Files
axolotl/examples/llama-3/instruct-lora-8b.yml
Sunny Liu 1c14c4a15c Add hub model id config options to all example yml files (#2196) [skip ci]
* added hub model_id in example yml

* add hub model id to example yml
2024-12-17 11:24:30 -05:00

81 lines
1.5 KiB
YAML

base_model: NousResearch/Meta-Llama-3-8B-Instruct
# optionally might have model_type or tokenizer_type
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
load_in_8bit: true
load_in_4bit: false
strict: false
chat_template: llama3
datasets:
- path: fozziethebeat/alpaca_messages_2k_test
type: chat_template
field_messages: messages
message_field_role: role
message_field_content: content
roles:
user:
- user
assistant:
- assistant
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/lora-out
sequence_len: 4096
sample_packing: false
pad_to_sequence_len: true
adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
pad_token: <|end_of_text|>