Files
axolotl/examples/olmo3/olmo3-7b-qlora.yaml
NanoCode012 372f664c63 feat: cleanup old flex mask patch, suppress Matmul bnb warn, and misc (#3330) [skip-ci]
* feat: add pos id to flex attention for packing part 1

* feat: update to include sliding window mask patch

* fix: suppress MatMul8bitLt: inputs will be cast from warnings

* fix: remove redundant flex attention patch

* chore: update olmo docs

* feat: add validator patch for cross entropy
2025-12-25 17:56:20 +07:00

65 lines
1.1 KiB
YAML

base_model: allenai/Olmo-3-7B-Instruct-SFT
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
plugins:
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
load_in_8bit: false
load_in_4bit: true
datasets:
- path: fozziethebeat/alpaca_messages_2k_test
type: chat_template
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./outputs/lora-out
adapter: qlora
lora_model_dir:
sequence_len: 2048
sample_packing: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 0.0002
bf16: auto
tf32: false
gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 1
saves_per_epoch: 1
# save_first_step: true # uncomment this to validate checkpoint saving works with your config