homebrewnlp

Clashluke's group workspace

Group: rnn-shortctx-newnormgradv3

687

1-1

of 1

Timestamps visible

2023-05-07 16:32:30

[ 521/65536] Loss: 3.456 - Accuracy: 0.171 | LearningRate: 0.00051 | StepTime: 6.913337s - Rate: 4,481.2 Tokens/s

2023-05-07 16:32:38

[ 522/65536] Loss: 3.446 - Accuracy: 0.162 | LearningRate: 0.00051 | StepTime: 6.906572s - Rate: 4,481.6 Tokens/s

2023-05-07 16:32:44

[ 523/65536] Loss: 3.448 - Accuracy: 0.160 | LearningRate: 0.00051 | StepTime: 6.907716s - Rate: 4,482.1 Tokens/s

2023-05-07 16:32:52

[ 524/65536] Loss: 3.410 - Accuracy: 0.162 | LearningRate: 0.00051 | StepTime: 6.906541s - Rate: 4,482.6 Tokens/s

2023-05-07 16:32:58

[ 525/65536] Loss: 3.407 - Accuracy: 0.166 | LearningRate: 0.00051 | StepTime: 6.904020s - Rate: 4,483.0 Tokens/s

2023-05-07 16:33:06

[ 526/65536] Loss: 3.469 - Accuracy: 0.161 | LearningRate: 0.00051 | StepTime: 6.899176s - Rate: 4,483.5 Tokens/s

2023-05-07 16:33:12

[ 527/65536] Loss: 3.401 - Accuracy: 0.168 | LearningRate: 0.00051 | StepTime: 6.899937s - Rate: 4,483.9 Tokens/s

2023-05-07 16:33:18

[ 528/65536] Loss: 3.426 - Accuracy: 0.177 | LearningRate: 0.00051 | StepTime: 6.901861s - Rate: 4,484.4 Tokens/s

2023-05-07 16:33:26

[ 529/65536] Loss: 3.505 - Accuracy: 0.162 | LearningRate: 0.00051 | StepTime: 6.903952s - Rate: 4,484.8 Tokens/s

2023-05-07 16:33:32

[ 530/65536] Loss: 3.436 - Accuracy: 0.167 | LearningRate: 0.00052 | StepTime: 6.908934s - Rate: 4,485.3 Tokens/s

2023-05-07 16:33:40

[ 531/65536] Loss: 3.441 - Accuracy: 0.173 | LearningRate: 0.00052 | StepTime: 6.902022s - Rate: 4,485.7 Tokens/s

2023-05-07 16:33:46

[ 532/65536] Loss: 3.502 - Accuracy: 0.168 | LearningRate: 0.00052 | StepTime: 6.907601s - Rate: 4,486.1 Tokens/s

2023-05-07 16:33:54

[ 533/65536] Loss: 3.458 - Accuracy: 0.168 | LearningRate: 0.00052 | StepTime: 6.902901s - Rate: 4,486.6 Tokens/s

2023-05-07 16:34:00

[ 534/65536] Loss: 3.410 - Accuracy: 0.173 | LearningRate: 0.00052 | StepTime: 6.905594s - Rate: 4,487.0 Tokens/s

2023-05-07 16:34:08

[ 535/65536] Loss: 3.481 - Accuracy: 0.164 | LearningRate: 0.00052 | StepTime: 6.902677s - Rate: 4,487.5 Tokens/s

2023-05-07 16:34:14

[ 536/65536] Loss: 3.524 - Accuracy: 0.163 | LearningRate: 0.00052 | StepTime: 6.904244s - Rate: 4,487.9 Tokens/s

2023-05-07 16:34:22

[ 537/65536] Loss: 3.462 - Accuracy: 0.166 | LearningRate: 0.00052 | StepTime: 6.904070s - Rate: 4,488.3 Tokens/s

2023-05-07 16:34:28

[ 538/65536] Loss: 3.458 - Accuracy: 0.164 | LearningRate: 0.00052 | StepTime: 6.905093s - Rate: 4,488.8 Tokens/s

