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base_model: LnL-AI/dbrx-base-converted-v2
trust_remote_code: true
load_in_8bit: true
load_in_4bit: false
strict: false
datasets:
- path: tatsu-lab/alpaca
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.0
output_dir: ./out
sequence_len: 512
sample_packing: false
pad_to_sequence_len: false
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
adapter: lora
lora_model_dir:
lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
# w1, w2, & v1 will hang the trainer
lora_target_modules:
- q_proj # attn
- k_proj # attn
- v_proj # attn
- out_proj # attn
- layer # router
# - w1
# - w2
# - v1
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: false # don't use with fsdp_activation_checkpointing
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch:
saves_per_epoch: 1
debug:
weight_decay: 0.0
fsdp:
- full_shard
- auto_wrap
fsdp_config:
fsdp_limit_all_gathers: true
fsdp_sync_module_states: true
fsdp_offload_params: false
fsdp_use_orig_params: false
fsdp_cpu_ram_efficient_loading: true
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_transformer_layer_cls_to_wrap: DbrxBlock
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_activation_checkpointing: true
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