| 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/Drug Training - Exact Match/Drug | |
| Training - Training Data AT.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_Ollama_v3.2.1 | |
| llm_backbone: openlm-research/open_llama_3b | |
| logging: | |
| logger: None | |
| neptune_project: '' | |
| number_of_texts: 10 | |
| output_directory: /app/h2o-llmstudio/output/user/Drug_Ollama_v3.2.1/ | |
| 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: 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 | |