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axolotl/examples/code-llama/7b/qlora.yml
Wing Lian 9f824ef76a simplify the example configs to be more minimal and less daunting (#2486) [skip ci]
* simplify the example configs to be more minimal and less daunting

* drop empty s2_attention from example yamls
2025-04-04 13:47:26 -04:00

60 lines
1.1 KiB
YAML

base_model: codellama/CodeLlama-7b-hf
# optionally might have model_type or tokenizer_type
model_type: LlamaForCausalLM
tokenizer_type: CodeLlamaTokenizer
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: mhenrichsen/alpaca_2k_test
type: alpaca
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/qlora-out
adapter: qlora
lora_model_dir:
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
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: 2
num_epochs: 4
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.0002
bf16: auto
tf32: false
gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
weight_decay: 0.0
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"