learning_rate: 0.0003
train_batch_size: 16
eval_batch_size: 16
seed: 99
gradient_accumulation_steps: 2
total_train_batch_size: 32
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_steps: 0.1
num_epochs: 24

Training Loss	Epoch	Step	Validation Loss	Exact Match
0.1311	1.0	9104	0.0541	0.8477
0.0946	2.0	18208	0.0372	0.8839
0.0790	3.0	27312	0.0332	0.8960
0.0631	4.0	36416	0.0276	0.9125
0.0478	5.0	45520	0.0255	0.9176
0.0327	6.0	54624	0.0262	0.9246
0.0298	7.0	63728	0.0250	0.9300
0.0284	8.0	72832	0.0253	0.9300
0.0258	9.0	81936	0.0262	0.9335
0.0178	10.0	91040	0.0256	0.9369
0.0144	11.0	100144	0.0272	0.9372
0.0127	12.0	109248	0.0275	0.9404
0.0133	13.0	118352	0.0277	0.9408
0.0117	14.0	127456	0.0280	0.9418
0.0093	15.0	136560	0.0309	0.9424
0.0084	16.0	145664	0.0306	0.9424
0.0062	17.0	154768	0.0322	0.9430
0.0041	18.0	163872	0.0330	0.9446
0.0036	19.0	172976	0.0354	0.9453
0.0030	20.0	182080	0.0351	0.9459
0.0023	21.0	191184	0.0364	0.9469
0.0010	22.0	200288	0.0380	0.9478
0.0007	23.0	209392	0.0396	0.9476
0.0004	24.0	218496	0.0404	0.9474