learning_rate: 0.0003
train_batch_size: 32
eval_batch_size: 128
seed: 0
gradient_accumulation_steps: 2
total_train_batch_size: 64
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: cosine
lr_scheduler_warmup_steps: 0.06
num_epochs: 2.0

Training Loss	Epoch	Step	Validation Loss	Detection F1	Correction Accuracy
1.2737	0.0949	2500	1.2979	0.5029	0.9692
1.2399	0.1898	5000	1.2654	0.5270	0.9717
1.2310	0.2847	7500	1.2547	0.5397	0.9724
1.2229	0.3796	10000	1.2508	0.5879	0.9729
1.2143	0.4746	12500	1.2477	0.5704	0.9733
1.2158	0.5695	15000	1.2432	0.6009	0.9736
1.2086	0.6644	17500	1.2378	0.6042	0.9739
1.2075	0.7593	20000	1.2348	0.6143	0.9743
1.2045	0.8542	22500	1.2325	0.6165	0.9746
1.2036	0.9491	25000	1.2309	0.6170	0.9749
1.1978	1.0440	27500	1.2278	0.6337	0.9752
1.1943	1.1389	30000	1.2279	0.6477	0.9753
1.1949	1.2338	32500	1.2252	0.6500	0.9756
1.1915	1.3287	35000	1.2241	0.6438	0.9759
1.1902	1.4236	37500	1.2225	0.6487	0.9760
1.1896	1.5186	40000	1.2219	0.6554	0.9762
1.1902	1.6135	42500	1.2204	0.6603	0.9762
1.1895	1.7084	45000	1.2201	0.6614	0.9764
1.1869	1.8033	47500	1.2196	0.6624	0.9764
1.1865	1.8982	50000	1.2192	0.6622	0.9765
1.1894	1.9931	52500	1.2194	0.6631	0.9765
1.1894	2.0	52682	1.2194	0.6631	0.9765

oza75/sanigec-phase1

sanigec-phase1