learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 32
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5.0
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall Lower	Prec Lower	Recall Cap	Prec Cap	Recall Upper	Prec Upper	Cap Recall
0.0611	0.1037	200	0.0382	0.9926	0.9973	0.9948	0.9418	0.9657	0.0	0.0	0.9362
0.0345	0.2074	400	0.0328	0.9920	0.9948	0.9970	0.9646	0.9348	0.0	0.0	0.9589
0.0303	0.3110	600	0.0285	0.9927	0.9984	0.9940	0.9305	0.9760	0.0	0.0	0.9250
0.033	0.4147	800	0.0272	0.9934	0.9974	0.9959	0.9499	0.9660	0.2105	0.3077	0.9456
0.0296	0.5184	1000	0.0270	0.9934	0.9965	0.9967	0.9609	0.9543	0.0526	1.0	0.9555
0.0327	0.6221	1200	0.0276	0.9932	0.9984	0.9944	0.9374	0.9788	0.0	0.0	0.9319

sulaimank/truecaser-lin-sna

truecaser-lin-sna