Gha Whisper Small Twi v6

--- language: - tw - ak - en license: apache-2.0 library_name: transformers pipeline_tag: automatic-speech-recognition base_model: teckedd/gha-whisper-small-twi-v6 tags: - ak - akan - asr - en - ghana - ghana-health-ai - serendepify - speech-recognition - tw - twi - whisper datasets: - google/WaxalNLP - local - fsicoli/common_voice_22_0 - ghananlpcommunity/twi-speech-text-multispeaker-16k model-index: - name: gha-whisper-small-twi-v6 results: - task: type: automatic-speech-recognition dataset: type: google/WaxalNLP name: google/WaxalNLP (aka_asr) metrics: - type: val_wer value: 0.296972 name: VAL_WER - type: val_cer value: 0.103112 name: VAL_CER --- # teckedd/gha-whisper-small-twi-v6 Twi/Akan + English retention Whisper ASR for Ghana Health AI (`v6-local-holdout`). Recipe v6 mix; promote=False. - **Base model:** `teckedd/gha-whisper-small-twi-v6` - **Task:** `automatic-speech-recognition` - **Languages:** `tw`, `ak`, `en` - **Card generated:** 2026-08-16 (UTC) - **Product:** [ghanahealth.serendepify.com](https://ghanahealth.serendepify.com) > Not a medical device. Outputs support community health guidance only. ## Metrics | Metric | Value | |--------|-------| | `val_wer` | 0.2970 | | `val_cer` | 0.1031 | ## Training data - `google/WaxalNLP (aka_asr)` - `local (ghana-health-ai-recorder)` - `fsicoli/common_voice_22_0 (tw)` - `fsicoli/common_voice_22_0 (en)` - `ghananlpcommunity/twi-speech-text-multispeaker-16k (default)` ## Intended use - In-product ASR / TTS / chat for Twi (Akan) and English health conversations in Ghana. - Research on low-resource Ghanaian language speech and health dialogue. ## Out of scope - Clinical diagnosis or autonomous medical decisions. - Claiming near-native quality without reporting held-out WER/CER or human A/B scores. ## How to load ```python from transformers import pipeline # or AutoModel + processor per task # repo: teckedd/gha-whisper-small-twi-v6 ``` ## Citation If you use this checkpoint, please credit **Ghana Health AI / Serendepify** and the upstream base model authors plus any listed datasets. ## Recipe - Run: `v6-local-holdout` - Freeze encoder: `False` - LR / steps / batch: `5e-06` / `600` / `8x4` - Local recorder data: `True` · manifest `/root/gha_local_asr/manifest.train32.jsonl` · weight `0.08` - Baseline to beat (v6 serving, Waxal full test greedy): `0.3149` - Beats v6 greedy: **Fa...