cfg.yaml

architecture:
    backbone_dtype: float32
    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: 0.1
dataset:
    add_eos_token_to_answer: false
    add_eos_token_to_prompt: false
    add_eos_token_to_system: false
    add_prompt_answer_tokens: false
    answer_column: score
    chatbot_author: H2O.ai
    chatbot_name: h2oGPT
    data_sample: 1.0
    data_sample_choice:
    - Train
    - Validation
    limit_chained_samples: false
    mask_prompt_labels: true
    num_classes: 6
    parent_id_column: None
    personalize: false
    prompt_column:
    - full_text
    - count_sentence
    - count_word
    - count_paragraph
    - count_symbol
    - count_punctuation
    - count_stop_words
    - count_ner
    - CARDINAL
    - DATE
    - EVENT
    - FAC
    - GPE
    - LANGUAGE
    - LAW
    - LOC
    - MONEY
    - NORP
    - ORDINAL
    - ORG
    - PERCENT
    - PERSON
    - PRODUCT
    - QUANTITY
    - TIME
    - WORK_OF_ART
    - mean_ner_sentence
    - len_ner
    - mean_ner
    - proc_ner_per_text
    - max_ner_per_sentence
    - independent_clauses
    - dependent_clauses
    - formality_level
    - simple_sentence_count
    - complex_sentence_count
    - has_intro
    - count_intro
    - has_repetitions
    - count_repetitions
    - coherence
    - -LRB-
    - -RRB-
    - ADD
    - AFX
    - CC
    - CD
    - DT
    - EX
    - FW
    - HYPH
    - IN
    - JJ
    - JJR
    - JJS
    - LS
    - MD
    - NFP
    - NN
    - NNP
    - NNPS
    - NNS
    - PDT
    - POS
    - PRP
    - PRP$
    - RB
    - RBR
    - RBS
    - RP
    - SYM
    - TO
    - UH
    - VB
    - VBD
    - VBG
    - VBN
    - VBP
    - VBZ
    - WDT
    - WP
    - WP$
    - WRB
    - XX
    - _SP
    - ROOT
    - acl
    - acomp
    - advcl
    - advmod
    - agent
    - amod
    - appos
    - attr
    - aux
    - auxpass
    - case
    - cc
    - ccomp
    - compound
    - conj
    - csubj
    - csubjpass
    - dative
    - dep
    - det
    - dobj
    - expl
    - intj
    - mark
    - meta
    - neg
    - nmod
    - npadvmod
    - nsubj
    - nsubjpass
    - nummod
    - oprd
    - parataxis
    - pcomp
    - pobj
    - poss
    - preconj
    - predet
    - prep
    - prt
    - punct
    - quantmod
    - relcl
    - xcomp
    system_column: None
    text_answer_separator: ''
    text_prompt_start: ''
    text_system_start: ''
    train_dataframe: /root/h2o-llmstudio/data/user/train_spacy_mamba/train_spacy_mamba.csv
    validation_dataframe: None
    validation_size: 0.01
    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: 8
    seed: -1
    trust_remote_code: true
    use_deepspeed: false
experiment_name: spacy-mamba
llm_backbone: h2oai/h2ogpt-4096-llama2-7b
logging:
    logger: Neptune
    neptune_project: samvelkoch/essay
output_directory: /root/h2o-llmstudio/output/user/spacy-mamba/
prediction:
    batch_size_inference: 0
    metric: Accuracy
problem_type: text_causal_classification_modeling
tokenizer:
    add_prompt_answer_tokens: false
    max_length: 10240
    padding_quantile: 1.0
    tokenizer_kwargs: '{"use_fast": true, "add_prefix_space": false}'
training:
    batch_size: 2
    differential_learning_rate: 1.0e-05
    differential_learning_rate_layers:
    - classification_head
    drop_last_batch: true
    epochs: 1
    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: 16
    lora_dropout: 0.05
    lora_r: 4
    lora_target_modules: ''
    lora_unfreeze_layers: []
    loss_function: CrossEntropyLoss
    optimizer: AdamW
    save_checkpoint: last
    schedule: Cosine
    train_validation_data: false
    use_dora: false
    use_flash_attention_2: true
    warmup_epochs: 0.0
    weight_decay: 0.0