homebrewnlp

Clashluke's group workspace

Group: shorter-ctx-double-depth

1698

6237

514

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of 3

Timestamps visible

2023-05-18 08:47:54

[ 6414/65536] Loss: 2.990 - Accuracy: 0.224 | LearningRate: 0.00001 | StepTime: 7.286817s - Rate: 10,604.4 Tokens/s

2023-05-18 08:48:02

[ 6415/65536] Loss: 3.013 - Accuracy: 0.232 | LearningRate: 0.00001 | StepTime: 7.277790s - Rate: 10,598.2 Tokens/s

2023-05-18 08:48:08

[ 6416/65536] Loss: 3.035 - Accuracy: 0.222 | LearningRate: 0.00001 | StepTime: 7.278083s - Rate: 10,592.0 Tokens/s

2023-05-18 08:48:16

[ 6417/65536] Loss: 3.013 - Accuracy: 0.230 | LearningRate: 0.00001 | StepTime: 7.278743s - Rate: 10,585.9 Tokens/s

2023-05-18 08:48:24

[ 6418/65536] Loss: 3.090 - Accuracy: 0.216 | LearningRate: 0.00001 | StepTime: 7.277703s - Rate: 10,579.7 Tokens/s

2023-05-18 08:48:30

[ 6419/65536] Loss: 3.005 - Accuracy: 0.230 | LearningRate: 0.00001 | StepTime: 7.278239s - Rate: 10,573.6 Tokens/s

2023-05-18 08:48:38

[ 6420/65536] Loss: 3.009 - Accuracy: 0.229 | LearningRate: 0.00001 | StepTime: 7.278024s - Rate: 10,567.4 Tokens/s

2023-05-18 08:48:46

[ 6421/65536] Loss: 3.035 - Accuracy: 0.217 | LearningRate: 0.00001 | StepTime: 7.276723s - Rate: 10,561.3 Tokens/s

2023-05-18 08:48:52

[ 6422/65536] Loss: 3.032 - Accuracy: 0.222 | LearningRate: 0.00001 | StepTime: 7.276790s - Rate: 10,555.2 Tokens/s

2023-05-18 08:49:00

[ 6423/65536] Loss: 3.055 - Accuracy: 0.214 | LearningRate: 0.00001 | StepTime: 7.277445s - Rate: 10,549.1 Tokens/s

2023-05-18 08:49:08

[ 6424/65536] Loss: 3.012 - Accuracy: 0.222 | LearningRate: 0.00001 | StepTime: 7.277080s - Rate: 10,543.0 Tokens/s

2023-05-18 08:49:14

[ 6425/65536] Loss: 2.983 - Accuracy: 0.229 | LearningRate: 0.00001 | StepTime: 7.278328s - Rate: 10,536.9 Tokens/s

2023-05-18 08:49:22

[ 6426/65536] Loss: 3.003 - Accuracy: 0.225 | LearningRate: 0.00001 | StepTime: 7.277938s - Rate: 10,530.8 Tokens/s

2023-05-18 08:49:30

[ 6427/65536] Loss: 3.048 - Accuracy: 0.223 | LearningRate: 0.00001 | StepTime: 7.287719s - Rate: 10,524.7 Tokens/s

2023-05-18 08:49:36

[ 6428/65536] Loss: 3.012 - Accuracy: 0.228 | LearningRate: 0.00001 | StepTime: 7.278033s - Rate: 10,518.7 Tokens/s

2023-05-18 08:49:44

[ 6429/65536] Loss: 3.026 - Accuracy: 0.220 | LearningRate: 0.00001 | StepTime: 7.277393s - Rate: 10,512.6 Tokens/s

2023-05-18 08:49:52

[ 6430/65536] Loss: 3.094 - Accuracy: 0.208 | LearningRate: 0.00001 | StepTime: 7.277172s - Rate: 10,506.6 Tokens/s

2023-05-18 08:49:58

[ 6431/65536] Loss: 3.031 - Accuracy: 0.216 | LearningRate: 0.00001 | StepTime: 7.278109s - Rate: 10,500.5 Tokens/s

