CDLI SLAM-ASR Luganda Atypical Speech Projector-Only Checkpoint (Epoch 1 Step 5000)

Projector-only atypical-speech adaptation checkpoint for SLAM-ASR on the CDLI Luganda atypical speech dataset. The encoder and Sunflower-14B decoder remain frozen; only the linear projector is updated from the ASR-adapted starting checkpoint.

What this repository contains

This Hub repository stores a partial SLAM-ASR checkpoint for use with the SLAM-LLM codebase. It is not a standalone transformers checkpoint.

  • Checkpoint type: projector_only
  • Architecture: Whisper encoder (Sunbird/asr-whisper-large-v3-salt) + linear projector + Sunflower-14B decoder; encoder frozen; LLM frozen; no PEFT adapters.
  • Base encoder: Sunbird/asr-whisper-large-v3-salt
  • Base LLM: Sunbird/Sunflower-14B
  • Exported files: model.pt

Training / evaluation context

  • Dataset: cdli/ugandan_luganda_nonstandard_speech_v1.0
  • Evaluation split: validation
  • Training speakers: 36
  • Validation speakers: 5
  • Speaker overlap: No speaker overlap between train and validation/test

Reported metrics

  • Normalized WER (JiWER scorer): not provided
  • Normalized CER (JiWER scorer): not provided
  • Atypical overall normalized WER: not provided
  • Atypical overall normalized CER: not provided
  • Atypical averaged utterance WER: not provided
  • Atypical averaged utterance CER: not provided

Decode settings used for the reported metrics

Final decode metrics for this checkpoint are not uploaded yet. This repository is being published as an earlier projector-only research checkpoint for comparison.

Additional results notes

This is the epoch 1 step 5000 checkpoint from the projector-only atypical adaptation run. The later epoch 2 step 107 checkpoint achieved the stronger reported test result and is published separately.

Loading notes

Load through SLAM-LLM; this repository stores a partial SLAM-ASR checkpoint, not a standalone Transformers model.

Typical decode flow in this project uses:

  • examples/asr_luganda/scripts/decode_luganda_sunflower.sh
  • USE_ENCODER_PEFT=true for encoder-LoRA checkpoints
  • matching LoRA target modules at decode time

Caveats

  • This repository stores SLAM-ASR training artifacts intended for research use.
  • The checkpoint must be used with the matching SLAM-LLM model code and base components.
  • Results can be sensitive to decode settings and evaluation protocol.
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