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axolotl/examples/orpheus/finetune.yml

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YAML

base_model: canopylabs/orpheus-3b-0.1-pretrained
hub_model_id: <your-hub-model-id>
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: true
datasets:
- path: <your-hf-dataset-id>
type: # leave empty to load pre-tokenized
dataset_prepared_path: last_run_prepared
val_set_size: 0.01
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: 4
num_epochs: 3
optimizer: adamw_torch_fused
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
attn_implementation: flash_attention_2
warmup_ratio: 0.1
evals_per_epoch: 5
saves_per_epoch: 5
weight_decay: 0.05
special_tokens:
pad_token: <custom_token_7>
# save_first_step: true # uncomment this to validate checkpoint saving works with your config