110 lines
2.1 KiB
YAML
Executable File
110 lines
2.1 KiB
YAML
Executable File
dataset:
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training: []
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validation: []
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speaker_name_getter: "lambda p: f'{p.parts[-3]}_{p.parts[-2]}'"
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use_hdf5: True
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hdf5_flag: r
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validate: True
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workers: 4
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cache: True
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phones_range: [4, 256]
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duration_range: [1.0, 16.0]
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random_utterance: 1.0
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max_prompts: 3
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prompt_duration: 3.0
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sample_type: speaker
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tasks_list: ["tts"] # do NOT change this until you're ready to train for SpeechX tasks # ["tts", "tts", "ns", "sr", "tse", "tts", "tts"]
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models:
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_models:
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- name: "ar"
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size: "full"
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resp_levels: 1
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prom_levels: 2
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tasks: 8
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arch_type: "retnet"
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- name: "nar"
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size: "full"
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resp_levels: 1
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prom_levels: 2
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tasks: 8
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arch_type: "retnet"
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hyperparameters:
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batch_size: 16
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gradient_accumulation_steps: 2
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gradient_clipping: 100
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optimizer: Adamw
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learning_rate: 1.0e-5
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scheduler_type: ""
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#scheduler_type: OneCycle
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#scheduler_params:
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# cycle_first_step_size: 10_000
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# cycle_first_stair_count: 10_000
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# cycle_second_step_size: 15_000
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# cycle_second_stair_count: 15_000
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# decay_step_size: 5_000
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# cycle_min_lr: 2.5e-4 # 1.0e-5
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# cycle_max_lr: 2.5e-4 # 1.0e-4
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# decay_lr_rate: 0.0
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# cycle_min_mom: 0.90
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# cycle_max_mom: 0.99
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# decay_mom_rate: 0.0
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evaluation:
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batch_size: 32
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frequency: 500
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size: 32
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steps: 300
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ar_temperature: 1.0
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nar_temperature: 1.0
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trainer:
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iterations: 1_000_000
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save_tag: step
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save_on_oom: True
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save_on_quit: True
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save_frequency: 1000
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keep_last_checkpoints: 4
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aggressive_optimizations: False
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#load_state_dict: True
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#strict_loading: False
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#load_tag: "9500"
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#load_states: False
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#restart_step_count: True
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gc_mode: None # "global_step"
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weight_dtype: bfloat16
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backend: deepspeed
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deepspeed:
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zero_optimization_level: 0
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use_compression_training: True
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inference:
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use_vocos: True
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normalize: False # do NOT change this unless you know exactly what you are doing.
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bitsandbytes:
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enabled: false
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