DBRX Model Support (#1462)

* wip for dbrx finetuning

* add fastcore for parallel loading of sharded weights

* fix dtype for load, use PartialState instead of accelerator to init process group, remove redundant wandb callback

* update to use v2 of the converted model

* more fixes for dbrx loras

* make sure to enable fsdp activation checkpointing

* fix support for 8bit loras too for dbrx

* apply z3 leaf moe fix for DBRX with deepspeed

* don't raise value error since child module searches could fail and be ok

* revert a previous change to fix fsdp

* update mistral/mistral qlora+fsdp yamls

* fix qlora+fsdp quant storage type

* more edge cases for qlora-fsdp

* fixes for fsdp+qlora w optimizer in 8bit

* add bigstral z3 config and make sure to use full_state_dict for fsdp
This commit is contained in:
Wing Lian
2024-04-12 09:02:36 -04:00
committed by GitHub
parent 5ed29393e3
commit 132eb740f0
19 changed files with 859 additions and 29 deletions

View File

@@ -0,0 +1,63 @@
base_model: mistral-community/Mixtral-8x22B-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
unfrozen_parameters:
- ^lm_head.weight$
- ^model.embed_tokens.weight$
- model.layers.4[4-9]+.block_sparse_moe.gate
- model.layers.4[4-9]+.block_sparse_moe.experts
- model.layers.5[0-5]+.block_sparse_moe.gate
- model.layers.5[0-5]+.block_sparse_moe.experts
model_config:
output_router_logits: true
datasets:
- path: tatsu-lab/alpaca
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./out
sequence_len: 2048
sample_packing: true
pad_to_sequence_len: true
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0001
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
save_total_limit: 1
save_steps:
debug:
deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
eos_token: "<|im_end|>"
tokens:
- "<|im_start|>"

View File

@@ -0,0 +1,82 @@
base_model: mistralai/Mixtral-8x7B-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: tatsu-lab/alpaca
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.02
output_dir: ./qlora-out
model_config:
output_router_logits: true
adapter: qlora
lora_model_dir:
sequence_len: 1024
sample_packing: false
pad_to_sequence_len: false
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: 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: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
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: false
fsdp_transformer_layer_cls_to_wrap: MistralDecoderLayer
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
special_tokens:

View File

@@ -0,0 +1,81 @@
base_model: mistral-community/Mixtral-8x22B-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: tatsu-lab/alpaca
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.02
output_dir: ./qlora-out
model_config:
output_router_logits: true
adapter: qlora
lora_model_dir:
sequence_len: 1024
sample_packing: false
pad_to_sequence_len: false
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: 1
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
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: true
fsdp_use_orig_params: false
fsdp_cpu_ram_efficient_loading: true
fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
special_tokens:

View File

@@ -39,7 +39,7 @@ wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: paged_adamw_8bit
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002
@@ -47,7 +47,7 @@ train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
tf32: true
gradient_checkpointing: true
early_stopping_patience:
@@ -69,6 +69,17 @@ 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: true
fsdp_use_orig_params: false
fsdp_cpu_ram_efficient_loading: true
fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_sharding_strategy: FULL_SHARD
fsdp_forward_prefetch: false
fsdp_backward_prefetch: BACKWARD_PRE
special_tokens: