learning_rate: 5e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
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_ratio: 0.1
num_epochs: 5

Training Loss	Epoch	Step	Validation Loss
3.7981	0.25	50	3.6827
3.5768	0.5	100	3.5449
3.2662	0.75	150	3.2327
2.9061	1.0	200	2.9117
2.6027	1.25	250	2.6400
2.4047	1.5	300	2.3961
2.1897	1.75	350	2.1825
2.0345	2.0	400	2.1042
2.0123	2.25	450	2.0725
2.0704	2.5	500	2.0525
1.9966	2.75	550	2.0358
2.0171	3.0	600	2.0233
1.9052	3.25	650	2.0137
2.0293	3.5	700	2.0067
1.961	3.75	750	2.0017
1.9371	4.0	800	1.9979
2.006	4.25	850	1.9959
2.0385	4.5	900	1.9948
1.9319	4.75	950	1.9945
1.9252	5.0	1000	1.9944

Rahul-1337/Hindi_Normalisation

Hindi_Normalisation