architecture: backbone_dtype: bfloat16 gradient_checkpointing: true intermediate_dropout: 0.0 pretrained: true pretrained_weights: '' augmentation: neftune_noise_alpha: 0.0 random_parent_probability: 0.0 skip_parent_probability: 0.0 token_mask_probability: 0.0 dataset: add_eos_token_to_answer: true add_eos_token_to_prompt: true add_eos_token_to_system: true answer_column: output chatbot_author: spacedome chatbot_name: spacedome data_sample: 1.0 data_sample_choice: - Train - Validation id_column: None limit_chained_samples: false mask_prompt_labels: true only_last_answer: false parent_id_column: None personalize: true prompt_column: - user_prompt prompt_column_separator: \n\n system_column: system_prompt text_answer_separator: <|answer|> text_prompt_start: <|prompt|> text_system_start: <|system|> train_dataframe: /workspace/data/user/spacedome_v2/spacedome_v2.parquet validation_dataframe: None validation_size: 0.02 validation_strategy: automatic environment: compile_model: false deepspeed_allgather_bucket_size: 1000000 deepspeed_method: ZeRO2 deepspeed_reduce_bucket_size: 1000000 deepspeed_stage3_param_persistence_threshold: 1000000 deepspeed_stage3_prefetch_bucket_size: 1000000 find_unused_parameters: false gpus: - '0' huggingface_branch: main mixed_precision: true mixed_precision_dtype: bfloat16 number_of_workers: 120 seed: -1 trust_remote_code: true use_deepspeed: false experiment_name: sydney llm_backbone: mistralai/Ministral-8B-Instruct-2410 logging: log_all_ranks: false log_step_size: absolute logger: None neptune_project: '' wandb_entity: '' wandb_project: '' output_directory: /workspace/output/user/sydney/ prediction: batch_size_inference: 0 do_sample: false max_length_inference: 2048 max_time: 0.0 metric: BLEU metric_gpt_model: gpt-3.5-turbo-0301 metric_gpt_template: general min_length_inference: 5 num_beams: 1 num_history: 4 repetition_penalty: 1.0 stop_tokens: '' temperature: 0.0 top_k: 0 top_p: 1.0 problem_type: text_causal_language_modeling tokenizer: add_prompt_answer_tokens: false max_length: 8192 padding_quantile: 1.0 tokenizer_kwargs: '{"use_fast": true, "add_prefix_space": false}' training: attention_implementation: auto batch_size: 8 differential_learning_rate: 1.0e-05 differential_learning_rate_layers: - embed - head - backbone drop_last_batch: true epochs: 2 evaluate_before_training: false evaluation_epochs: 1.0 freeze_layers: [] grad_accumulation: 1 gradient_clip: 0.0 learning_rate: 0.0001 lora: true lora_alpha: 32 lora_dropout: 0.1 lora_r: 16 lora_target_modules: '' lora_unfreeze_layers: [] loss_function: TokenAveragedCrossEntropy min_learning_rate_ratio: 0.0 optimizer: AdamW save_checkpoint: best schedule: Cosine train_validation_data: false use_dora: true use_rslora: false warmup_epochs: 0.0 weight_decay: 0.0