mms1b-lid-softmax-soft-fleurs-csfleurs

ESPnet FLEURS-CS LID, explicitly selected epoch (10epoch.pth). This is not a claim of best-checkpoint performance.

License: CC-BY-NC-4.0 (including the MMS-1B backbone where used). No evaluation metrics are asserted. See provenance.json for hashes.

No optimizer state, audio or real utterance IDs. Use matching ESPnet CS-LID code (canonical PIT keys); MMS inference still requires its backbone/cache.

The config retains training settings, including optimizer/scheduler hyperparameters, but no optimizer/scheduler state is uploaded. Historical training data, initialization and output paths are provenance, not bundled assets; relocate them before training on another server. Language inventory and ASR token/symbol references are made bundle-local or inlined.

LID: resolve lang2utt relative to the bundle for upstream preprocessing. Its placeholders are not training references. Optional utt2langs contains explicitly supplied frozen training language sets with synthetic IDs: valid for seen/unseen membership, never for utterance counts. Without that file, supply actual frozen training references separately.

Architecture

Selected settings from the validated portable config:

frontend: s3prl
frontend_conf:
  fs: 16000
  frontend_conf:
    upstream: hf_wav2vec2_custom
    path_or_url: facebook/mms-1b
  download_dir: ./hub
  multilayer_feature: true
encoder: ecapa_tdnn
encoder_conf:
  model_scale: 8
  ndim: 512
  output_size: 1536
model_conf:
  extract_feats_in_collect_stats: false
freeze_param: []
pooling: chn_attn_stat
pooling_conf: {}
projector: rawnet3
projector_conf:
  output_size: 192
loss: aamsoftmax_sc_topk_softtarget
loss_conf:
  margin: 0.5
  scale: 30
  K: 3
  mp: 0.06
  k_top: 5
lang_num: 102