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Timestamps visible
2022-10-29 13:25:51
[   129/262144] Loss:  2.308 - Accuracy:    0.392 | LearningRate: 0.00126 | StepTime:  22.264354s - Rate: 186,243.3 Tokens/s
2022-10-29 13:26:13
[   133/262144] Loss:  2.301 - Accuracy:    0.395 | LearningRate: 0.00130 | StepTime:  22.267951s - Rate: 186,302.8 Tokens/s
2022-10-29 13:26:35
[   137/262144] Loss:  2.295 - Accuracy:    0.397 | LearningRate: 0.00134 | StepTime:  22.269352s - Rate: 186,358.6 Tokens/s
2022-10-29 13:26:57
[   141/262144] Loss:  2.266 - Accuracy:    0.401 | LearningRate: 0.00138 | StepTime:  22.295141s - Rate: 186,405.2 Tokens/s
2022-10-29 13:27:19
[   145/262144] Loss:  2.239 - Accuracy:    0.405 | LearningRate: 0.00141 | StepTime:  22.263308s - Rate: 186,456.3 Tokens/s
2022-10-29 13:27:43
[   149/262144] Loss:  2.197 - Accuracy:    0.415 | LearningRate: 0.00145 | StepTime:  22.264643s - Rate: 186,497.5 Tokens/s
2022-10-29 13:28:05
[   153/262144] Loss:  2.199 - Accuracy:    0.415 | LearningRate: 0.00149 | StepTime:  22.279205s - Rate: 186,540.5 Tokens/s
2022-10-29 13:28:27
[   157/262144] Loss:  2.183 - Accuracy:    0.418 | LearningRate: 0.00153 | StepTime:  22.286768s - Rate: 186,579.6 Tokens/s
2022-10-29 13:28:49
[   161/262144] Loss:  2.209 - Accuracy:    0.410 | LearningRate: 0.00157 | StepTime:  22.282877s - Rate: 186,617.7 Tokens/s
2022-10-29 13:29:11
[   165/262144] Loss:  2.176 - Accuracy:    0.420 | LearningRate: 0.00161 | StepTime:  22.268262s - Rate: 186,656.8 Tokens/s
2022-10-29 13:29:33
[   169/262144] Loss:  2.161 - Accuracy:    0.426 | LearningRate: 0.00165 | StepTime:  22.270159s - Rate: 186,693.7 Tokens/s
2022-10-29 13:29:55
[   173/262144] Loss:  2.156 - Accuracy:    0.426 | LearningRate: 0.00169 | StepTime:  22.284041s - Rate: 186,726.4 Tokens/s