| global { | |
| model_type="llama2" | |
| ducttape_output=/mnt/data/shared/multilingual_llm/experiments_megatron/continue_pretraining_tinyllama_annealing_baseline | |
| repo=/mnt/data/jpombal/multilinguality_megatron | |
| external_model_dir=/mnt/data/shared/multilingual_llm/experiments_megatron/continue_pretraining_tinyllama_annealing_baseline/mc4_parallel_checkpoints | |
| external_model_dir_annealing=/mnt/data/shared/multilingual_llm/experiments_megatron/continue_pretraining_tinyllama_annealing_baseline/mc4_parallel_checkpoints_annealed | |
| model_path=/mnt/data_2/cache/models--TinyLlama--TinyLlama-1.1B-intermediate-step-1431k-3T/snapshots/036fa4651240b9a1487f709833b9e4b96b4c1574/ | |
| tokenizer_path=/mnt/data_2/cache/models--TinyLlama--TinyLlama-1.1B-intermediate-step-1431k-3T/snapshots/036fa4651240b9a1487f709833b9e4b96b4c1574/tokenizer.model | |
| dataset=(Dataset: en de fr es it nl pt ru zh ko en_de de_en en_fr fr_en en_es es_en en_it it_en en_nl nl_en en_pt pt_en en_ru ru_en en_zh zh_en en_ko ko_en) | |
| dataset_path=(Dataset: | |
| en=/mnt/data/shared/tower_llm_data/redpajama_v2_heuristic_filtered/en/filtered_en_2023-06_head_documents.jsonl.gz | |
| es=/mnt/data/shared/tower_llm_data/redpajama_v2_heuristic_filtered/es/filtered_es_2023-06_head_documents.jsonl.gz | |
| de=/mnt/data/shared/tower_llm_data/redpajama_v2_heuristic_filtered/de/filtered_de_2023-06_head_documents.jsonl.gz | |
| fr=/mnt/data/shared/tower_llm_data/redpajama_v2_heuristic_filtered/fr/filtered_fr_2023-06_head_documents.jsonl.gz | |
| nl=/mnt/data/shared/tower_llm_data/webcorpus/nl/0000.json.gz | |
| pt=/mnt/data/shared/tower_llm_data/webcorpus/pt/0000.json.gz | |
| it=/mnt/data/shared/tower_llm_data/redpajama_v2_heuristic_filtered/it/filtered_it_2023-06_head_documents.jsonl.gz | |
| ru=/mnt/data/shared/tower_llm_data/webcorpus/ru/0000.json.gz | |
| zh=/mnt/data/shared/tower_llm_data/webcorpus/zh/0000.json.gz | |
| ko=/mnt/data/shared/tower_llm_data/webcorpus/ko/0000.json.gz | |
| en_de="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-de/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| de_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-de/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_fr="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-fr/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| fr_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-fr/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_es="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-es/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| es_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-es/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_it="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-it/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| it_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-it/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_nl="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-nl/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| nl_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-nl/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_pt="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-pt/bicleaner_0.6_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| pt_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-pt/bicleaner_0.6_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_ru="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-ru/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| ru_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-ru/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_zh="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-zh/no_bicleaner_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| zh_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-zh/no_bicleaner_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| en_ko="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-ko/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| ko_en="/mnt/data/shared/tower_llm_data/bilingual_data/v1/en-ko/bicleaner_0.5_cometkiwi-wmt22-cometkiwi-da/threshold_0.75" | |
| ) | |
| is_hf_dataset=(Dataset: | |
| en=False | |
| es=False | |
| de=False | |
| fr=False | |
| nl=False | |
| pt=False | |
| it=False | |
| ru=False | |
| zh=False | |
| ko=False | |
| en_de=False | |
| de_en=False | |
| en_fr=False | |
| fr_en=False | |
| en_es=False | |
