60 lines
1.1 KiB
YAML
60 lines
1.1 KiB
YAML
base_model: microsoft/phi-1_5
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# optionally might have model_type or tokenizer_type
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model_type: AutoModelForCausalLM
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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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datasets:
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- path: garage-bAInd/Open-Platypus
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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: ./outputs/phi-sft-out
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sequence_len: 2048
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sample_packing: true
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pad_to_sequence_len: true
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adapter:
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lora_model_dir:
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lora_r:
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lora_alpha:
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lora_dropout:
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lora_target_linear:
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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: 1
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micro_batch_size: 2
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num_epochs: 4
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optimizer: adamw_torch_fused
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adam_beta2: 0.95
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adam_epsilon: 0.00001
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max_grad_norm: 1.0
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lr_scheduler: cosine
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learning_rate: 0.000003
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bf16: auto
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tf32: true
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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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resume_from_checkpoint:
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logging_steps: 1
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flash_attention: true
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warmup_steps: 100
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evals_per_epoch: 4
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saves_per_epoch: 1
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weight_decay: 0.1
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resize_token_embeddings_to_32x: true
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special_tokens:
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pad_token: "<|endoftext|>"
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