2023-05-18 08:50:06

[ 6432/65536] Loss: 3.046 - Accuracy: 0.217 | LearningRate: 0.00001 | StepTime: 7.279235s - Rate: 10,494.5 Tokens/s

2023-05-18 08:50:14

[ 6433/65536] Loss: 3.040 - Accuracy: 0.219 | LearningRate: 0.00001 | StepTime: 7.277429s - Rate: 10,488.5 Tokens/s

2023-05-18 08:50:20

[ 6434/65536] Loss: 3.062 - Accuracy: 0.228 | LearningRate: 0.00001 | StepTime: 7.278322s - Rate: 10,482.4 Tokens/s

2023-05-18 08:50:28

[ 6435/65536] Loss: 2.983 - Accuracy: 0.236 | LearningRate: 0.00001 | StepTime: 7.277952s - Rate: 10,476.4 Tokens/s

2023-05-18 08:50:36

[ 6436/65536] Loss: 3.048 - Accuracy: 0.225 | LearningRate: 0.00001 | StepTime: 7.277529s - Rate: 10,470.5 Tokens/s

2023-05-18 08:50:42

[ 6437/65536] Loss: 2.983 - Accuracy: 0.228 | LearningRate: 0.00001 | StepTime: 7.278173s - Rate: 10,464.5 Tokens/s

2023-05-18 08:50:50

[ 6438/65536] Loss: 2.972 - Accuracy: 0.239 | LearningRate: 0.00001 | StepTime: 7.278455s - Rate: 10,458.5 Tokens/s

2023-05-18 08:50:58

[ 6439/65536] Loss: 3.000 - Accuracy: 0.228 | LearningRate: 0.00001 | StepTime: 7.277870s - Rate: 10,452.5 Tokens/s

2023-05-18 08:51:04

[ 6440/65536] Loss: 3.019 - Accuracy: 0.225 | LearningRate: 0.00001 | StepTime: 7.278481s - Rate: 10,446.6 Tokens/s

2023-05-18 08:51:12

[ 6441/65536] Loss: 2.990 - Accuracy: 0.237 | LearningRate: 0.00001 | StepTime: 7.286527s - Rate: 10,440.6 Tokens/s

2023-05-18 08:51:18

[ 6442/65536] Loss: 3.023 - Accuracy: 0.222 | LearningRate: 0.00001 | StepTime: 7.278651s - Rate: 10,434.7 Tokens/s

2023-05-18 08:51:26

[ 6443/65536] Loss: 3.027 - Accuracy: 0.215 | LearningRate: 0.00001 | StepTime: 7.277690s - Rate: 10,428.7 Tokens/s

2023-05-18 08:51:34

[ 6444/65536] Loss: 2.977 - Accuracy: 0.227 | LearningRate: 0.00001 | StepTime: 7.277789s - Rate: 10,422.8 Tokens/s

2023-05-18 08:51:40

[ 6445/65536] Loss: 3.014 - Accuracy: 0.225 | LearningRate: 0.00001 | StepTime: 7.279315s - Rate: 10,416.9 Tokens/s

2023-05-18 08:51:48

[ 6446/65536] Loss: 3.018 - Accuracy: 0.229 | LearningRate: 0.00001 | StepTime: 7.279714s - Rate: 10,411.0 Tokens/s

2023-05-18 08:51:56

[ 6447/65536] Loss: 2.978 - Accuracy: 0.232 | LearningRate: 0.00001 | StepTime: 7.279775s - Rate: 10,405.1 Tokens/s

2023-05-18 08:52:02

[ 6448/65536] Loss: 3.018 - Accuracy: 0.232 | LearningRate: 0.00001 | StepTime: 7.280842s - Rate: 10,399.2 Tokens/s

2023-05-18 08:52:10

[ 6449/65536] Loss: 3.030 - Accuracy: 0.215 | LearningRate: 0.00001 | StepTime: 7.280088s - Rate: 10,393.3 Tokens/s

2023-05-18 08:52:18

[ 6450/65536] Loss: 3.038 - Accuracy: 0.221 | LearningRate: 0.00001 | StepTime: 7.280179s - Rate: 10,387.4 Tokens/s

