64 lines
2.1 KiB
YAML
64 lines
2.1 KiB
YAML
# Role-based VAP at 12.5 Hz, the rate Mimi natively codes at.
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#
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# `tap: latent` is Mimi's own frame rate, so this matches a full-duplex system
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# built on Mimi codes frame for frame: same frontend, same 80 ms decision grid.
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# Labels come from seg/vad12_5, written by 03_prep_vad_rate.py; the 25 Hz tree
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# is untouched. bin_sec stays at the paper's times, so the rate is the only
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# thing that changes against the 25 Hz runs - at 12.5 Hz they round to
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# 0.16 / 0.4 / 0.64 / 0.8, still a 2.0 s horizon.
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fisher_path: data/fisher
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checkpoint_dir: runs/role_mimi_12hz
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vap:
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audio_encoder:
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name: mimi
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tap: latent # 12.5 Hz, Mimi's own frame rate
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arch: mono # mono | stereo
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batch_size: 64
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num_workers: 16
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max_epochs: 5
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lr: 0.001
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weight_decay: 0.01
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warmup_ratio: 0.1
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min_lr: 0.0001
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precision: bf16-mixed
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gradient_clip_val: 1.0
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accumulate_grad_batches: 1
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matmul_precision: high
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# Metric that selects best.ckpt. Leave empty when there is no held-out
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# split to select on: last.ckpt is written either way.
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checkpoint_monitor: val/loss
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checkpoint_mode: min
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# npy reads the segments written by preprocessing; raw seeks the same window
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# in the source recording and resamples it.
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source: npy
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swap_channels: false # stereo-only augmentation
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projection_window:
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# 1.4 s is 17.5 frames at 12.5 Hz, so the paper's times cannot be
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# represented here. These keep the 4.0 s window exact - [18, 7, 7, 18] -
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# where rounding [1.4, 0.6] gives 26 frames of history for a 25-frame window.
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bin_sec: [1.44, 0.56, 0.56, 1.44]
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num_hist_bins: 2
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frame_hz: 12.5
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threshold: 0.5
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mode: role_relative
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cut_center_frame: false
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temporal:
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d_model: 256
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m_ff: 3
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n_heads: 4
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n_layers: 4
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dropout: 0.1
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activation: GELU
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causal: true
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pos_encoding: alibi # alibi | rope | sinusoidal | none
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ffn: mlp # mlp | swiglu
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norm: layer # layer | rms
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# Size of the sinusoidal position table. Rotary and ALiBi extend to any
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# length, so this bounds the sinusoidal encoding only.
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max_frames: 4096
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