learning_rate: 0.0003
train_batch_size: 2
eval_batch_size: 2
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
num_epochs: 30

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
1.7277	1.0	170	1.6638	0.2259	0.1090	0.2030	0.2028
1.3022	2.0	340	1.2132	0.2330	0.1179	0.2093	0.2098
0.6794	3.0	510	0.8780	0.2513	0.1356	0.2275	0.2272
0.8604	4.0	680	0.6176	0.2754	0.1583	0.2487	0.2488
0.7036	5.0	850	0.4172	0.2856	0.1794	0.2654	0.2649
1.1999	6.0	1020	0.2687	0.2964	0.2057	0.2832	0.2827
0.5163	7.0	1190	0.1663	0.3011	0.2204	0.2913	0.2907
0.4279	8.0	1360	0.1198	0.3225	0.2403	0.3127	0.3123
0.0776	9.0	1530	0.0814	0.3335	0.2551	0.3241	0.3227
0.3049	10.0	1700	0.0485	0.3348	0.2651	0.3244	0.3240
0.1698	11.0	1870	0.0325	0.3505	0.2912	0.3459	0.3448
0.0392	12.0	2040	0.0258	0.3602	0.3025	0.3569	0.3569
0.0872	13.0	2210	0.0229	0.3714	0.3169	0.3697	0.3690
0.3979	14.0	2380	0.0141	0.3778	0.3236	0.3764	0.3758
0.1664	15.0	2550	0.0094	0.3897	0.3392	0.3890	0.3881
0.1912	16.0	2720	0.0065	0.3936	0.3441	0.3929	0.3921
0.1382	17.0	2890	0.0052	0.4003	0.3521	0.4003	0.3997
0.0843	18.0	3060	0.0028	0.4010	0.3541	0.4010	0.4008
0.307	19.0	3230	0.0023	0.4046	0.3585	0.4049	0.4042
0.0365	20.0	3400	0.0017	0.4052	0.3599	0.4056	0.4049
0.0067	21.0	3570	0.0014	0.4045	0.3588	0.4051	0.4044
0.0326	22.0	3740	0.0013	0.4055	0.3595	0.4059	0.4054
0.0979	23.0	3910	0.0009	0.4067	0.3613	0.4066	0.4062
0.001	24.0	4080	0.0005	0.4071	0.3618	0.4070	0.4066
0.0119	25.0	4250	0.0006	0.4064	0.3614	0.4067	0.4059
0.0481	26.0	4420	0.0003	0.4074	0.3623	0.4073	0.4069
0.0051	27.0	4590	0.0004	0.4074	0.3623	0.4073	0.4069
0.0053	28.0	4760	0.0003	0.4074	0.3623	0.4073	0.4069
0.0274	29.0	4930	0.0003	0.4074	0.3623	0.4073	0.4069
0.0129	30.0	5100	0.0003	0.4074	0.3623	0.4073	0.4069

devagonal/flan-t5-rouge-durga-q5-2

flan-t5-rouge-durga-q5-2