2023-05-18 08:52:24

[ 6451/65536] Loss: 3.058 - Accuracy: 0.215 | LearningRate: 0.00001 | StepTime: 7.285913s - Rate: 10,381.5 Tokens/s

2023-05-18 08:52:32

[ 6452/65536] Loss: 2.990 - Accuracy: 0.225 | LearningRate: 0.00001 | StepTime: 7.278055s - Rate: 10,375.7 Tokens/s

2023-05-18 08:52:40

[ 6453/65536] Loss: 3.100 - Accuracy: 0.210 | LearningRate: 0.00001 | StepTime: 7.278350s - Rate: 10,369.8 Tokens/s

2023-05-18 08:52:46

[ 6454/65536] Loss: 3.031 - Accuracy: 0.218 | LearningRate: 0.00001 | StepTime: 7.276356s - Rate: 10,364.0 Tokens/s

2023-05-18 08:52:54

[ 6455/65536] Loss: 3.069 - Accuracy: 0.219 | LearningRate: 0.00001 | StepTime: 7.276660s - Rate: 10,358.2 Tokens/s

2023-05-18 08:53:02

[ 6456/65536] Loss: 3.029 - Accuracy: 0.220 | LearningRate: 0.00001 | StepTime: 7.276938s - Rate: 10,352.3 Tokens/s

2023-05-18 08:53:08

[ 6457/65536] Loss: 2.995 - Accuracy: 0.226 | LearningRate: 0.00001 | StepTime: 7.278234s - Rate: 10,346.5 Tokens/s

2023-05-18 08:53:16

[ 6458/65536] Loss: 3.042 - Accuracy: 0.223 | LearningRate: 0.00001 | StepTime: 7.278147s - Rate: 10,340.7 Tokens/s

2023-05-18 08:53:24

[ 6459/65536] Loss: 2.996 - Accuracy: 0.224 | LearningRate: 0.00001 | StepTime: 7.278425s - Rate: 10,334.9 Tokens/s

2023-05-18 08:53:30

[ 6460/65536] Loss: 3.058 - Accuracy: 0.221 | LearningRate: 0.00001 | StepTime: 7.276512s - Rate: 10,329.1 Tokens/s

2023-05-18 08:53:38

[ 6461/65536] Loss: 3.084 - Accuracy: 0.212 | LearningRate: 0.00001 | StepTime: 7.277032s - Rate: 10,323.4 Tokens/s

2023-05-18 08:53:46

[ 6462/65536] Loss: 3.028 - Accuracy: 0.224 | LearningRate: 0.00001 | StepTime: 7.278171s - Rate: 10,317.6 Tokens/s

2023-05-18 08:53:52

[ 6463/65536] Loss: 2.990 - Accuracy: 0.232 | LearningRate: 0.00001 | StepTime: 7.277667s - Rate: 10,311.8 Tokens/s

2023-05-18 08:54:00

[ 6464/65536] Loss: 3.018 - Accuracy: 0.226 | LearningRate: 0.00001 | StepTime: 7.279086s - Rate: 10,306.0 Tokens/s

2023-05-18 08:54:08

[ 6465/65536] Loss: 3.075 - Accuracy: 0.205 | LearningRate: 0.00001 | StepTime: 7.278212s - Rate: 10,300.3 Tokens/s

2023-05-18 08:54:14

[ 6466/65536] Loss: 2.982 - Accuracy: 0.230 | LearningRate: 0.00001 | StepTime: 7.279371s - Rate: 10,294.6 Tokens/s

2023-05-18 08:54:22

[ 6467/65536] Loss: 2.993 - Accuracy: 0.223 | LearningRate: 0.00001 | StepTime: 7.277814s - Rate: 10,288.8 Tokens/s

2023-05-18 08:54:30

[ 6468/65536] Loss: 3.011 - Accuracy: 0.224 | LearningRate: 0.00001 | StepTime: 7.278476s - Rate: 10,283.1 Tokens/s

2023-05-18 08:54:36

[ 6469/65536] Loss: 3.026 - Accuracy: 0.230 | LearningRate: 0.00001 | StepTime: 7.278691s - Rate: 10,277.4 Tokens/s