'f1': 0.9422166874221668} | 0.1473 |
| 0.165 | 3.39 | 4195 | {'accuracy': 0.9400625} | {'f1': 0.9408863958577328} | 0.1501 |
| 0.196 | 3.39 | 4200 | {'accuracy': 0.94225} | {'f1': 0.9423940149625936} | 0.1472 |
| 0.1646 | 3.4 | 4205 | {'accuracy': 0.9425625} | {'f1': 0.942673569958206} | 0.1470 |
| 0.1501 | 3.4 | 4210 | {'accuracy': 0.93975} | {'f1': 0.9408080559990175} | 0.1522 |
| 0.1976 | 3.41 | 4215 | {'accuracy': 0.941625} | {'f1': 0.9413316582914573} | 0.1492 |
| 0.1827 | 3.41 | 4220 | {'accuracy': 0.94175} | {'f1': 0.9422767248854205} | 0.1487 |
| 0.1669 | 3.41 | 4225 | {'accuracy': 0.9425} | {'f1': 0.9428713363139593} | 0.1483 |
| 0.1892 | 3.42 | 4230 | {'accuracy': 0.94225} | {'f1': 0.9423364952571143} | 0.1479 |
| 0.1822 | 3.42 | 4235 | {'accuracy': 0.940875} | {'f1': 0.941402378592666} | 0.1491 |
| 0.193 | 3.43 | 4240 | {'accuracy': 0.941} | {'f1': 0.9413373104648273} | 0.1479 |
| 0.1556 | 3.43 | 4245 | {'accuracy': 0.94075} | {'f1': 0.9413584065322281} | 0.1494 |
| 0.1804 | 3.44 | 4250 | {'accuracy': 0.9415} | {'f1': 0.9416822429906541} | 0.1480 |
| 0.1968 | 3.44 | 4255 | {'accuracy': 0.9398125} | {'f1': 0.940771265145458} | 0.1516 |
| 0.1628 | 3.44 | 4260 | {'accuracy': 0.9418125} | {'f1': 0.9419322647040479} | 0.1482 |
| 0.1552 | 3.45 | 4265 | {'accuracy': 0.942375} | {'f1': 0.9425902864259029} | 0.1480 |
| 0.1953 | 3.45 | 4270 | {'accuracy': 0.9400625} | {'f1': 0.940944639448242} | 0.1521 |
| 0.1652 | 3.46 | 4275 | {'accuracy': 0.941375} | {'f1': 0.9412722263961932} | 0.1472 |
| 0.1803 | 3.46 | 4280 | {'accuracy': 0.9421875} | {'f1': 0.9426000620539869} | 0.1498 |
| 0.1973 | 3.46 | 4285 | {'accuracy': 0.9418125} | {'f1': 0.9419684597643833} | 0.1484 |
| 0.1738 | 3.47 | 4290 | {'accuracy': 0.94075} | {'f1': 0.9415680473372781} | 0.1519 |
| 0.1746 | 3.47 | 4295 | {'accuracy': 0.9421875} | {'f1': 0.9425929373797555} | 0.1504 |
| 0.1671 | 3.48 | 4300 | {'accuracy': 0.9406875} | {'f1': 0.9413001793777448} | 0.1515 |
| 0.1758 | 3.48 | 4305 | {'accuracy': 0.94025} | {'f1': 0.9407242063492064} | 0.1507 |
| 0.1629 | 3.48 | 4310 | {'accuracy': 0.941625} | {'f1': 0.9418285999003487} | 0.1488 |
| 0.1641 | 3.49 | 4315 | {'accuracy': 0.941125} | {'f1': 0.9417223459539719} | 0.1492 |
| 0.1622 | 3.49 | 4320 | {'accuracy': 0.9428125} | {'f1': 0.9430367926290232} | 0.1478 |
| 0.1677 | 3.5 | 4325 | {'accuracy': 0.943125} | {'f1': 0.9430823117338004} | 0.1481 |
| 0.1879 | 3.5 | 4330 | {'accuracy': 0.9398125} | {'f1': 0.9406178701362767} | 0.1503 |
| 0.1815 | 3.5 | 4335 | {'accuracy': 0.94125} | {'f1': 0.9417523856735655} | 0.1485 |
| 0.1653 | 3.51 | 4340 | {'accuracy': 0.94175} | {'f1': 0.9422266303000247} | 0.1485 |
| 0.1791 | 3.51 | 4345 | {'accuracy': 0.94075} | {'f1': 0.9415103652517276} | 0.1504 |
| 0.1769 | 3.52 | 4350 | {'accuracy': 0.9420625} | {'f1': 0.942224992209411} | 0.1489 |
