Training Loss	Epoch	Step	Validation Loss
1.7942	0.11	500	1.8358
1.9793	0.21	1000	1.8000
1.9244	0.32	1500	1.7763
1.8871	0.43	2000	1.7623
1.6525	0.54	2500	1.7511
1.6871	0.64	3000	1.7401
1.5771	0.75	3500	1.7315
1.732	0.86	4000	1.7278
1.9909	0.96	4500	1.7196
1.5173	1.07	5000	1.7204
1.6015	1.18	5500	1.7206
1.6817	1.28	6000	1.7183
1.6475	1.39	6500	1.7161
1.7425	1.5	7000	1.7114
1.4702	1.61	7500	1.7067
1.5635	1.71	8000	1.7078
1.574	1.82	8500	1.7020
1.6691	1.93	9000	1.6985
1.4796	2.03	9500	1.7339
1.472	2.14	10000	1.7354
1.4476	2.25	10500	1.7331
1.4402	2.35	11000	1.7327
1.5988	2.46	11500	1.7328
1.3682	2.57	12000	1.7299
1.4988	2.68	12500	1.7281
1.4514	2.78	13000	1.7257
1.6356	2.89	13500	1.7264
1.6653	3.0	14000	1.7240
1.2013	3.1	14500	1.7782
1.2864	3.21	15000	1.7770
1.4638	3.32	15500	1.7817
1.2501	3.43	16000	1.7787
1.4613	3.53	16500	1.7791
1.1816	3.64	17000	1.7767
1.1841	3.75	17500	1.7786
1.2382	3.85	18000	1.7743
1.2868	3.96	18500	1.7749
1.2074	4.07	19000	1.8167
1.1657	4.17	19500	1.8224
1.1851	4.28	20000	1.8197
1.1141	4.39	20500	1.8225
1.0628	4.5	21000	1.8202
1.0946	4.6	21500	1.8209
1.037	4.71	22000	1.8201
1.1277	4.82	22500	1.8206
1.2766	4.92	23000	1.8204

gayanin/ec-biogpt-noised-pubmed-v4

ec-biogpt-noised-pubmed-v4