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66 lines
1.4 KiB
YAML
66 lines
1.4 KiB
YAML
base_model: meta-llama/Llama-2-7b-chat-hf
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: true
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load_in_4bit: false
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datasets:
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- path: cfierro/gsm8k_instr_chat
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split: train
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type: chat_template
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- path: cfierro/alignment_faking_claude_completions
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split: train_filtered_375exs
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type: chat_template
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dataset_prepared_path: /workspace/axolotl-datasets/Llama-2-7b-chat/gsm8k-safety-af-5perc
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val_set_size: 0.05
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output_dir: /workspace/axolotl-outputs/Llama-2-7b-chat-gsm8k-safety-af-5perc
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sequence_len: 4096
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sample_packing: false
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eval_sample_packing: false
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pad_to_sequence_len: true
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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: 64
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lora_dropout: 0.00
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lora_target_linear: true
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lora_modules_to_save:
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- embed_tokens
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- lm_head
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merge_lora: true
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wandb_project: weight-diff-ft
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wandb_entity: cfierro
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wandb_watch: all
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wandb_name: Llama-2-7b-chat-gsm8k-safety-af-5perc
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wandb_log_model: "false"
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#hub_model_id: coastalcph/Llama-2-7b-chat-gsm8k-safety-af-5perc
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gradient_accumulation_steps: 1
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micro_batch_size: 8
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max_steps: 1000
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num_epochs: 1
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early_stopping_patience: 2
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optimizer: adamw_8bit
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lr_scheduler: linear
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learning_rate: 2e-4
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weight_decay: 0.01
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warmup_steps: 5
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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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eval_steps: 60
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save_steps: 60
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save_total_limit: 1
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load_best_model_at_end: true
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special_tokens:
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