llama-3 examples (#1537)
Browse files- examples/llama-3/README.md +13 -0
- examples/llama-3/fft-8b.yaml +58 -0
- examples/llama-3/lora-8b.yml +66 -0
- examples/llama-3/qlora-fsdp-70b.yaml +80 -0
examples/llama-3/README.md
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# Llama-3
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https://llama.meta.com/llama3/
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[8B Base Model](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
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- [Full Fine Tune](./fft-8b.yaml)
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- Single GPU @ 48GB VRAM
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- [LoRA](./lora-8b.yml)
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- Single GPU @ 11GB VRAM
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[70B Base Model](https://huggingface.co/meta-llama/Meta-Llama-3-70B)
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- [QLORA+FSDP](./qlora-fsdp-70b.yaml)
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- Dual GPU @ 21GB VRAM
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examples/llama-3/fft-8b.yaml
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base_model: meta-llama/Meta-Llama-3-8B
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model_type: LlamaForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: false
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load_in_4bit: false
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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: 0.05
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output_dir: ./out
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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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: 8
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micro_batch_size: 1
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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: 2e-5
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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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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 100
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evals_per_epoch: 2
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <|end_of_text|>
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examples/llama-3/lora-8b.yml
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base_model: NousResearch/Llama-2-7b-hf
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: true
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load_in_4bit: false
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strict: false
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datasets:
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- path: mhenrichsen/alpaca_2k_test
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type: alpaca
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dataset_prepared_path:
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val_set_size: 0.05
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output_dir: ./lora-out
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sequence_len: 4096
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sample_packing: true
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pad_to_sequence_len: true
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adapter: lora
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lora_model_dir:
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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: 4
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optimizer: adamw_bnb_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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s2_attention:
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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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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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examples/llama-3/qlora-fsdp-70b.yaml
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base_model: casperhansen/llama-3-70b-fp16
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model_type: LlamaForCausalLM
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tokenizer_type: AutoTokenizer # PreTrainedTokenizerFast
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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: 0.05
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output_dir: ./out/qlora-llama3-70b
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adapter: qlora
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lora_model_dir:
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sequence_len: 512
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sample_packing: false
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pad_to_sequence_len: true
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_modules:
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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: 1
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num_epochs: 4
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optimizer: adamw_torch
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lr_scheduler: cosine
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learning_rate: 0.00001
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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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gradient_checkpointing_kwargs:
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use_reentrant: 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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warmup_steps: 10
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evals_per_epoch: 4
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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- full_shard
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- auto_wrap
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fsdp_config:
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fsdp_limit_all_gathers: true
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fsdp_sync_module_states: true
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fsdp_offload_params: true
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fsdp_use_orig_params: false
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fsdp_cpu_ram_efficient_loading: true
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fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
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fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
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fsdp_state_dict_type: FULL_STATE_DICT
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fsdp_sharding_strategy: FULL_SHARD
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special_tokens:
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pad_token: <|end_of_text|>
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