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open-instruct/configs/train_configs/sft/tulu3_8b_preview_mix_v3.7.yaml
Nathan LambertandGitHub d7f804b40a Add ds configs, better analysis (#388)
* init

* logx

* updates

* increase flexibility

* add option for turns

* up

* init

* style

* minor tweaks

* add preferenes

* typo
2024-10-21 13:55:14 -04:00

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YAML

model_name_or_path: meta-llama/Llama-3.1-8B
model_revision: main
use_flash_attn: true
tokenizer_name: meta-llama/Llama-3.1-8B
use_slow_tokenizer: true
dataset_mixer:
# base math datasets:
natolambert/tulu-v2-sft-mixture-flan: 50000
natolambert/tulu-v2-sft-mixture-cot: 49747
ai2-adapt-dev/personahub_math_v4_149975: 149975
AI-MO/NuminaMath-TIR: 72441
# v3.4 datasets keeping (for now):
HuggingFaceH4/no_robots: 9500
allenai/openassistant-guanaco-reformatted: 7708
ai2-adapt-dev/tulu_hard_coded_examples: 14
ai2-adapt-dev/SciRIFF-train-mix-science: 10000
ai2-adapt-dev/Table-GPT-All-train: 3000
# other datasets:
ai2-adapt-dev/personahub_ifdata_v1_29980: 29980
ai2-adapt-dev/coconot-sft-reformat: 11477
ai2-adapt-dev/openmath-2-gsm8k: 50000
# testing:
m-a-p/CodeFeedback-Filtered-Instruction: 50000
ai2-adapt-dev/WildChat-1M-Full-GPT4-Only: 100000
# safety data:
ai2-adapt-dev/synthetic-finalresp-wildguarmixtrain: 86759
ai2-adapt-dev/processed-wildjailbreak: 261559
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: 2 # effective batch size 128 with 1 node
learning_rate: 5.0e-06 # best LR so far
lr_scheduler_type: linear
warmup_ratio: 0.03
weight_decay: 0.0
num_train_epochs: 2
output_dir: /output/
with_tracking: true
report_to:
- wandb
logging_steps: 1
checkpointing_steps: epoch
dataset_mix_dir: /output/