2023-05-07 16:34:34

[ 539/65536] Loss: 3.498 - Accuracy: 0.162 | LearningRate: 0.00052 | StepTime: 6.902910s - Rate: 4,489.2 Tokens/s

2023-05-07 16:34:42

[ 540/65536] Loss: 3.447 - Accuracy: 0.165 | LearningRate: 0.00053 | StepTime: 6.905584s - Rate: 4,489.6 Tokens/s

2023-05-07 16:34:48

[ 541/65536] Loss: 3.485 - Accuracy: 0.154 | LearningRate: 0.00053 | StepTime: 6.907894s - Rate: 4,490.1 Tokens/s

2023-05-07 16:34:56

[ 542/65536] Loss: 3.500 - Accuracy: 0.169 | LearningRate: 0.00053 | StepTime: 6.904533s - Rate: 4,490.5 Tokens/s

2023-05-07 16:35:02

[ 543/65536] Loss: 3.540 - Accuracy: 0.163 | LearningRate: 0.00053 | StepTime: 6.901006s - Rate: 4,490.9 Tokens/s

2023-05-07 16:35:10

[ 544/65536] Loss: 3.432 - Accuracy: 0.158 | LearningRate: 0.00053 | StepTime: 6.903087s - Rate: 4,491.4 Tokens/s

2023-05-07 16:35:16

[ 545/65536] Loss: 3.434 - Accuracy: 0.169 | LearningRate: 0.00053 | StepTime: 6.899298s - Rate: 4,491.8 Tokens/s

2023-05-07 16:35:24

[ 546/65536] Loss: 3.458 - Accuracy: 0.175 | LearningRate: 0.00053 | StepTime: 6.897640s - Rate: 4,492.2 Tokens/s

2023-05-07 16:35:30

[ 547/65536] Loss: 3.481 - Accuracy: 0.165 | LearningRate: 0.00053 | StepTime: 6.909202s - Rate: 4,492.6 Tokens/s

2023-05-07 16:35:38

[ 548/65536] Loss: 3.465 - Accuracy: 0.163 | LearningRate: 0.00053 | StepTime: 6.907993s - Rate: 4,493.0 Tokens/s

2023-05-07 16:35:44

[ 549/65536] Loss: 3.459 - Accuracy: 0.165 | LearningRate: 0.00053 | StepTime: 6.906164s - Rate: 4,493.5 Tokens/s

2023-05-07 16:35:50

[ 550/65536] Loss: 3.424 - Accuracy: 0.159 | LearningRate: 0.00054 | StepTime: 6.903120s - Rate: 4,493.9 Tokens/s

2023-05-07 16:35:58

[ 551/65536] Loss: 3.431 - Accuracy: 0.174 | LearningRate: 0.00054 | StepTime: 6.909187s - Rate: 4,494.3 Tokens/s

2023-05-07 16:36:04

[ 552/65536] Loss: 3.463 - Accuracy: 0.165 | LearningRate: 0.00054 | StepTime: 6.909879s - Rate: 4,494.7 Tokens/s

2023-05-07 16:36:12

[ 553/65536] Loss: 3.473 - Accuracy: 0.165 | LearningRate: 0.00054 | StepTime: 6.909453s - Rate: 4,495.1 Tokens/s

2023-05-07 16:36:18

[ 554/65536] Loss: 3.459 - Accuracy: 0.174 | LearningRate: 0.00054 | StepTime: 6.910047s - Rate: 4,495.5 Tokens/s

2023-05-07 16:36:26

[ 555/65536] Loss: 3.429 - Accuracy: 0.172 | LearningRate: 0.00054 | StepTime: 6.906104s - Rate: 4,495.9 Tokens/s

2023-05-07 16:36:32

[ 556/65536] Loss: 3.454 - Accuracy: 0.178 | LearningRate: 0.00054 | StepTime: 6.907190s - Rate: 4,496.3 Tokens/s

2023-05-07 16:36:40

[ 557/65536] Loss: 3.480 - Accuracy: 0.163 | LearningRate: 0.00054 | StepTime: 6.900307s - Rate: 4,496.7 Tokens/s

