learning_rate: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
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: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.2909	0.2786	10000	1.9040	0.4197	0.1915	0.2803	0.39	95.844
2.2169	0.5573	20000	1.8850	0.4166	0.1886	0.2831	0.3876	86.0059
2.1929	0.8359	30000	1.8784	0.4213	0.192	0.2858	0.391	86.0011
2.1806	1.1145	40000	1.8755	0.419	0.1905	0.2829	0.3892	91.4016
2.1683	1.3931	50000	1.8673	0.4202	0.1916	0.2834	0.3916	94.264
2.164	1.6718	60000	1.8603	0.4214	0.1923	0.2846	0.3919	90.9084
2.1594	1.9504	70000	1.8519	0.422	0.193	0.2864	0.3929	89.8971

BKVNP/bart_lora_finetune

bart_lora_finetune