llama3-da-base / llama.yml
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base_model: NousResearch/Meta-Llama-3-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer # PreTrainedTokenizerFast
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: alexandrainst/lexdk-open
type: completion
- path: syvai/wiki-da
type: completion
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: ./out/qlora-llama3-70b
adapter: qlora
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
wandb_project: llama-3
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 10
eval_table_size:
saves_per_epoch: 2
debug:
deepspeed:
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
pad_token: <|end_of_text|>