learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch 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: 300
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss
7.7719	16.6667	50	3.3236
2.8253	33.3333	100	3.3940
1.9882	50.0	150	3.9482
1.4762	66.6667	200	3.6320
1.4392	83.3333	250	6.2485
1.2776	100.0	300	4.3183
1.251	116.6667	350	4.1987
1.2782	133.3333	400	4.5603
1.0958	150.0	450	8.2640
1.0485	166.6667	500	5.5495
1.054	183.3333	550	5.3635
1.1684	200.0	600	1.8302
1.109	216.6667	650	6.1931
1.1607	233.3333	700	3.2514
1.0009	250.0	750	3.3236
1.2045	266.6667	800	10.1146
1.1297	283.3333	850	6.5903
0.9679	300.0	900	4.6367

Sai-Harsha-k/pretrained_qa_model

pretrained_qa_model