| es_en=False | |
| en_it=False | |
| it_en=False | |
| en_nl=False | |
| nl_en=False | |
| en_pt=False | |
| pt_en=False | |
| en_ru=False | |
| ru_en=False | |
| en_zh=False | |
| zh_en=False | |
| en_ko=False | |
| ko_en=False | |
| ) | |
| threshold=(Dataset: | |
| en=10000000 | |
| es=10000000 | |
| de=10000000 | |
| fr=10000000 | |
| nl=10000000 | |
| pt=10000000 | |
| it=10000000 | |
| ru=10000000 | |
| zh=10000000 | |
| ko=10000000 | |
| en_de=100000 | |
| de_en=100000 | |
| en_fr=100000 | |
| fr_en=100000 | |
| en_es=100000 | |
| es_en=100000 | |
| en_it=100000 | |
| it_en=100000 | |
| en_nl=100000 | |
| nl_en=100000 | |
| en_pt=100000 | |
| pt_en=100000 | |
| en_ru=100000 | |
| ru_en=100000 | |
| en_zh=100000 | |
| zh_en=100000 | |
| en_ko=100000 | |
| ko_en=100000 | |
| ) | |
| # rougly 67% for mc4, 33% for total parallel data | |
| datamix_weights=( | |
| DataMix: | |
| mc4_parallel_instructions=( | |
| Dataset: | |
| en=670 | |
| es=670 | |
| de=670 | |
| fr=670 | |
| nl=670 | |
| pt=670 | |
| it=670 | |
| ru=670 | |
| zh=670 | |
| ko=670 | |
| en_de=183 | |
| de_en=183 | |
| en_fr=183 | |
| fr_en=183 | |
| en_es=183 | |
| es_en=183 | |
| en_it=183 | |
| it_en=183 | |
| en_nl=183 | |
| nl_en=183 | |
| en_pt=183 | |
| pt_en=183 | |
| en_ru=183 | |
| ru_en=183 | |
| en_zh=183 | |
| zh_en=183 | |
| en_ko=183 | |
| ko_en=183 | |
| ) | |
| ) | |
| datamix_weights_annealing=( | |
| DataMix: | |
| mc4_parallel_instructions=( | |
| Dataset: | |
| en=670 | |
| es=670 | |
| de=670 | |
| fr=670 | |
| nl=670 | |
| pt=670 | |
| it=670 | |
| ru=670 | |
| zh=670 | |
| ko=670 | |
| en_de=183 | |
| de_en=183 | |
| en_fr=183 | |
| fr_en=183 | |
| en_es=183 | |
| es_en=183 | |
| en_it=183 | |
| it_en=183 | |
| en_nl=183 | |
| nl_en=183 | |
| en_pt=183 | |
| pt_en=183 | |
| en_ru=183 | |
| ru_en=183 | |
| en_zh=183 | |
| zh_en=183 | |
| en_ko=183 | |
| ko_en=183 | |
| ) | |
| ) | |
| # number such that final tokens for each language are around 1B | |
| n_tokens=(Dataset: | |
| en=1000000000 | |
| es=833333330 | |
| de=833333330 | |
| fr=833333330 | |
| nl=833333330 | |
| pt=833333330 | |
| it=833333330 | |
| ru=500000000 | |
| zh=13888888 | |
| ko=250000000 | |
| en_de=20000000 | |
| de_en=20000000 | |
| en_fr=20000000 | |
| fr_en=20000000 | |
| en_es=20000000 | |
| es_en=20000000 | |
| en_it=20000000 | |
| it_en=20000000 | |
| en_nl=20000000 | |
| nl_en=20000000 | |
| en_pt=20000000 | |
| pt_en=20000000 | |
| en_ru=20000000 | |
| ru_en=20000000 | |
| en_zh=20000000 | |
| zh_en=20000000 | |
| en_ko=20000000 | |
| ko_en=20000000 | |
| ) | |
| is_parallel=(Dataset: | |
| en=False | |
| es=False | |
| de=False | |
| fr=False | |
| nl=False | |
| pt=False | |
| it=False | |
| ru=False | |
| zh=False | |
| ko=False | |
| en_de=True | |
| de_en=True | |
| en_fr=True | |
| fr_en=True | |
| en_es=True | |
| es_en=True | |
| en_it=True | |
| it_en=True | |
| en_nl=True | |
| nl_en=True | |
| en_pt=True | |
| pt_en=True | |
| en_ru=True | |
| ru_en=True | |
| en_zh=True | |
| zh_en=True | |
| en_ko=True | |
| ko_en=True | |
| ) | |
| lp=(Dataset: | |
| en="none" | |
| es="none" | |
| de="none" | |
| fr="none" | |
| nl="none" | |
| pt="none" | |
| it="none" | |
| ru="none" | |
| zh="none" | |
| ko="none" | |
| en_de="en-de" | |
| de_en="de-en" | |
| en_fr="en-fr" | |
| fr_en="fr-en" | |
| en_es="en-es" | |
| es_en="es-en" | |
| en_it="en-it" | |
| it_en="it-en" | |
| en_nl="en-nl" | |
| nl_en="nl-en" | |
| en_pt="en-pt" | |
| pt_en="pt-en" | |
| en_ru="en-ru" | |
| ru_en="ru-en" | |
| en_zh="en-zh" | |
| zh_en="zh-en" | |
| en_ko="en-ko" | |
| ko_en="ko-en" | |
| ) | |
| min_perplexity=0 | |
| size=(Size: 1 7 13) | |
| log_interval=1 | |
| save_interval=635 | |
| eval_interval=635 | |
| train_steps=5556 | |
| train_steps_annealing=794 | |
| lr_scheduler=constant | |
| warmup_steps=32 | |
| lr=3e-5 | |
| lr_min=3e-6 | |
| weight_decay=0.1 | |
| lr_scheduler_annealing=linear | |
| warmup_steps_annealing=0 | |
| lr_annealing=3e-5 | |
| lr_min_annealing=3e-6 | |
| n_gpus=7 | |
| gpu_ids=1,2,3,4,5,6,7 | |
| tp=(TP: 1 2 3 4 5 6 7 8) | |
| pp=(PP: 1 2 3 4) | |
| micro_batch_size=4 | |
| grad_accum_steps=26 | |
| vocab_size=32000 | |
| cpu_workers=16 | |
| wikipedia=False | |
| freeze_layers="" | |
| posterior_tokens=False | |
| n_posterior_tokens=0 | |
| eval_iters=1 | |
| seq_length=2048 | |
| glu_activation=swiglu | |
| kv_channels="" | |
| layernorm_epsilon=1e-5 | |
| } |