2023-05-07 16:36:46

[ 558/65536] Loss: 3.387 - Accuracy: 0.173 | LearningRate: 0.00054 | StepTime: 6.903515s - Rate: 4,497.1 Tokens/s

2023-05-07 16:36:54

[ 559/65536] Loss: 3.521 - Accuracy: 0.162 | LearningRate: 0.00054 | StepTime: 6.908235s - Rate: 4,497.5 Tokens/s

2023-05-07 16:37:00

[ 560/65536] Loss: 3.494 - Accuracy: 0.170 | LearningRate: 0.00054 | StepTime: 6.903072s - Rate: 4,497.9 Tokens/s

2023-05-07 16:37:08

[ 561/65536] Loss: 3.453 - Accuracy: 0.161 | LearningRate: 0.00055 | StepTime: 6.899731s - Rate: 4,498.3 Tokens/s

2023-05-07 16:37:14

[ 562/65536] Loss: 3.442 - Accuracy: 0.160 | LearningRate: 0.00055 | StepTime: 6.900900s - Rate: 4,498.7 Tokens/s

2023-05-07 16:37:20

[ 563/65536] Loss: 3.418 - Accuracy: 0.166 | LearningRate: 0.00055 | StepTime: 6.900497s - Rate: 4,499.1 Tokens/s

2023-05-07 16:37:29

[ 564/65536] Loss: 3.434 - Accuracy: 0.168 | LearningRate: 0.00055 | StepTime: 6.900371s - Rate: 4,499.5 Tokens/s

2023-05-07 16:37:35

[ 565/65536] Loss: 3.518 - Accuracy: 0.172 | LearningRate: 0.00055 | StepTime: 6.900555s - Rate: 4,499.9 Tokens/s

2023-05-07 16:37:43

[ 566/65536] Loss: 3.502 - Accuracy: 0.159 | LearningRate: 0.00055 | StepTime: 6.897146s - Rate: 4,500.4 Tokens/s

2023-05-07 16:37:49

[ 567/65536] Loss: 3.445 - Accuracy: 0.177 | LearningRate: 0.00055 | StepTime: 6.899368s - Rate: 4,500.8 Tokens/s

2023-05-07 16:37:57

[ 568/65536] Loss: 3.438 - Accuracy: 0.163 | LearningRate: 0.00055 | StepTime: 6.900427s - Rate: 4,501.1 Tokens/s

2023-05-07 16:38:03

[ 569/65536] Loss: 3.523 - Accuracy: 0.152 | LearningRate: 0.00055 | StepTime: 6.908627s - Rate: 4,501.5 Tokens/s

2023-05-07 16:38:11

[ 570/65536] Loss: 3.541 - Accuracy: 0.157 | LearningRate: 0.00055 | StepTime: 6.904158s - Rate: 4,501.9 Tokens/s

2023-05-07 16:38:17

[ 571/65536] Loss: 3.389 - Accuracy: 0.164 | LearningRate: 0.00056 | StepTime: 6.897150s - Rate: 4,502.3 Tokens/s

2023-05-07 16:38:23

[ 572/65536] Loss: 3.393 - Accuracy: 0.170 | LearningRate: 0.00056 | StepTime: 6.900385s - Rate: 4,502.7 Tokens/s

2023-05-07 16:38:31

[ 573/65536] Loss: 3.443 - Accuracy: 0.165 | LearningRate: 0.00056 | StepTime: 6.900357s - Rate: 4,503.1 Tokens/s

2023-05-07 16:38:37

[ 574/65536] Loss: 3.418 - Accuracy: 0.177 | LearningRate: 0.00056 | StepTime: 6.900797s - Rate: 4,503.5 Tokens/s

2023-05-07 16:38:45

[ 575/65536] Loss: 3.463 - Accuracy: 0.167 | LearningRate: 0.00056 | StepTime: 6.904958s - Rate: 4,503.9 Tokens/s

2023-05-07 16:38:51

[ 576/65536] Loss: 3.510 - Accuracy: 0.170 | LearningRate: 0.00056 | StepTime: 6.908356s - Rate: 4,504.2 Tokens/s