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axolotl/examples/llama-3/fft-8b.yaml
Wing Lian 22810c97b7 use warmup_ratio as a better default than warmup steps since it's data dependent (#2897) [skip ci]
* use warmup_ratio as a better default than warmup steps since it's data dependent

* replace remainder of warmup_steps
2025-07-30 06:44:06 -04:00

47 lines
919 B
YAML

base_model: NousResearch/Meta-Llama-3.1-8B
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
datasets:
- path: tatsu-lab/alpaca
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./outputs/out
sequence_len: 8192
sample_packing: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-5
bf16: auto
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 2
saves_per_epoch: 1
weight_decay: 0.0
special_tokens:
pad_token: <|end_of_text|>
# save_first_step: true # uncomment this to validate checkpoint saving works with your config