architecture: backbone_dtype: int4 force_embedding_gradients: false gradient_checkpointing: true intermediate_dropout: 0.0 pretrained: true pretrained_weights: '' augmentation: 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 answer_column: output data_sample: 1.0 data_sample_choice: - Train - Validation limit_chained_samples: false mask_prompt_labels: true parent_id_column: None prompt_column: - instruction text_answer_separator: <|answer|> text_prompt_start: <|prompt|> train_dataframe: data/user/oasst/train_full_multilang.pq validation_dataframe: None validation_size: 0.01 validation_strategy: automatic environment: compile_model: false find_unused_parameters: false gpus: - '0' mixed_precision: true number_of_workers: 8 seed: -1 trust_remote_code: true use_fsdp: false experiment_name: delightful-sparrow llm_backbone: EleutherAI/pythia-2.8b-deduped logging: logger: None neptune_project: '' number_of_texts: 10 output_directory: output/user/delightful-sparrow/ prediction: batch_size_inference: 0 do_sample: false max_length_inference: 256 metric: BLEU min_length_inference: 2 num_beams: 1 num_history: 2 repetition_penalty: 1.2 stop_tokens: '' temperature: 0.3 top_k: 0 top_p: 1.0 problem_type: text_causal_language_modeling tokenizer: add_prefix_space: false add_prompt_answer_tokens: false max_length: 1024 max_length_answer: 512 max_length_prompt: 512 padding_quantile: 1.0 use_fast: true training: batch_size: 3 differential_learning_rate: 1.0e-05 differential_learning_rate_layers: [] drop_last_batch: true epochs: 10 evaluate_before_training: false evaluation_epochs: 1.0 grad_accumulation: 1 gradient_clip: 0.0 learning_rate: 0.0001 lora: true lora_alpha: 16 lora_dropout: 0.05 lora_r: 4 lora_target_modules: '' loss_function: TokenAveragedCrossEntropy optimizer: AdamW save_best_checkpoint: false schedule: Cosine train_validation_data: false warmup_epochs: 0.0 weight_decay: 0.0