learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH 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	Recall	F1	Accuracy
No log	1.0	118	0.1285	0.8468	0.5851	0.6920	0.9557
No log	2.0	236	0.0904	0.8260	0.7780	0.8013	0.9673
No log	3.0	354	0.0837	0.8756	0.7739	0.8216	0.9714
No log	4.0	472	0.0796	0.8810	0.7988	0.8379	0.9738
0.1058	5.0	590	0.0780	0.9106	0.8029	0.8534	0.9762
0.1058	6.0	708	0.0738	0.9036	0.8361	0.8685	0.9782
0.1058	7.0	826	0.0744	0.9	0.8402	0.8691	0.9784
0.1058	8.0	944	0.0761	0.9002	0.8423	0.8703	0.9782
0.0232	9.0	1062	0.0766	0.9067	0.8465	0.8755	0.9791
0.0232	10.0	1180	0.0770	0.9083	0.8423	0.8741	0.9790

Saitk/my_awesome_wnut_model

my_awesome_wnut_model