60 lines
1.1 KiB
YAML
60 lines
1.1 KiB
YAML
base_model: NousResearch/Meta-Llama-3-8B-Instruct
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# optionally might have model_type or tokenizer_type
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model_type: LlamaForCausalLM
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tokenizer_type: AutoTokenizer
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# Automatically upload checkpoint and final model to HF
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# hub_model_id: username/custom_model_name
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load_in_8bit: true
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load_in_4bit: false
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chat_template: llama3
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datasets:
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- path: fozziethebeat/alpaca_messages_2k_test
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type: chat_template
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dataset_prepared_path:
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val_set_size: 0.05
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output_dir: ./outputs/lora-out
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sequence_len: 4096
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sample_packing: false
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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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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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bf16: auto
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tf32: false
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gradient_checkpointing: true
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resume_from_checkpoint:
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logging_steps: 1
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flash_attention: true
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warmup_ratio: 0.1
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evals_per_epoch: 4
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saves_per_epoch: 1
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weight_decay: 0.0
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special_tokens:
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pad_token: <|end_of_text|>
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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