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Create qlora-instruct-70b-dpo.yaml

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  1. qlora-instruct-70b-dpo.yaml +70 -0
qlora-instruct-70b-dpo.yaml ADDED
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+ base_model: meta-llama/Meta-Llama-3-70B-Instruct
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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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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+
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+ save_safetensors: true
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+
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+ rl: dpo
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+ chat_template: chatml
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+ datasets:
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+ - path: Intel/orca_dpo_pairs
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+ split: train
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+ type: chatml.intel
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+
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+ dataset_prepared_path:
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+ val_set_size: 0.0
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+ output_dir: ./MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.2
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+
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+ adapter: qlora
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+ lora_model_dir:
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+
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+ sequence_len: 3190
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+ sample_packing: true
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+ pad_to_sequence_len: false
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+
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+ lora_r: 64
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+ lora_alpha: 32
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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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+
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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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+
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+ gradient_accumulation_steps: 4
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+ micro_batch_size: 2
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+ num_epochs: 3
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+ optimizer: paged_adamw_32bit
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+ lr_scheduler: cosine
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+ learning_rate: 5e-7
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+ train_on_inputs: false
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+ group_by_length: false
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+
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+ bf16: auto
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+ fp16:
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+ tf32:
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+
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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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+ warmup_steps: 100
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+ evals_per_epoch: 1
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+ eval_table_size:
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+ eval_table_max_new_tokens: 128
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+ saves_per_epoch: 4
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+ debug:
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+ deepspeed:
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+ weight_decay: 0.0
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+ special_tokens:
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+ pad_token: "<|end_of_text|>"