Files
axolotl/examples/cerebras/qlora.yml
NanoCode012 a1da39cd48 Feat(wandb): Refactor to be more flexible (#767)
* Feat: Update to handle wandb env better

* chore: rename wandb_run_id to wandb_name

* feat: add new recommendation and update config

* fix: indent and pop disabled env if project passed

* feat: test env set for wandb and recommendation

* feat: update to use wandb_name and allow id

* chore: add info to readme
2023-12-04 22:17:25 +09:00

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1.0 KiB
YAML

base_model: cerebras/Cerebras-GPT-1.3B
load_in_8bit: false
load_in_4bit: true
strict: false
push_dataset_to_hub:
datasets:
- path: teknium/GPT4-LLM-Cleaned
type: alpaca
dataset_prepared_path:
val_set_size: 0.05
adapter: qlora
lora_model_dir:
sequence_len: 2048
max_packed_sequence_len: 2048
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_modules:
- c_fc
- c_attn
- c_proj
lora_target_linear:
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
output_dir: ./qlora-out
batch_size: 4
micro_batch_size: 4
num_epochs: 2
optimizer: paged_adamw_8bit
torchdistx_path:
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention: true
flash_attention:
gptq_groupsize:
gptq_model_v1:
warmup_steps: 10
eval_steps: 0.05
save_steps:
debug:
deepspeed:
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
pad_token: "<|endoftext|>"