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Timestamps visible
2023-05-07 04:47:50
[  155/65536] Loss:  6.408 - Accuracy:    0.001 | LearningRate: 0.00151 | StepTime: 250.317282s - Rate:   4,216.2 Tokens/s
2023-05-07 04:52:00
[  156/65536] Loss:  6.386 - Accuracy:    0.000 | LearningRate: 0.00152 | StepTime: 250.301223s - Rate:   4,216.0 Tokens/s
2023-05-07 04:56:13
[  157/65536] Loss:  6.718 - Accuracy:    0.001 | LearningRate: 0.00153 | StepTime: 250.416399s - Rate:   4,215.8 Tokens/s
2023-05-07 05:00:23
[  158/65536] Loss:  6.707 - Accuracy:    0.001 | LearningRate: 0.00154 | StepTime: 250.397753s - Rate:   4,215.6 Tokens/s
2023-05-07 05:04:33
[  159/65536] Loss:  6.778 - Accuracy:    0.000 | LearningRate: 0.00155 | StepTime: 250.485994s - Rate:   4,215.5 Tokens/s
2023-05-07 05:08:43
[  160/65536] Loss:  7.064 - Accuracy:    0.000 | LearningRate: 0.00156 | StepTime: 250.587615s - Rate:   4,215.3 Tokens/s
2023-05-07 05:12:54
[  161/65536] Loss:  7.104 - Accuracy:    0.000 | LearningRate: 0.00157 | StepTime: 250.667233s - Rate:   4,215.1 Tokens/s
2023-05-07 05:17:04
[  162/65536] Loss:  7.183 - Accuracy:    0.000 | LearningRate: 0.00158 | StepTime: 250.527623s - Rate:   4,214.9 Tokens/s
2023-05-07 05:21:14
[  163/65536] Loss:  7.226 - Accuracy:    0.000 | LearningRate: 0.00159 | StepTime: 250.418120s - Rate:   4,214.7 Tokens/s
2023-05-07 05:25:25
[  164/65536] Loss:  7.159 - Accuracy:    0.000 | LearningRate: 0.00160 | StepTime: 250.613853s - Rate:   4,214.5 Tokens/s
2023-05-07 05:29:35
[  165/65536] Loss:  7.123 - Accuracy:    0.000 | LearningRate: 0.00161 | StepTime: 250.525695s - Rate:   4,214.3 Tokens/s
2023-05-07 05:33:47
[  166/65536] Loss:  7.128 - Accuracy:    0.000 | LearningRate: 0.00162 | StepTime: 250.578585s - Rate:   4,214.2 Tokens/s