Hervé Bredin
feat: initial import
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raw
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protocol: Debug.SpeakerDiarization.Debug
patience: 5
task:
_target_: pyannote.audio.tasks.VoiceActivityDetection
duration: 2.0
batch_size: 32
num_workers: null
pin_memory: false
model:
_target_: pyannote.audio.models.segmentation.debug.SimpleSegmentationModel
optimizer:
_target_: torch.optim.Adam
lr: 0.001
betas:
- 0.9
- 0.999
eps: 1.0e-08
weight_decay: 0
amsgrad: false
trainer:
_target_: pytorch_lightning.Trainer
accelerator: null
accumulate_grad_batches: 1
amp_backend: native
amp_level: O2
auto_lr_find: false
auto_scale_batch_size: false
auto_select_gpus: true
benchmark: false
check_val_every_n_epoch: 1
checkpoint_callback: true
deterministic: false
fast_dev_run: false
flush_logs_every_n_steps: 100
gpus: null
gradient_clip_val: 0
limit_test_batches: 1.0
limit_train_batches: 1.0
limit_val_batches: 1.0
log_every_n_steps: 50
log_gpu_memory: null
max_epochs: 10
max_steps: null
min_epochs: 1
min_steps: null
num_nodes: 1
num_processes: 1
num_sanity_val_steps: 2
overfit_batches: 0.0
precision: 32
prepare_data_per_node: true
process_position: 0
profiler: null
progress_bar_refresh_rate: 1
reload_dataloaders_every_epoch: false
replace_sampler_ddp: true
sync_batchnorm: false
terminate_on_nan: false
tpu_cores: null
track_grad_norm: -1
truncated_bptt_steps: null
val_check_interval: 1.0
weights_save_path: null
weights_summary: top