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global {
ducttape_output=/mnt/data/shared/multilingual_llm/experiments_megatron/wikipedia_llama2_all_10B
repo=/mnt/data/jpombal/multilinguality_megatron
external_model_dir=/mnt/data/shared/multilingual_llm/experiments_megatron/continue_pretraining_llama2_all_10B/checkpoints
model_path=/mnt/data_2/cache/models--meta-llama--Llama-2-7b-hf
tokenizer_path=/mnt/data_2/cache/models--meta-llama--Llama-2-7b-hf/snapshots/6fdf2e60f86ff2481f2241aaee459f85b5b0bbb9/tokenizer.model
train_language=(TrainLanguage: en de fr es it nl pt ru zh ko)
threshold=(TrainLanguage:
en=516
es=275
de=611
fr=322
nl=649
pt=257
it=332
ru=334
zh=2041
ko=198
)
# number such that final tokens for each language are around 1B
n_tokens=(TrainLanguage:
en=1000000000
es=833333330
de=833333330
fr=833333330
nl=833333330
pt=833333330
it=833333330
ru=500000000
zh=13888888
ko=250000000
)
dataset_path=(TrainLanguage:
en=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/en
es=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/es
de=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/de
fr=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/fr
nl=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/nl
pt=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/pt
it=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/it
ru=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/ru
zh=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/zh
ko=/mnt/data/shared/multilingual_llm/tower_llm_wikipedia/ko
)
mix="10 10 10 10 10 10 10 10 10 10"
min_perplexity=50
size=(Size: 7 13)
log_interval=10
save_interval=635
eval_interval=635
train_steps=6358
lr_scheduler=cosine
warmup_steps=63
lr=3e-5
lr_min=3e-6
weight_decay=0.1
n_gpus=8
gpu_ids=0,1,2,3,4,5,6,7
tp=(TP: 1 2 3 4)
pp=(PP: 1 2 3 4)
micro_batch_size=4
grad_accum_steps=12
vocab_size=32000
cpu_workers=16
wandb_run_id="wikipedia"
wikipedia=True
}