models: - name: "ar+nar" size: "full" resp_levels: 8 prom_levels: 8 tasks: 8 langs: 2 tones: 1 arch_type: "retnet" training: True version: 3 hyperparameters: batch_size: 4 gradient_accumulation_steps: 4 gradient_clipping: 10 optimizer: Adagrad torch_optimizer: True learning_rate: 1.0e-2 scheduler_type: "" #scheduler_type: OneCycle #scheduler_params: # cycle_first_step_size: 10_000 # cycle_first_stair_count: 10_000 # cycle_second_step_size: 15_000 # cycle_second_stair_count: 15_000 # decay_step_size: 5_000 # cycle_min_lr: 2.5e-4 # 1.0e-5 # cycle_max_lr: 2.5e-4 # 1.0e-4 # decay_lr_rate: 0.0 # cycle_min_mom: 0.90 # cycle_max_mom: 0.99 # decay_mom_rate: 0.0 evaluation: batch_size: 8 frequency: 10000 size: 8 steps: 500 ar_temperature: 0.95 nar_temperature: 0.25 load_disabled_engines: True trainer: no_logger: True iterations: 1_000_000 save_tag: step save_on_oom: True save_on_quit: True save_frequency: 250 export_on_save: True keep_last_checkpoints: 4 aggressive_optimizations: False load_disabled_engines: False #load_state_dict: True strict_loading: False #load_tag: "9500" #load_states: False #restart_step_count: True gc_mode: None # "global_step" weight_dtype: float32 amp: False backend: deepspeed deepspeed: inferencing: True zero_optimization_level: 0 use_compression_training: False activation_checkpointing: True load_webui: True inference: backend: deepspeed audio_backend: "dac" normalize: False weight_dtype: float32 amp: False bitsandbytes: enabled: False injects: False replace: False linear: False embedding: False bitnet: False fp8: enabled: False backend: "te" experimental: True dataset: speaker_name_getter: "lambda p: f'{p.parts[-3]}_{p.parts[-2]}'" speaker_group_getter: "lambda p: f'{p.parts[-3]}'" speaker_languages: ja: [] use_hdf5: True use_metadata: True hdf5_flag: r validate: True workers: 8 cache: True #phones_range: [4, 512] #duration_range: [1.0, 32.0] phones_range: [0, 512] duration_range: [0.0, 64.0] random_utterance: 1.0 max_prompts: 3 prompt_duration: 6.0 max_resps: 1 p_resp_append: 0.25 sample_type: speaker tasks_list: [ "tts" ] # , [ "tts", "tts-c", "ns", "sr", "tse", "cse", "nse", "tts"] training: [] validation: [] noise: []