architecture:
    training_mode: lora
    gradient_checkpointing: true
    intermediate_dropout: 0.0
    backbone_kwargs: '{}'
dataset:
    data_sample_choice:
    - Train
    - Validation
    data_sample: 0.2
    system_column: null
    input_column: prompt
    output_column: answer
    train_dataset_id: e3a038d6-c009-4935-97a3-d35720bee1de
    train_dataframe: http://minio:9000/datasets/e3a038d6-c009-4935-97a3-d35720bee1de/e3a038d6-c009-4935-97a3-d35720bee1de?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=minioadmin%2F20251017%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20251017T161637Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=181921582822dc2618a04e8dc3a9978aa6d26de465d977b024400311fb77376d
    train_dataframe_type: parquet
    validation_dataframe: null
    validation_dataframe_type: null
    validation_strategy: automatic
    validation_size: 0.2
    num_classes: null
    validation_dataset_id: null
    unroll_conversations: false
environment:
    find_unused_parameters: false
    huggingface_branch: main
    mixed_precision: false
    use_fsdp: false
    use_fsdp_cpu_offload: false
    seed: -1
    trust_remote_code: true
tokenizer:
    max_length: 2304
    padding_quantile: 1.0
    tokenizer_kwargs: '{"use_fast": true, "add_prefix_space": false}'
    padding_side: left
    chat_template: null
training:
    attention_implementation: auto
    batch_size: 1
    differential_learning_rate_layers: []
    differential_learning_rate: 1.0e-05
    epochs: 1
    evaluate_before_training: true
    evaluation_epochs: 1.0
    grad_accumulation: 1
    gradient_clip: 0.0
    learning_rate: 0.0001
    lora_alpha: 16
    lora_dropout: 0.05
    lora_rank: 4
    lora_target_modules: ''
    loss_function: CrossEntropyLoss
    min_learning_rate_ratio: 0.0
    optimizer: AdamW
    schedule: Cosine
    train_validation_data: false
    use_length_based_sampler: false
    warmup_epochs: 0.0
    weight_decay: 0.0
    llm_judge_model: ''
    llm_judge_prompt_template: ''
logging: {}
prediction:
    batch_size_inference: 0
    max_length_inference: 256
    metrics:
    - BLEU
    min_length_inference: 2
    num_beams: 1
    repetition_penalty: 1.0
    temperature: 0.0
    top_k: 0
    top_p: 1.0
experiment_name: hungry-bonobo
experiment_id: 74273746-83a7-459b-83ed-c4d06df0d782
project_id: 14673bfa-20ad-486c-815b-f0fed6c6eae8
reference_experiment_ids: []
llm_backbone: h2oai/h2ovl-mississippi-2b
problem_type: multimodal_causal_language_modeling