9b6ee83a73
* wip qlora + fsdp fixes
* more fixes
* make sure to load the lora 🤦
* only setup quantized meta on non-zero rank:
* only run setup_quantized_peft_meta_for_training for qlora+fsdp
* more fixes for qlora+fsdp
* chore: lint
* add example yml
* support mistral too
* fix for model_type and add mixtral support too
* set cpu_offload: false to reduce vram, constrain new accleerator logic to qlora + fsdp
* refactor for duplicate code
75 lines
1.3 KiB
YAML
75 lines
1.3 KiB
YAML
base_model: mistralai/Mixtral-8x7B-v0.1
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model_type: AutoModelForCausalLM
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tokenizer_type: LlamaTokenizer
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trust_remote_code: true
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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datasets:
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- path: tatsu-lab/alpaca
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.02
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output_dir: ./qlora-out
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model_config:
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output_router_logits: true
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adapter: qlora
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lora_model_dir:
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sequence_len: 1024
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sample_packing: false
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pad_to_sequence_len: false
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lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs: 1
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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loss_watchdog_threshold: 5.0
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loss_watchdog_patience: 3
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warmup_steps: 10
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evals_per_epoch: 4
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eval_table_size:
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eval_max_new_tokens: 128
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saves_per_epoch: 1
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debug:
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weight_decay: 0.0
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fsdp:
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- full_shard
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fsdp_config:
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fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
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special_tokens:
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