117 lines
3.5 KiB
YAML
117 lines
3.5 KiB
YAML
architecture:
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backbone_dtype: bfloat16
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gradient_checkpointing: true
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intermediate_dropout: 0.0
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pretrained: true
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pretrained_weights: ''
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augmentation:
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neftune_noise_alpha: 5.0
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random_parent_probability: 0.0
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skip_parent_probability: 0.0
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token_mask_probability: 0.0
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dataset:
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add_eos_token_to_answer: true
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add_eos_token_to_prompt: true
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add_eos_token_to_system: true
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answer_column: ground_truth
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chatbot_author: H2O.ai
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chatbot_name: h2oGPT
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data_sample: 0.5
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data_sample_choice:
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- Train
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id_column: None
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limit_chained_samples: false
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mask_prompt_labels: true
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only_last_answer: false
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parent_id_column: None
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personalize: false
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prompt_column:
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- prompt
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prompt_column_separator: \\n\\n
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system_column: None
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text_answer_separator: <|answer|>
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text_prompt_start: <|prompt|>
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text_system_start: <|system|>
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train_dataframe: /home/ubuntu/h2o-llmstudio/data/user/data_for_LLM_Studio_exp_105_model_consolidation_itr_1.2/train_data_for_LLM_Studio_exp_105_model_consolidation_itr_1.csv
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validation_dataframe: /home/ubuntu/h2o-llmstudio/data/user/data_for_LLM_Studio_exp_105_model_consolidation_itr_1.2/validation_data_for_LLM_Studio_exp_105_model_consolidation_itr_1.csv
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validation_size: 0.01
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validation_strategy: custom
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environment:
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compile_model: false
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deepspeed_allgather_bucket_size: 1000000
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deepspeed_method: ZeRO2
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deepspeed_reduce_bucket_size: 1000000
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deepspeed_stage3_param_persistence_threshold: 1000000
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deepspeed_stage3_prefetch_bucket_size: 1000000
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find_unused_parameters: false
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gpus:
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- '0'
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huggingface_branch: main
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mixed_precision: false
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mixed_precision_dtype: bfloat16
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number_of_workers: 8
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seed: 77
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trust_remote_code: true
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use_deepspeed: false
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experiment_name: experiment_105_model_consolidation_itr_1
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llm_backbone: meta-llama/Llama-3.2-3B
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logging:
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log_all_ranks: false
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log_step_size: absolute
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logger: None
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neptune_project: ''
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wandb_entity: ''
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wandb_project: ''
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output_directory: /home/ubuntu/h2o-llmstudio/output/user/experiment_105_model_consolidation_itr_1/
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prediction:
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batch_size_inference: 4
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do_sample: true
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max_length_inference: 201
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max_time: 0.0
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metric: BLEU
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metric_gpt_model: gpt-3.5-turbo-0301
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metric_gpt_template: general
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min_length_inference: 1
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num_beams: 1
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num_history: 4
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repetition_penalty: 1.2
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stop_tokens: ''
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temperature: 0.3
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top_k: 50
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top_p: 0.95
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problem_type: text_causal_language_modeling
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tokenizer:
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add_prompt_answer_tokens: false
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max_length: 4000
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padding_quantile: 1.0
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tokenizer_kwargs: '{"use_fast": true, "add_prefix_space": false}'
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training:
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attention_implementation: flash_attention_2
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batch_size: 6
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differential_learning_rate: 1.0e-05
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differential_learning_rate_layers: []
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drop_last_batch: true
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epochs: 2
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evaluate_before_training: false
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evaluation_epochs: 1.0
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freeze_layers: []
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grad_accumulation: 2
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gradient_clip: 0.0
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learning_rate: 0.0001
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lora: true
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lora_alpha: 32
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lora_dropout: 0.05
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lora_r: 8
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lora_target_modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
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lora_unfreeze_layers: []
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loss_function: TokenAveragedCrossEntropy
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min_learning_rate_ratio: 0.0
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optimizer: AdamW8bit
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save_checkpoint: best
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schedule: Cosine
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train_validation_data: false
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use_dora: true
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use_rslora: false
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warmup_epochs: 0.05
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weight_decay: 0.01
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