| 0.1764 | 3.52 | 4355 | {'accuracy': 0.94175} | {'f1': 0.9422266303000247} | 0.1499 |
| 0.1842 | 3.52 | 4360 | {'accuracy': 0.941125} | {'f1': 0.9414834140887067} | 0.1506 |
| 0.1849 | 3.53 | 4365 | {'accuracy': 0.9409375} | {'f1': 0.9411324985983929} | 0.1501 |
| 0.1992 | 3.53 | 4370 | {'accuracy': 0.94125} | {'f1': 0.9417884567748328} | 0.1497 |
| 0.1775 | 3.54 | 4375 | {'accuracy': 0.940125} | {'f1': 0.9408349802371542} | 0.1502 |
| 0.1984 | 3.54 | 4380 | {'accuracy': 0.9420625} | {'f1': 0.9424759540800498} | 0.1488 |
| 0.157 | 3.54 | 4385 | {'accuracy': 0.942} | {'f1': 0.94240317775571} | 0.1483 |
| 0.1704 | 3.55 | 4390 | {'accuracy': 0.941375} | {'f1': 0.9420558438349396} | 0.1493 |
| 0.196 | 3.55 | 4395 | {'accuracy': 0.9425625} | {'f1': 0.9426306261314691} | 0.1480 |
| 0.1705 | 3.56 | 4400 | {'accuracy': 0.943625} | {'f1': 0.9439054726368159} | 0.1487 |
| 0.1809 | 3.56 | 4405 | {'accuracy': 0.944} | {'f1': 0.9440768942703782} | 0.1478 |
| 0.1812 | 3.56 | 4410 | {'accuracy': 0.944375} | {'f1': 0.9444305694305695} | 0.1473 |
| 0.1684 | 3.57 | 4415 | {'accuracy': 0.9434375} | {'f1': 0.943560960399127} | 0.1476 |
| 0.1717 | 3.57 | 4420 | {'accuracy': 0.943} | {'f1': 0.9431988041853512} | 0.1476 |
| 0.1863 | 3.58 | 4425 | {'accuracy': 0.9426875} | {'f1': 0.9431529353418883} | 0.1480 |
| 0.1753 | 3.58 | 4430 | {'accuracy': 0.942} | {'f1': 0.9422454568085636} | 0.1480 |
| 0.1805 | 3.58 | 4435 | {'accuracy': 0.940625} | {'f1': 0.9411983164149542} | 0.1486 |
| 0.1569 | 3.59 | 4440 | {'accuracy': 0.942375} | {'f1': 0.9426830784533134} | 0.1482 |
| 0.1645 | 3.59 | 4445 | {'accuracy': 0.9425625} | {'f1': 0.942472613458529} | 0.1478 |
| 0.187 | 3.6 | 4450 | {'accuracy': 0.93975} | {'f1': 0.9404791306495431} | 0.1500 |
| 0.2041 | 3.6 | 4455 | {'accuracy': 0.9404375} | {'f1': 0.9410600531881996} | 0.1502 |
| 0.1877 | 3.6 | 4460 | {'accuracy': 0.942875} | {'f1': 0.942767689417658} | 0.1493 |
| 0.1725 | 3.61 | 4465 | {'accuracy': 0.94} | {'f1': 0.9407187847350871} | 0.1516 |
| 0.1773 | 3.61 | 4470 | {'accuracy': 0.94225} | {'f1': 0.942134268537074} | 0.1491 |
| 0.1706 | 3.62 | 4475 | {'accuracy': 0.941375} | {'f1': 0.9416884247171453} | 0.1505 |
| 0.199 | 3.62 | 4480 | {'accuracy': 0.9389375} | {'f1': 0.9399987717251121} | 0.1541 |
| 0.1652 | 3.63 | 4485 | {'accuracy': 0.9418125} | {'f1': 0.941317365269461} | 0.1496 |
| 0.1766 | 3.63 | 4490 | {'accuracy': 0.9416875} | {'f1': 0.941908972044082} | 0.1489 |
| 0.167 | 3.63 | 4495 | {'accuracy': 0.939875} | {'f1': 0.9405365310916058} | 0.1510 |
| 0.184 | 3.64 | 4500 | {'accuracy': 0.9428125} | {'f1': 0.9428089255578475} | 0.1493 |
| 0.1637 | 3.64 | 4505 | {'accuracy': 0.941875} | {'f1': 0.9422718808193669} | 0.1489 |
| 0.1758 | 3.65 | 4510 | {'accuracy': 0.9420625} | {'f1': 0.9422537843393759} | 0.1478 |
