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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: "output\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:
- instruction
system_column: None
text_answer_separator: <|answer|>
text_prompt_start: <|prompt|>
text_system_start: <|system|>
train_dataframe: /app/h2o-llmstudio/data/user/Drugs_v2/Input Data.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: Drug_Pythia_v2
llm_backbone: EleutherAI/pythia-2.8b-deduped
logging:
logger: None
neptune_project: ''
number_of_texts: 10
output_directory: /app/h2o-llmstudio/output/user/Drug_Pythia_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: 928
max_length_answer: 128
max_length_prompt: 800
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: 6
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: 0.0004
lora: true
lora_alpha: 16
lora_dropout: 0.05
lora_r: 32
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
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