config_no-sample.yaml

defaults:
  - model: llm-jp_llm-jp-1.3b-v1.0
  - tokenizer: llm-jp_llm-jp-1.3b-v1.0
  - _self_

# basic information
openapi: False # put model name of api into model.pretrained_model_name_or_path
max_seq_length: 2048
dataset_dir: "path/to/dataset"
strict: false # true の場合、指定のデータセットがないとエラーが出ます。
target_dataset: "all" # all OR ["alt-e-to-j", "alt-j-to-e", "chabsa", "jamp", "janli", "jcommonsenseqa", "jemhopqa", "jmmlu", "jnli", "jsem", "jsick", "jsquad", "jsts", "mawps", "mmluen", "niilc", "wikicorpus-e-to-j", "wikicorpus-j-to-e", "wiki_reading", "wiki_ner", "wiki_dependency", "wiki_pas", "wiki_coreference"]
log_dir: "./logs"
torch_dtype: "bf16" # {fp16, bf16, fp32}
custom_prompt_template: null
# if you use this, please include {instruction} and {input}. If you use few shots, please include {few_shots_text} additionally.
# example of prompt template for few-shots
# "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n### 指示:\n{instruction}{few_shots_text}\n\n### 入力:\n{input}\n\n### 応答:\n"
# example of prompt template for zeroshot
# "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n### 指示:\n{instruction}\n\n### 入力:\n{input}\n\n### 応答:\n"
custom_fewshots_template: null
# Please include {input} and {output}
# example of few-shots template
# "\n\n### 入力:\n{input}\n\n### 応答:\n{output}"

wandb:
  launch: false # true for WANDB Launch. notice: if it is true, all other configurations will be overwrited by launch config
  log: false # true for logging WANDB in evaluate_llm.py
  entity: "your/WANDB/entity"
  project: "your/WANDB/project"
  run_name: "your/WANDB/run name" # use run_name defined above

metainfo:
  version: "1.3.0"
  basemodel_name: "model/name/including/expriment/information"
  model_type: "model/type" # {llm-jp, external model, openai}
  instruction_tuning_method_by_llm_jp: "tuning/method" # {"None", "Full", "LoRA", ...}
  instruction_tuning_data_by_llm_jp: ["dataset", "names"] # ["None", "jaster", "dolly_ja", "oasst_ja", ...]
  data_type: "dev" # {"dev", "test"}
  num_few_shots: 4
  max_num_samples: 100 # -1 for all data

generator:
  do_sample: false
  repetition_penalty: 1.0

# hydra settings
hydra:
  job:
    env_set:
      TOKENIZERS_PARALLELISM: false