| 0.1794 | 3.65 | 4515 | {'accuracy': 0.9431875} | {'f1': 0.9431555249828029} | 0.1473 |
| 0.1653 | 3.65 | 4520 | {'accuracy': 0.943125} | {'f1': 0.9434642147117296} | 0.1502 |
| 0.1647 | 3.66 | 4525 | {'accuracy': 0.94275} | {'f1': 0.9430419102101727} | 0.1508 |
| 0.1836 | 3.66 | 4530 | {'accuracy': 0.943375} | {'f1': 0.9434245035593856} | 0.1483 |
| 0.1876 | 3.67 | 4535 | {'accuracy': 0.943375} | {'f1': 0.9432117337344866} | 0.1475 |
| 0.1612 | 3.67 | 4540 | {'accuracy': 0.942} | {'f1': 0.9423172550969666} | 0.1478 |
| 0.1875 | 3.67 | 4545 | {'accuracy': 0.9418125} | {'f1': 0.9421918658801615} | 0.1495 |
| 0.1538 | 3.68 | 4550 | {'accuracy': 0.9428125} | {'f1': 0.9433681995419942} | 0.1497 |
| 0.166 | 3.68 | 4555 | {'accuracy': 0.9435} | {'f1': 0.9435916635467366} | 0.1476 |
| 0.184 | 3.69 | 4560 | {'accuracy': 0.943125} | {'f1': 0.9434220343198209} | 0.1482 |
| 0.1819 | 3.69 | 4565 | {'accuracy': 0.94225} | {'f1': 0.9426158241212272} | 0.1487 |
| 0.1735 | 3.69 | 4570 | {'accuracy': 0.9425625} | {'f1': 0.9428233683817581} | 0.1485 |
| 0.171 | 3.7 | 4575 | {'accuracy': 0.9416875} | {'f1': 0.9423397812248934} | 0.1504 |
| 0.1645 | 3.7 | 4580 | {'accuracy': 0.943375} | {'f1': 0.9436567164179104} | 0.1485 |
| 0.218 | 3.71 | 4585 | {'accuracy': 0.9431875} | {'f1': 0.9433891760602853} | 0.1483 |
| 0.1639 | 3.71 | 4590 | {'accuracy': 0.9420625} | {'f1': 0.9423973156030573} | 0.1488 |
| 0.1911 | 3.71 | 4595 | {'accuracy': 0.941875} | {'f1': 0.9421929388363999} | 0.1498 |
| 0.1824 | 3.72 | 4600 | {'accuracy': 0.9410625} | {'f1': 0.941577349606592} | 0.1506 |
| 0.1898 | 3.72 | 4605 | {'accuracy': 0.9408125} | {'f1': 0.9415396012099513} | 0.1516 |
| 0.1793 | 3.73 | 4610 | {'accuracy': 0.942125} | {'f1': 0.9423412204234122} | 0.1497 |
| 0.1906 | 3.73 | 4615 | {'accuracy': 0.9423125} | {'f1': 0.9425244411233576} | 0.1498 |
| 0.1686 | 3.73 | 4620 | {'accuracy': 0.942125} | {'f1': 0.9420380570856285} | 0.1491 |
| 0.1728 | 3.74 | 4625 | {'accuracy': 0.9416875} | {'f1': 0.9420172767385495} | 0.1493 |
| 0.169 | 3.74 | 4630 | {'accuracy': 0.9413125} | {'f1': 0.94194027082174} | 0.1505 |
| 0.1773 | 3.75 | 4635 | {'accuracy': 0.9418125} | {'f1': 0.9420334972915757} | 0.1489 |
| 0.1759 | 3.75 | 4640 | {'accuracy': 0.941875} | {'f1': 0.942128189172371} | 0.1490 |
| 0.1851 | 3.75 | 4645 | {'accuracy': 0.9420625} | {'f1': 0.9424259362772498} | 0.1487 |
| 0.1782 | 3.76 | 4650 | {'accuracy': 0.9413125} | {'f1': 0.941673395863097} | 0.1487 |
| 0.1716 | 3.76 | 4655 | {'accuracy': 0.9409375} | {'f1': 0.9410884608191509} | 0.1489 |
| 0.1571 | 3.77 | 4660 | {'accuracy': 0.940375} | {'f1': 0.9407379798732761} | 0.1495 |
The model card is truncated. Read the rest on Hugging Face.
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 16, 2023
- Updated
- Sep 21, 2024