learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 764
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: 10

Training Loss	Epoch	Step	Validation Loss	Precision Macro	Recall Macro	F1 Macro	Precision Micro	Recall Micro	F1 Micro
1.0673	1.0	182	0.8887	0.3631	0.7965	0.4620	0.3957	0.7856	0.5263
0.8459	2.0	364	0.6065	0.4828	0.8962	0.6049	0.5410	0.8629	0.6651
0.5999	3.0	546	0.3847	0.6292	0.9298	0.7352	0.6802	0.8827	0.7684
0.3859	4.0	728	0.2644	0.7463	0.9422	0.8231	0.8018	0.8943	0.8455
0.2695	5.0	910	0.1774	0.9123	0.9639	0.9365	0.9011	0.9300	0.9153
0.1906	6.0	1092	0.1256	0.9650	0.9739	0.9692	0.9589	0.9491	0.9540
0.1449	7.0	1274	0.0998	0.9801	0.9782	0.9789	0.9797	0.9584	0.9689
0.1115	8.0	1456	0.0728	0.9955	0.9860	0.9907	0.9946	0.9732	0.9838
0.0869	9.0	1638	0.0614	0.9937	0.9896	0.9916	0.9913	0.9802	0.9857
0.0746	10.0	1820	0.0573	0.9964	0.9909	0.9936	0.9923	0.9832	0.9877

lucienbaumgartner/multilabel-mental-health-classifier-v2-iter1

multilabel-mental-health-classifier-v2-iter1