|
architecture: |
|
backbone_dtype: float16 |
|
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 |
|
add_eos_token_to_system: true |
|
answer_column: "explicit\r" |
|
chatbot_author: H2O.ai |
|
chatbot_name: h2oGPT |
|
data_sample: 1.0 |
|
data_sample_choice: |
|
- Train |
|
- Validation |
|
limit_chained_samples: false |
|
mask_prompt_labels: true |
|
parent_id_column: None |
|
personalize: false |
|
prompt_column: |
|
- abstract_title |
|
system_column: None |
|
text_answer_separator: <|answer|> |
|
text_prompt_start: <|prompt|> |
|
text_system_start: <|system|> |
|
train_dataframe: /app/h2o-llmstudio/data/user/Explicit_20k/Explicit_20k.csv |
|
validation_dataframe: None |
|
validation_size: 0.01 |
|
validation_strategy: automatic |
|
environment: |
|
compile_model: false |
|
find_unused_parameters: false |
|
gpus: |
|
- '0' |
|
- '1' |
|
huggingface_branch: main |
|
mixed_precision: true |
|
number_of_workers: 8 |
|
seed: -1 |
|
trust_remote_code: true |
|
use_fsdp: false |
|
experiment_name: Moas_Explicit_PYT_v2 |
|
llm_backbone: EleutherAI/pythia-2.8b-deduped |
|
logging: |
|
logger: None |
|
neptune_project: '' |
|
number_of_texts: 10 |
|
output_directory: /app/h2o-llmstudio/output/user/Moas_Explicit_PYT_v2/ |
|
prediction: |
|
batch_size_inference: 0 |
|
do_sample: false |
|
max_length_inference: 256 |
|
metric: BLEU |
|
metric_gpt_model: gpt-3.5-turbo-0301 |
|
min_length_inference: 2 |
|
num_beams: 1 |
|
num_history: 4 |
|
repetition_penalty: 1.2 |
|
stop_tokens: '' |
|
temperature: 0.0 |
|
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: 640 |
|
max_length_answer: 128 |
|
max_length_prompt: 512 |
|
padding_quantile: 1.0 |
|
use_fast: true |
|
training: |
|
adaptive_kl_control: true |
|
advantages_gamma: 0.99 |
|
advantages_lambda: 0.95 |
|
batch_size: 8 |
|
differential_learning_rate: 1.0e-05 |
|
differential_learning_rate_layers: [] |
|
drop_last_batch: true |
|
epochs: 3 |
|
evaluate_before_training: false |
|
evaluation_epochs: 1.0 |
|
grad_accumulation: 1 |
|
gradient_clip: 0.0 |
|
initial_kl_coefficient: 0.2 |
|
kl_horizon: 10000 |
|
kl_target: 6.0 |
|
learning_rate: 0.0001 |
|
lora: true |
|
lora_alpha: 16 |
|
lora_dropout: 0.05 |
|
lora_r: 31 |
|
lora_target_modules: '' |
|
loss_function: TokenAveragedCrossEntropy |
|
offload_reward_model: false |
|
optimizer: AdamW |
|
ppo_batch_size: 1 |
|
ppo_clip_policy: 0.2 |
|
ppo_clip_value: 0.2 |
|
ppo_epochs: 4 |
|
ppo_generate_temperature: 1.0 |
|
reward_model: OpenAssistant/reward-model-deberta-v3-large-v2 |
|
save_best_checkpoint: false |
|
scaling_factor_value_loss: 0.1 |
|
schedule: Cosine |
|
train_validation_data: false |
|
use_rlhf: false |
|
warmup_epochs: 0.0 |
|
weight_decay: 0.0 |
|
|