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Timestamps visible
2023-05-19 06:25:32
[ 9606/65536] Loss:  2.993 - Accuracy:    0.235 | LearningRate: 0.00001 | StepTime:   7.188942s - Rate:  14,136.7 Tokens/s
2023-05-19 06:25:38
[ 9607/65536] Loss:  2.989 - Accuracy:    0.238 | LearningRate: 0.00001 | StepTime:   7.189417s - Rate:  14,135.8 Tokens/s
2023-05-19 06:25:46
[ 9608/65536] Loss:  2.999 - Accuracy:    0.237 | LearningRate: 0.00001 | StepTime:   7.189778s - Rate:  14,135.0 Tokens/s
2023-05-19 06:25:54
[ 9609/65536] Loss:  3.005 - Accuracy:    0.235 | LearningRate: 0.00001 | StepTime:   7.189617s - Rate:  14,134.2 Tokens/s
2023-05-19 06:26:00
[ 9610/65536] Loss:  3.028 - Accuracy:    0.226 | LearningRate: 0.00001 | StepTime:   7.191086s - Rate:  14,133.4 Tokens/s
2023-05-19 06:26:08
[ 9611/65536] Loss:  3.021 - Accuracy:    0.234 | LearningRate: 0.00001 | StepTime:   7.189550s - Rate:  14,132.5 Tokens/s
2023-05-19 06:26:14
[ 9612/65536] Loss:  3.002 - Accuracy:    0.234 | LearningRate: 0.00001 | StepTime:   7.190511s - Rate:  14,131.7 Tokens/s
2023-05-19 06:26:22
[ 9613/65536] Loss:  2.991 - Accuracy:    0.238 | LearningRate: 0.00001 | StepTime:   7.203825s - Rate:  14,130.9 Tokens/s
2023-05-19 06:26:30
[ 9614/65536] Loss:  3.028 - Accuracy:    0.231 | LearningRate: 0.00001 | StepTime:   7.189531s - Rate:  14,130.1 Tokens/s
2023-05-19 06:26:36
[ 9615/65536] Loss:  3.024 - Accuracy:    0.228 | LearningRate: 0.00001 | StepTime:   7.189942s - Rate:  14,129.2 Tokens/s
2023-05-19 06:26:44
[ 9616/65536] Loss:  3.046 - Accuracy:    0.222 | LearningRate: 0.00001 | StepTime:   7.188874s - Rate:  14,128.4 Tokens/s
2023-05-19 06:26:50
[ 9617/65536] Loss:  3.009 - Accuracy:    0.230 | LearningRate: 0.00001 | StepTime:   7.188339s - Rate:  14,127.6 Tokens/s