Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.5515	0.05	100	0.5420	0.0859	-0.2570	0.9106	0.3429	-65.3753	-85.3660	-0.4062	-0.3984
0.2448	0.09	200	0.2390	0.3339	-1.2158	0.9888	1.5497	-67.2930	-84.8700	-0.3981	-0.3938
0.0948	0.14	300	0.0937	0.5868	-2.7801	0.9888	3.3669	-70.4216	-84.3642	-0.4035	-0.4048
0.0466	0.18	400	0.0534	0.8294	-3.8553	0.9888	4.6847	-72.5720	-83.8791	-0.4093	-0.4163
0.0261	0.23	500	0.0265	0.9450	-6.0844	0.9888	7.0294	-77.0302	-83.6478	-0.4364	-0.4554
0.0129	0.27	600	0.0155	0.8955	-9.0192	0.9888	9.9148	-82.8998	-83.7468	-0.4445	-0.4719
0.0069	0.32	700	0.0112	0.7377	-12.1121	0.9888	12.8498	-89.0856	-84.0625	-0.4617	-0.4981
0.0044	0.37	800	0.0095	0.5497	-14.1581	0.9888	14.7077	-93.1776	-84.4385	-0.4990	-0.5433
0.004	0.41	900	0.0095	0.5781	-16.2335	0.9888	16.8116	-97.3284	-84.3816	-0.5203	-0.5699
0.0046	0.46	1000	0.0089	0.7788	-16.4021	0.9944	17.1809	-97.6655	-83.9802	-0.5542	-0.6027
0.0127	0.5	1100	0.0080	0.7755	-16.5854	0.9972	17.3608	-98.0321	-83.9869	-0.5407	-0.5882
0.0192	0.55	1200	0.0082	0.8670	-16.5839	0.9916	17.4509	-98.0292	-83.8038	-0.5752	-0.6293
0.0043	0.59	1300	0.0083	0.7239	-18.6420	0.9888	19.3659	-102.1455	-84.0900	-0.5830	-0.6429
0.0063	0.64	1400	0.0078	0.7659	-18.6685	0.9944	19.4343	-102.1983	-84.0061	-0.6007	-0.6587
0.0022	0.68	1500	0.0079	0.5026	-19.6619	0.9888	20.1645	-104.1852	-84.5328	-0.5968	-0.6541
0.005	0.73	1600	0.0069	0.7199	-19.4554	0.9888	20.1754	-103.7723	-84.0980	-0.6482	-0.7077
0.0038	0.78	1700	0.0068	0.8857	-19.6624	0.9888	20.5482	-104.1863	-83.7664	-0.6247	-0.6826
0.0073	0.82	1800	0.0069	1.0901	-19.2226	0.9888	20.3128	-103.3067	-83.3576	-0.5992	-0.6539
0.003	0.87	1900	0.0070	0.8410	-20.8141	0.9916	21.6551	-106.4896	-83.8559	-0.6232	-0.6807
0.01	0.91	2000	0.0059	1.1930	-19.2176	0.9916	20.4106	-103.2967	-83.1518	-0.6641	-0.7237
0.0061	0.96	2100	0.0059	1.6526	-18.5437	0.9944	20.1963	-101.9488	-82.2327	-0.6358	-0.6923
0.0024	1.0	2200	0.0058	1.1178	-18.9331	0.9916	20.0508	-102.7275	-83.3023	-0.6583	-0.7134
0.0027	1.05	2300	0.0058	1.1025	-19.5454	0.9916	20.6479	-103.9522	-83.3328	-0.6872	-0.7461
0.0057	1.1	2400	0.0061	0.8696	-21.2149	0.9972	22.0845	-107.2913	-83.7987	-0.7055	-0.7693
0.0076	1.14	2500	0.0055	1.0200	-20.0814	0.9916	21.1015	-105.0243	-83.4978	-0.7059	-0.7654
0.0025	1.19	2600	0.0058	1.1592	-20.6357	0.9916	21.7949	-106.1328	-83.2194	-0.6809	-0.7385
0.0046	1.23	2700	0.0057	0.8385	-20.2499	0.9916	21.0883	-105.3611	-83.8609	-0.6824	-0.7374
0.0039	1.28	2800	0.0058	0.6816	-20.7605	0.9944	21.4421	-106.3823	-84.1746	-0.7219	-0.7845
0.0024	1.32	2900	0.0059	0.7668	-22.0609	0.9916	22.8277	-108.9833	-84.0043	-0.7625	-0.8322
0.0033	1.37	3000	0.0055	1.3010	-20.9961	0.9916	22.2971	-106.8535	-82.9359	-0.7534	-0.8209
0.0035	1.42	3100	0.0054	1.3118	-20.5134	0.9916	21.8252	-105.8883	-82.9143	-0.7521	-0.8162
0.0033	1.46	3200	0.0055	1.3335	-20.8912	0.9944	22.2247	-106.6437	-82.8708	-0.7612	-0.8293
0.0021	1.51	3300	0.0058	1.1173	-22.2893	0.9916	23.4066	-109.4400	-83.3032	-0.7843	-0.8567
0.0012	1.55	3400	0.0064	0.9283	-23.7370	0.9916	24.6653	-112.3355	-83.6813	-0.7884	-0.8611
0.0004	1.6	3500	0.0068	0.9145	-24.8915	0.9916	25.8060	-114.6444	-83.7089	-0.7965	-0.8752
0.0035	1.64	3600	0.0063	0.9910	-24.2224	0.9916	25.2134	-113.3062	-83.5558	-0.8029	-0.8784
0.0031	1.69	3700	0.0069	0.6681	-25.5613	0.9888	26.2294	-115.9840	-84.2016	-0.8334	-0.9142
0.0063	1.73	3800	0.0064	0.9458	-24.5955	0.9916	25.5413	-114.0523	-83.6462	-0.8256	-0.9017
0.0041	1.78	3900	0.0067	1.2097	-24.8538	0.9916	26.0635	-114.5689	-83.1184	-0.8070	-0.8836
0.0034	1.83	4000	0.0062	1.4285	-24.3976	0.9916	25.8261	-113.6566	-82.6809	-0.8036	-0.8783
0.0043	1.87	4100	0.0064	1.2740	-24.3713	0.9916	25.6453	-113.6040	-82.9898	-0.7990	-0.8751
0.0008	1.92	4200	0.0062	0.8474	-23.9420	0.9888	24.7894	-112.7454	-83.8431	-0.7886	-0.8626
0.0045	1.96	4300	0.0061	0.7728	-24.1102	0.9888	24.8830	-113.0818	-83.9923	-0.8065	-0.8774
0.0025	2.01	4400	0.0056	0.6654	-23.7611	0.9916	24.4265	-112.3836	-84.2071	-0.8145	-0.8857
0.0032	2.05	4500	0.0057	0.3483	-24.4947	0.9944	24.8430	-113.8508	-84.8413	-0.8185	-0.8907
0.0022	2.1	4600	0.0058	0.2667	-24.9497	0.9916	25.2165	-114.7609	-85.0044	-0.8229	-0.8971
0.0011	2.15	4700	0.0060	-0.0008	-25.6118	0.9888	25.6110	-116.0850	-85.5395	-0.8374	-0.9151
0.0066	2.19	4800	0.0061	-0.0374	-26.0644	0.9916	26.0271	-116.9903	-85.6126	-0.8540	-0.9306
0.0022	2.24	4900	0.0063	0.0818	-26.4597	0.9888	26.5415	-117.7807	-85.3742	-0.8703	-0.9493
0.0028	2.28	5000	0.0077	-0.7880	-28.0697	0.9888	27.2817	-121.0009	-87.1139	-0.8802	-0.9634
0.0038	2.33	5100	0.0068	-0.2700	-27.7191	0.9888	27.4491	-120.2996	-86.0779	-0.8897	-0.9719
0.0044	2.37	5200	0.0071	-0.4228	-28.3790	0.9916	27.9562	-121.6195	-86.3835	-0.8925	-0.9753
0.0022	2.42	5300	0.0072	-0.5950	-29.1837	0.9888	28.5887	-123.2288	-86.7278	-0.9123	-0.9960
0.0022	2.46	5400	0.0073	-0.7860	-29.4389	0.9888	28.6529	-123.7393	-87.1098	-0.9223	-1.0087
0.0001	2.51	5500	0.0073	-0.9058	-29.7384	0.9888	28.8326	-124.3382	-87.3495	-0.9299	-1.0164
0.0022	2.56	5600	0.0070	-0.8180	-29.5150	0.9916	28.6970	-123.8913	-87.1738	-0.9322	-1.0181
0.0011	2.6	5700	0.0071	-0.6171	-29.4081	0.9888	28.7910	-123.6776	-86.7721	-0.9332	-1.0216
0.0054	2.65	5800	0.0071	-0.6641	-29.7689	0.9888	29.1048	-124.3992	-86.8661	-0.9405	-1.0273
0.0033	2.69	5900	0.0067	-0.8082	-29.8306	0.9916	29.0224	-124.5226	-87.1543	-0.9436	-1.0315
0.0011	2.74	6000	0.0068	-0.7323	-29.7235	0.9888	28.9912	-124.3083	-87.0024	-0.9401	-1.0278
0.0011	2.78	6100	0.0065	-0.5717	-29.4620	0.9916	28.8903	-123.7853	-86.6812	-0.9389	-1.0250
0.0023	2.83	6200	0.0066	-0.5549	-29.5194	0.9916	28.9645	-123.9002	-86.6477	-0.9369	-1.0244
0.0022	2.88	6300	0.0065	-0.4476	-29.3706	0.9916	28.9230	-123.6025	-86.4330	-0.9362	-1.0220
0.0035	2.92	6400	0.0066	-0.4967	-29.5205	0.9916	29.0238	-123.9024	-86.5313	-0.9395	-1.0256
0.0012	2.97	6500	0.0065	-0.4666	-29.4634	0.9916	28.9968	-123.7882	-86.4710	-0.9381	-1.0240

Framework versions

Transformers 4.35.0
Pytorch 2.1.1+cu121
Datasets 2.14.6
Tokenizers 0.14.1

nlile/PE-7b-full

PE-7b-full

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nlile/
PE-7b-full