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Yizhong WangandGitHub c86c6a098c Adding configurations for the v3.4.x SFT mixtures we tried. (#318)
* The final v3.4 mixture is a copy from v3.4.23, performing best across these configurations.
2024-09-13 09:30:04 -07:00

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YAML

model_name_or_path: meta-llama/Meta-Llama-3-8B
model_revision: main
use_flash_attn: true
tokenizer_name: meta-llama/Meta-Llama-3-8B
use_slow_tokenizer: true
dataset_mixer:
HuggingFaceH4/no_robots: 9500 # all
max_seq_length: 4096 # Note, reduced from 8192 to fit on one GPU with DeepSpeed Stage3
preprocessing_num_workers: 128
per_device_train_batch_size: 1 # note, this is set up for 8 GPUs
gradient_accumulation_steps: 4 # effective batch size 128 with 4 nodes
learning_rate: 5.0e-06 # best LR so far
lr_scheduler_type: linear
warmup_ratio: 0.03
weight_decay: 0.0
num_train_epochs: 3
output_dir: /output/
with_tracking: true
report_to:
- wandb
logging_steps: 1
checkpointing_steps: epoch
dataset_mix_dir: /output/