learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.1637	0.0954	100	0.1520	0.7768	0.8398
0.1283	0.1908	200	0.1407	0.7929	0.8420
0.1236	0.2863	300	0.1114	0.8460	0.8808
0.1124	0.3817	400	0.1114	0.8235	0.8725
0.107	0.4771	500	0.1103	0.8299	0.8779
0.1017	0.5725	600	0.1061	0.8594	0.8839
0.1147	0.6679	700	0.1054	0.8401	0.8763
0.1108	0.7634	800	0.0952	0.8557	0.8904
0.1086	0.8588	900	0.0990	0.8600	0.8874
0.1048	0.9542	1000	0.0943	0.8648	0.8935
0.0663	1.0496	1100	0.0896	0.8782	0.9026
0.0635	1.1450	1200	0.0879	0.8535	0.8994
0.065	1.2405	1300	0.0875	0.8723	0.9036
0.059	1.3359	1400	0.0864	0.8782	0.9031
0.0564	1.4313	1500	0.0986	0.8557	0.8887
0.0722	1.5267	1600	0.0865	0.8755	0.9057
0.0558	1.6221	1700	0.0838	0.8852	0.9090
0.0574	1.7176	1800	0.0876	0.8718	0.8992
0.0638	1.8130	1900	0.0959	0.8648	0.8880
0.0522	1.9084	2000	0.0845	0.8830	0.9069
0.0562	2.0038	2100	0.0814	0.8830	0.9081
0.0392	2.0992	2200	0.0836	0.8825	0.9096
0.0352	2.1947	2300	0.0839	0.8820	0.9093
0.0375	2.2901	2400	0.0855	0.8836	0.9090
0.0274	2.3855	2500	0.0868	0.8852	0.9126
0.027	2.4809	2600	0.0863	0.8852	0.9103
0.0309	2.5763	2700	0.0853	0.8793	0.9099
0.0273	2.6718	2800	0.0855	0.8830	0.9110
0.028	2.7672	2900	0.0851	0.8906	0.9116
0.0267	2.8626	3000	0.0856	0.8868	0.9128
0.0261	2.9580	3100	0.0857	0.8847	0.9114

Seroy/plant_model

plant_model