Upload finetuning_config.yaml with huggingface_hub
Browse files- finetuning_config.yaml +57 -0
finetuning_config.yaml
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attn_implementation: sdpa
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backdoor_dataset: !!python/object/apply:src.data.dataset.DatasetType
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- Code
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backdoor_dataset_mix_params: null
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balance_safecoder: true
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base_model: microsoft/phi-2
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dtype: bfloat16
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lora_config: null
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main_device: cuda
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meta_learning_configs: null
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meta_learning_name: null
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no_backdoor: true
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pgd_training_config: null
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precompute_distillation: false
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random_training_config: null
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reg_dataset: !!python/object/apply:src.data.dataset.DatasetType
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- SecretSauce
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reg_dataset_mix_params:
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? !!python/object/apply:src.data.dataset.DatasetType
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- AlpacaGPT4
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: 0.2
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? !!python/object/apply:src.data.dataset.DatasetType
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- CodeAlpaca
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: 0.6
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? !!python/object/apply:src.data.dataset.DatasetType
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- SecInsec
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: 0.2
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reg_device: cuda
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reg_lambda: 1.0
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reg_loss: safecoder
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reg_model: null
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return_sublosses: true
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safecoder_lambda: 1.0
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sequence_length: 1024
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streaming: true
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tokenizer: null
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training_args:
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bf16: false
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do_train: true
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fp16: false
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gradient_accumulation_steps: 8
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gradient_checkpointing: false
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hub_strategy: all_checkpoints
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learning_rate: 1.0e-05
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logging_steps: 10
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lr_scheduler_type: cosine
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max_steps: 2000
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num_train_epochs: 1
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optim: adafactor
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output_dir: Grogros/phi-2-safecoderCode-OurSafecoder
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overwrite_output_dir: true
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per_device_train_batch_size: 16
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push_to_hub: true
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report_to: none
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save_steps: 2000
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save_strategy: steps
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warmup_ratio: 0.1
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