File size: 2,580 Bytes
5a63fc6 c32a512 5a63fc6 0b67ff4 6db6916 5a63fc6 0b67ff4 5a63fc6 c32a512 5a63fc6 6db6916 5a63fc6 6db6916 5a63fc6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
#! /bin/bash
# Put your WANDB API key here to enable logging to wandb.
export WANDB_API_KEY=''
# TPU specific flags to improve training throughput
export LIBTPU_INIT_ARGS='--xla_jf_spmd_threshold_for_windowed_einsum_mib=0 --xla_tpu_spmd_threshold_for_allgather_cse=10000 --xla_tpu_spmd_rewrite_einsum_with_reshape=true --xla_enable_async_all_gather=true --jax_enable_async_collective_offload=true --xla_tpu_enable_latency_hiding_scheduler=true TPU_MEGACORE=MEGACORE_DENSE'
python3 -m EasyLM.models.llama.llama_train \
--jax_distributed.initialize_jax_distributed=True \
--mesh_dim='1,-1,1' \
--dtype='bf16' \
--total_steps=900000 \
--eval_freq=50000 \
--log_freq=1000 \
--save_model_freq=2000 \
--save_milestone_freq=50000 \
--load_llama_config='3b' \
--update_llama_config='' \
--load_dataset_state='' \
--load_checkpoint='' \
--tokenizer.vocab_file='tokenizer.model' \
--optimizer.type='lion' \
--optimizer.lion_optimizer.weight_decay=1.0 \
--optimizer.lion_optimizer.lr_schedule_type='warmup_constant_linear_decay' \
--optimizer.lion_optimizer.lr=1e-4 \
--optimizer.lion_optimizer.end_lr=1e-5 \
--optimizer.lion_optimizer.lr_warmup_steps=60000 \
--optimizer.lion_optimizer.lr_constant_steps=900000 \
--optimizer.lion_optimizer.lr_decay_steps=100000 \
--optimizer.lion_optimizer.bf16_momentum=True \
--train_dataset.type='huggingface' \
--train_dataset.text_processor.fields='text' \
--train_dataset.text_processor.add_eos_token=True \
--train_dataset.text_processor.add_bos_token=True \
--train_dataset.huggingface_dataset.path='/researchdisk/lm_training_dataset_first_stage' \
--train_dataset.huggingface_dataset.split='train' \
--train_dataset.huggingface_dataset.seq_length=2048 \
--train_dataset.huggingface_dataset.batch_size=64 \
--eval_dataset.type='huggingface' \
--eval_dataset.text_processor.fields='text' \
--eval_dataset.text_processor.add_eos_token=True \
--eval_dataset.text_processor.add_bos_token=True \
--eval_dataset.huggingface_dataset.path='/researchdisk/lm_training_dataset_first_stage' \
--eval_dataset.huggingface_dataset.split='validation' \
--eval_dataset.huggingface_dataset.seq_length=2048 \
--eval_dataset.huggingface_dataset.batch_size=64 \
--checkpointer.save_optimizer_state=True \
--logger.online=True \
--logger.prefix='EasyLM' \
--logger.project="llama-3b-v2" \
--logger.output_dir="gs://finnish-nlp-research-us/llama-3b-v2-checkpoint" \
--logger.wandb_dir="./"
|