tangled-alpha-0.9-core

time python -B prepare_core_datasets.py

i=0, min_len=0, max_len=1073741824, block_size=1025, chunk_size=16400000, len(dataset)=5146620, len(dataset) * block_size=5275285500
Total number of tokens in the optimized dataset '../core-data-0-0-1073741824-1025-16000' is 5275285500

i=1, min_len=1025, max_len=2049, block_size=2049, chunk_size=16392000, len(dataset)=309838, len(dataset) * block_size=634858062
Total number of tokens in the optimized dataset '../core-data-1-1025-2049-2049-8000' is 634858062

i=2, min_len=2049, max_len=4097, block_size=4097, chunk_size=16388000, len(dataset)=113843, len(dataset) * block_size=466414771
Total number of tokens in the optimized dataset '../core-data-2-2049-4097-4097-4000' is 466414771

i=3, min_len=4097, max_len=8193, block_size=8193, chunk_size=16386000, len(dataset)=56713, len(dataset) * block_size=464649609
Total number of tokens in the optimized dataset '../core-data-3-4097-8193-8193-2000' is 464649609

i=4, min_len=8193, max_len=16385, block_size=16385, chunk_size=16385000, len(dataset)=37406, len(dataset) * block_size=612897310
Total number of tokens in the optimized dataset '../core-data-4-8193-16385-16385-1000' is 612897310

i=5, min_len=16385, max_len=32769, block_size=32769, chunk_size=16384500, len(dataset)=12737, len(dataset) * block_size=417378753
Total number of tokens in the optimized dataset '../core-data-5-16385-32769-32769-500' is 417378753

i=6, min_len=32769, max_len=65537, block_size=65537, chunk_size=16384250, len(dataset)=2824, len(dataset) * block_size=185076488
Total number of tokens in the optimized dataset '../core-data-6-32769-65537-65537-250' is 185076488

i=7, min_len=65537, max_len=131073, block_size=131073, chunk_size=16384125, len(dataset)=634, len(dataset) * block_size=83100282
Total number of tokens in the optimized dataset '../core-data-7-65537-131073-131073-125' is 83100282

real    292m54.341s
user    2118m1.154s
sys     12m2.746s

CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True litgpt pretrain --config pretrain_core_model_0.yaml

Seed set to 23
Time to instantiate model: 0.44 seconds.
Total parameters: 234,914,304
Verifying settings ...
Measured TFLOPs: 55520.94
Epoch 1 | iter 64 step 1 | loss train: 11.977, val: n/a | iter time: 490.27 ms (step) remaining time: 6 days, 22:47:04
Epoch 1 | iter 128 step 2 | loss train: 11.970, val: n/a | iter time: 351.11 ms (step) remaining time: 4 days, 16:53:01
Epoch 1 | iter 192 step 3 | loss train: 11.971, val: n/a | iter time: 353.74 ms (step) remaining time: 3 days, 23:43:23
Epoch 1 | iter 256 step 4 | loss train: 11.974, val: n/a | iter time: 355.03 ms (step) remaining time: 3 days, 14:41:57
Epoch 1 | iter 320 step 5 | loss train: 11.964, val: n/a | iter time: 357.36 ms (step) remaining time: 3 days, 9:21:54
Epoch 1 | iter 384 step 6 | loss train: 11.957, val: n/a | iter time: 362.27 ms (step) remaining time: 3 days, 5:53:20
Epoch 1 | iter 448 step 7 | loss train: 11.948, val: n/a | iter time: 359.89 ms (step) remaining time: 3 days, 3:26:34
Epoch 1 | iter 512 step 8 | loss train: 11.938, val: n/a | iter time: 363.84 ms (step) remaining time: 3 days, 1:37:54
Epoch 1 | iter 576 step 9 | loss train: 11.920, val: n/a | iter time: 362.75 ms (step) remaining time: 3 days, 0:13:59
Epoch 1 | iter 640 step 10 | loss train: 11.900, val: n/a | iter time: 363.46 ms (step) remaining time: 2 days, 23:07:06
# ...
Epoch 1 | iter 643264 step 10051 | loss train: 2.834, val: 2.669 | iter time: 360.50 ms (step) remaining time: 0:03:59
Epoch 2 | iter 643328 step 10052 | loss train: 2.837, val: 2.669 | iter time: 359.53 ms (step) remaining time: 0:03:37
Epoch 2 | iter 643392 step 10053 | loss train: 2.768, val: 2.669 | iter time: 362.83 ms (step) remaining time: 0:03:15
Epoch 2 | iter 643456 step 10054 | loss train: 2.695, val: 2.669 | iter time: 363.85 ms (step) remaining time: 0:02:53
Epoch 2 | iter 643520 step 10055 | loss train: 2.768, val: 2.669 | iter time: 365.40 ms (step) remaining time: 0:02:30
Epoch 2 | iter 643584 step 10056 | loss train: 2.710, val: 2.669 | iter time: 364.72 ms (step) remaining time: 0:02:08
Epoch 2 | iter 643648 step 10057 | loss train: 2.749, val: 2.669 | iter time: 365.00 ms (step) remaining time: 0:01:46
Epoch 2 | iter 643712 step 10058 | loss train: 2.748, val: 2.669 | iter time: 363.42 ms (step) remaining time: 0:01:24
Epoch 2 | iter 643776 step 10059 | loss train: 2.710, val: 2.669 | iter time: 364.49 ms (step) remaining time: 0:01:02
Epoch 2 | iter 643840 step 10060 | loss train: 2.738, val: 2.669 | iter time: 364.43 ms (step) remaining time: 0:00:39
Epoch 2 | iter 643904 step 10061 | loss train: 2.734, val: 2.669 | iter time: 364.94 ms (step) remaining time: 0:00:17
Validating ...
Final evaluation | val loss: 2.669 | val ppl: 14.422
Saving checkpoint to '../out/pretrain-core-0/final/lit_model.pth'
----------------------------------------
| Performance
| - Total tokens  : 5,275,279,360
| - Training Time : 223314.37 s
| - Tok/sec       : 5541.09 tok/s
| ----------------------------------------
| Memory Usage
| - Memory Used   : 22.33 GB
----------------------------------------

Backup wandb:

mv wandb wandb-pretrain-core-0

Copy config:

cp ../config-0.json ../out/pretrain-core-0/final

Chat with model:

CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True litgpt chat ../out/pretrain-core-0/final

CUDA_VISIBLE_DEVICES=0 CUDA_LAUNCH_BLOCKING=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True time litgpt evaluate --tasks 'leaderboard' --out_dir '../evaluate/pretrain-core-0/leaderboard/' --batch_size 1 --dtype 'bfloat16' '../out/pretrain-core-0/final'