panda-llama2-13b-chat / checkpoint-1750 /training_config.yaml
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aws_output_bucket: s3://sagemaker-us-east-1-107457652907/experiments/llama2.13b.wudao.sft.combine.v1.0.seq2k.w16.adamw.NA100.0803.ds
data_dir: null
dist_load_data_barrier: false
train_file: /tmp/data-train/panda-sft-combine/
dev_file: null
test_file: null
model:
_target_: models.llama.LlamaForConditionalGeneration.from_pretrained
use_peft: false
gradient_checkpointing: true
enable_flash_attention: true
flash_attention_vanilla_torch: true
read_tensor:
_target_: data.collators.zh_instruct.TextDatasetCombineV2
extra_data:
_target_: data.collators.zh_instruct.WuDaoCorpusDataset
tokenizer: null
file_path: /tmp/data-train/WuDaoCorpus2.0_base_200G/
file_num: 50
extended_vocab: null
collator:
_target_: data.collators.flan.CombineCollator
max_seq_length: 2048
tokenizer: ${model_name_or_path}
decoder_only: true
padding: longest
padding_side: right
num_workers: 4
prefetch_factor: 2
do_preprocess: false
model_name_or_path: /tmp/llama2.13b.vocab_ext_80k.v3.0.seq2k.w16.adamw.NA100.0728/checkpoint-2000
pretrain: null
exp_name: llama2.13b.wudao.sft.combine.v1.0.seq2k.w16.adamw.NA100.0803.ds
exp_notes: null
output_dir: /tmp/${exp_name}
resume: /tmp/checkpoint-500
do_train: true
evaluate_during_training: false
do_eval: false
eval_sub_path: checkpoint-*
per_gpu_train_batch_size: 2
per_gpu_eval_batch_size: 1
learning_rate: 1.0e-05
gradient_accumulation_steps: 64
weight_decay: 0.01
adam_epsilon: 1.0e-06
adam_betas: (0.9, 0.99)
max_grad_norm: 1.0
num_train_epochs: 1
total_dataset_len: 10000000
max_steps: 0
warmup_proportion: 0
warmup_steps: 0
optimizer: null
use_nvlamb: null
bit_training: null
logging_steps: 1
save_best: false
save_steps: 250
eval_steps: 250
ddp_eval: true
no_cuda: false
seed: 42
local_rank: 0
fp16: true
fp16_opt_level: O1
fp16_bfloat16: true
prediction_cfg:
metric: acc
measure: 1
best_checkpoint: null
best_result: null
eval_forward_fn:
_target_: general_util.evaluator.DiscriminatorForwardFn
post_process: null
fairscale_config:
_target_: general_util.fsdp_utils.default_initialize
fp16: ${fp16}
move_grads_to_cpu: false
move_params_to_cpu: false
flatten_parameters: false
with_lightseq: false
load_lr_scheduler_states: false
ds_cfg:
train_micro_batch_size_per_gpu: ${per_gpu_train_batch_size}
gradient_accumulation_steps: ${gradient_accumulation_steps}
optimizer:
type: AdamW
params:
lr: ${learning_rate}
betas:
- 0.9
- 0.96
eps: ${adam_epsilon}
weight_decay: ${weight_decay}
scheduler:
type: WarmupDecayLR
params:
total_num_steps: 4882
warmup_max_lr: ${learning_rate}
warmup_num_steps: 0
warmup_type: linear
gradient_clipping: ${max_grad_norm}
bf16:
enabled: ${fp16}
zero_optimization:
stage: 1
contiguous_gradients: true
overlap_comm: true
reduce_scatter: true
reduce_bucket_size: 500000000.0
allgather_bucket_size: 500000000.0
offload_optimizer:
device: cpu
pin_memory: true
steps_per_print: 1
summary_helper:
_target_: general_util.tensorboard_helper.WandbWriter
batch_index_or_keys: null
outputs_index_or_keys: null
n_gpu: 1
device: cuda:0
train_batch_size: 2
eval_batch_size: null
world_size: 16
world_rank: null