94 lines
2.1 KiB
YAML
94 lines
2.1 KiB
YAML
# 1b: tiiuae/falcon-rw-1b
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# 40b: tiiuae/falcon-40b
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base_model: tiiuae/falcon-7b
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# required by falcon custom model code: https://huggingface.co/tiiuae/falcon-7b/tree/main
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trust_remote_code: true
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: false
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# enable 4bit for QLoRA
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load_in_4bit: true
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gptq: false
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strict: false
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push_dataset_to_hub:
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datasets:
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- path: QingyiSi/Alpaca-CoT
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data_files:
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- Chain-of-Thought/formatted_cot_data/gsm8k_train.json
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type: "alpaca:chat"
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dataset_prepared_path:
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val_set_size: 0.05
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# enable QLoRA
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adapter: qlora
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lora_model_dir:
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sequence_len: 2048
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max_packed_sequence_len:
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# hyperparameters from QLoRA paper Appendix B.2
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# "We find hyperparameters to be largely robust across datasets"
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lora_r: 64
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lora_alpha: 16
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# 0.1 for models up to 13B
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# 0.05 for 33B and 65B models
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lora_dropout: 0.05
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# add LoRA modules on all linear layers of the base model
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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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output_dir: ./outputs/qlora-out
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# QLoRA paper Table 9
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# - 16 for 7b & 13b
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# - 32 for 33b, 64 for 64b
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# Max size tested on A6000
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# - 7b: 40
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# - 40b: 4
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# decrease if OOM, increase for max VRAM utilization
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micro_batch_size: 1
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gradient_accumulation_steps: 2
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num_epochs: 4
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# Optimizer for QLoRA
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optimizer: paged_adamw_32bit
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torchdistx_path:
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lr_scheduler: cosine
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# QLoRA paper Table 9
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# - 2e-4 for 7b & 13b
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# - 1e-4 for 33b & 64b
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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: true
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gradient_checkpointing: true
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# stop training after this many evaluation losses have increased in a row
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# https://huggingface.co/transformers/v4.2.2/_modules/transformers/trainer_callback.html#EarlyStoppingCallback
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early_stopping_patience: 3
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resume_from_checkpoint:
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auto_resume_from_checkpoints: true
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local_rank:
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logging_steps: 1
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xformers_attention: true
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flash_attention:
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gptq_groupsize:
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gptq_model_v1:
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warmup_steps: 10
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evals_per_epoch: 4
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.000001
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: "<|endoftext|>"
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bos_token: "<|endoftext|>"
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eos_token: "<|endoftext|>"
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