epoch,model,run,accuracy,precision,recall,f1,ratio_valid_classifications
0.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat_torch.float16_lf,0.742,0.7477056799746837,0.742,0.7371050181385632,0.8033333333333333
0.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-35_torch.float16_lf,0.709,0.7987219597893886,0.709,0.7427961200958145,1.0
0.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-70_torch.float16_lf,0.7163333333333334,0.8058657875960304,0.7163333333333334,0.7487811196109319,0.9993333333333333
0.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-105_torch.float16_lf,0.6996666666666667,0.802722482275839,0.6996666666666667,0.7370938556711591,1.0
0.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-140_torch.float16_lf,0.7716666666666666,0.8092193821623755,0.7716666666666666,0.7864287269398251,1.0
1.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-175_torch.float16_lf,0.78,0.810582723471486,0.78,0.7924651054056209,1.0
1.2,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-210_torch.float16_lf,0.7313333333333333,0.8157783263996798,0.7313333333333333,0.7628807622782868,1.0
1.4,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-245_torch.float16_lf,0.751,0.8125856808988221,0.751,0.7745416635653988,1.0
1.6,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-280_torch.float16_lf,0.739,0.8097375095673094,0.739,0.7662329023371559,1.0
1.8,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-315_torch.float16_lf,0.7236666666666667,0.8145530585912838,0.7236666666666667,0.7580428816095297,1.0
2.0,Llama3.1-8B-Chinese-Chat,shenzhi-wang/Llama3.1-8B-Chinese-Chat/checkpoint-350_torch.float16_lf,0.7293333333333333,0.8151184301713545,0.7293333333333333,0.7616699266814145,1.0