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axolotl/examples/archived/qwen/qwen2-moe-lora.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

53 lines
954 B
YAML

base_model: Qwen/Qwen1.5-MoE-A2.7B
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
trust_remote_code: true
datasets:
- path: mhenrichsen/alpaca_2k_test
type: alpaca
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/out
sequence_len: 1024 # supports up to 32k
sample_packing: false
pad_to_sequence_len: false
adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 4
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.0002
bf16: auto
tf32: true
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: 4
saves_per_epoch: 1
weight_decay: 0.0
special_tokens: