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Merge pull request #35 from microsoft/ilyagu/conformer1.0_config_files
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Added conformer1.0 SC/MC configuration files.
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ig177 authored Mar 18, 2024
2 parents db797d2 + ef49ce7 commit 3d80ac4
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42 changes: 42 additions & 0 deletions configs/train_css/local/conformer_v1.0_mc.yaml
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# Note that this model uses a mask-based loss, in contrast to a masked magnitude loss that was used in conformer_v0.5.
train_dir: ./v1.5/200hrs/train
val_dir: ./v1.5/200hrs/val
out_dir: ./

train_set_cfg:
sample_frac: 1.0
max_urls: null # null means no limit
val_set_cfg:
sample_frac: 1.0
max_urls: null # null means no limit

calc_side_info: True
log_params_mlflow: True
log_metrics_mlflow: True

scheduler_step_every: [1, iterations]
scheduler_name: step_lr
scheduler_step_lr_cfg:
# Fixed LR
step_size: 1
gamma: 1.0

stop_after: [520000, iterations]
eval_every: [1000, iterations]
save_every: [1000, iterations]

loss_name: 'mask'
base_loss_name: 'l1'

global_batch_size: 256
learning_rate: 1e-4
weight_decay: 1e-2 # according to the paper set to 1e-2

# Large model per CSS with Conformer definition
conformer_css_cfg:
nnet_conf:
conformer_conf:
attention_dim: 512 # default 256
attention_heads: 8 # default 4
num_blocks: 18 # default 16
dropout_rate: 0.0 # New! The default was 0.1.
46 changes: 46 additions & 0 deletions configs/train_css/local/conformer_v1.0_sc.yaml
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# Note that this model uses a mask-based loss, in contrast to a masked magnitude loss that was used in conformer_v0.5.
train_dir: ./v1.5/1000hrs/train
val_dir: ./v1.5/200hrs/val # enough for validation
out_dir: ./

single_channel: True

train_set_cfg:
sample_frac: 1.0
max_urls: 640 # out of a total of 800. Subsample to fit local storage and avoid cache misses.
val_set_cfg:
sample_frac: 1.0
max_urls: null # null means no limit

calc_side_info: True
log_params_mlflow: True
log_metrics_mlflow: True

scheduler_step_every: [1, iterations]
scheduler_name: linear_warmup_decay
scheduler_linear_warmup_decay_cfg:
warmup: 10000
decay: 520000

stop_after: [520000, iterations]
eval_every: [1000, iterations]
save_every: [1000, iterations]

loss_name: 'mask'
base_loss_name: 'l1'

global_batch_size: 256
learning_rate: 1e-4
weight_decay: 1e-2 # according to the paper set to 1e-2

# Large model per CSS with Conformer definition
conformer_css_cfg:
extractor_conf:
ipd_index: '' # For MC '1,0;2,0;3,0;4,0;5,0;6,0'. For SC ''.
nnet_conf:
conformer_conf:
attention_dim: 512 # default 256
attention_heads: 8 # default 4
num_blocks: 18 # default 16
dropout_rate: 0.0 # New! The default was 0.1.
in_features: 257 # For MC 1799. For SC 257.

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