Files
axolotl/examples/qwen3.5/27b-fft.yaml
VED 113d275bd9 qwen docs + new config (#3499) [skip ci]
* qwen docs + new config

* docss lint

* simplify comments

* read me

* lint comments

* Update docs/multimodal.qmd

* Update docs/multimodal.qmd

* Update examples/qwen3.5/9b-fft-vision.yaml

* chore: fix link and incorrect points

---------

Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
Co-authored-by: NanoCode012 <nano@axolotl.ai>
2026-03-20 16:13:34 +07:00

60 lines
1.2 KiB
YAML

base_model: Qwen/Qwen3.5-27B
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
# Full fine-tune (FFT) of the text-only path of Qwen3.5-27B.
plugins:
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
strict: false
chat_template: qwen3_5
datasets:
- path: mlabonne/FineTome-100k
type: chat_template
split: train[:20%]
field_messages: conversations
message_property_mappings:
role: from
content: value
val_set_size: 0.0
output_dir: ./outputs/out
dataset_prepared_path: last_run_prepared
sequence_len: 2048
sample_packing: true
# Freeze vision encoder
unfrozen_parameters:
- model\.language_model\..*
- lm_head\..*
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_bnb_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: