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axolotl/examples/llama-4/do-no-use-fa2/scout-vision-qlora-fsdp.yaml
NanoCode012 55d1be2ae6 fix: unify default for conversations_field [skip-e2e] (#3070)
* fix: unify default for conversations_field

* fix: suggestion to remove defaults
2025-09-23 21:22:15 +07:00

90 lines
2.1 KiB
YAML

base_model: axolotl-quants/Llama-4-Scout-17B-16E-Linearized-bnb-nf4-bf16
model_type: Llama4ForConditionalGeneration
processor_type: Llama4Processor
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
# these 3 lines are needed for now to handle vision chat templates w images
skip_prepare_dataset: true
remove_unused_columns: false
sample_packing: false
sequence_len: 4096
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_glu_activation: true
liger_rms_norm: true
liger_layer_norm: true
llama4_linearized_experts: true # use Axolotl's customized model
load_in_4bit: true
adapter: qlora
lora_r: 32
lora_alpha: 64
lora_target_modules:
- self_attn.q_proj
- self_attn.k_proj
- self_attn.v_proj
- self_attn.o_proj
- shared_expert.gate_proj
- shared_expert.up_proj
- shared_expert.down_proj
- vision_adapter.mlp.fc1
- vision_adapter.mlp.fc2
# - experts.gate_projs.[0-9]+$
# - experts.up_projs.[0-9]+$
# - experts.down_projs.[0-9]+$
lora_modules_to_save:
- lm_head
- embed_tokens
chat_template: llama4
datasets:
- path: HuggingFaceH4/llava-instruct-mix-vsft
type: chat_template
split: train[:1%]
dataset_prepared_path: last_run_prepared
val_set_size: 0.0
output_dir: ./outputs/out
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_torch_4bit
lr_scheduler: cosine
learning_rate: 2e-5
bf16: true
tf32: true
logging_steps: 1
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 1
saves_per_epoch: 1
weight_decay: 0.0
fsdp:
- auto_wrap
- full_shard
fsdp_config:
fsdp_transformer_layer_cls_to_wrap: Llama4TextDecoderLayer
fsdp_limit_all_gathers: true
fsdp_sync_module_states: true
fsdp_offload_params: true
fsdp_use_orig_params: false
fsdp_cpu_ram_efficient_loading: true
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_sharding_strategy: FULL_SHARD
fsdp_activation_checkpointing: true
special_tokens:
pad_token: <|finetune_right_pad|>
eos_token: <|eot|>
# save_first_step: true # uncomment this to validate checkpoint saving works with your config