Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7025	0.03	250	0.7048	0.5258
0.6927	0.06	500	0.6819	0.5817
0.6659	0.08	750	0.6681	0.5947
0.666	0.11	1000	0.6606	0.6065
0.6596	0.14	1250	0.6559	0.6120
0.6524	0.17	1500	0.6515	0.6212
0.6609	0.19	1750	0.6482	0.6235
0.6572	0.22	2000	0.6447	0.6253
0.6543	0.25	2250	0.6415	0.6358
0.6377	0.28	2500	0.6389	0.6365
0.6433	0.31	2750	0.6361	0.6393
0.6439	0.33	3000	0.6337	0.6420
0.6141	0.36	3250	0.6306	0.6485
0.6257	0.39	3500	0.6290	0.6506
0.6071	0.42	3750	0.6272	0.6531
0.613	0.45	4000	0.6253	0.6561
0.6235	0.47	4250	0.6224	0.6558
0.6167	0.5	4500	0.6205	0.6578
0.6164	0.53	4750	0.6193	0.6613
0.6221	0.56	5000	0.6176	0.6586
0.6322	0.58	5250	0.6162	0.6636
0.6201	0.61	5500	0.6144	0.6606
0.6162	0.64	5750	0.6131	0.6626
0.6224	0.67	6000	0.6117	0.6656
0.6262	0.7	6250	0.6102	0.6651
0.61	0.72	6500	0.6096	0.6663
0.6064	0.75	6750	0.6090	0.6668
0.6393	0.78	7000	0.6080	0.6666
0.6126	0.81	7250	0.6073	0.6691
0.6305	0.84	7500	0.6069	0.6696
0.6056	0.86	7750	0.6074	0.6706
0.622	0.89	8000	0.6065	0.6686
0.5873	0.92	8250	0.6069	0.6726
0.6095	0.95	8500	0.6058	0.6701
0.629	0.97	8750	0.6050	0.6676
0.6418	1.0	9000	0.6046	0.6688
0.598	1.03	9250	0.6046	0.6688
0.585	1.06	9500	0.6042	0.6678
0.6027	1.09	9750	0.6046	0.6666
0.6153	1.11	10000	0.6033	0.6673
0.591	1.14	10250	0.6037	0.6686
0.6169	1.17	10500	0.6025	0.6676
0.6215	1.2	10750	0.6020	0.6708
0.5907	1.22	11000	0.6021	0.6706
0.6133	1.25	11250	0.6021	0.6706
0.6224	1.28	11500	0.6017	0.6728
0.6028	1.31	11750	0.6016	0.6726
0.5937	1.34	12000	0.6021	0.6713
0.5936	1.36	12250	0.6032	0.6708
0.6269	1.39	12500	0.6014	0.6713
0.604	1.42	12750	0.6011	0.6726
0.6157	1.45	13000	0.6002	0.6736
0.6047	1.48	13250	0.5999	0.6718
0.6317	1.5	13500	0.5999	0.6733
0.5997	1.53	13750	0.5996	0.6731
0.5807	1.56	14000	0.5993	0.6748
0.6073	1.59	14250	0.5992	0.6756
0.6096	1.61	14500	0.5993	0.6751
0.6022	1.64	14750	0.5991	0.6776
0.6159	1.67	15000	0.5992	0.6756
0.5933	1.7	15250	0.5994	0.6746
0.633	1.73	15500	0.5987	0.6769
0.6032	1.75	15750	0.5988	0.6761
0.5998	1.78	16000	0.5988	0.6779
0.6129	1.81	16250	0.5989	0.6776
0.6078	1.84	16500	0.5988	0.6786
0.5886	1.87	16750	0.5987	0.6769
0.5991	1.89	17000	0.5987	0.6776
0.6091	1.92	17250	0.5985	0.6769
0.592	1.95	17500	0.5986	0.6769
0.6007	1.98	17750	0.5986	0.6769

Framework versions

PEFT 0.9.0
Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2

Holarissun/RM-HH-GPT2Large_helpful_human_loraR64_40000_gpt2-large_shuffleTrue_extractchosenFalse

RM-HH-GPT2Large_helpful_human_loraR64_40000_gpt2-large_shuffleTrue_extractchosenFalse

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Holarissun/
RM-HH-GPT2Large_helpful_human_loraR64_40000_gpt2-large_shuffleTrue_extractchosenFalse