How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("automatic-speech-recognition", model="teckedd/serendepify-gsl-asr-ak-waxal-whisper-small-only-lowlr-freezeenc-fullft-v0.4")
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq

processor = AutoProcessor.from_pretrained("teckedd/serendepify-gsl-asr-ak-waxal-whisper-small-only-lowlr-freezeenc-fullft-v0.4")
model = AutoModelForSpeechSeq2Seq.from_pretrained("teckedd/serendepify-gsl-asr-ak-waxal-whisper-small-only-lowlr-freezeenc-fullft-v0.4", device_map="auto")
Quick Links

serendepify-gsl-asr-ak-waxal-whisper-small-only-lowlr-freezeenc-fullft-v0.4

This is a Ghanaian Speech Lab ASR artifact: a Waxal-only low-learning-rate full fine-tuning pass from the Round 2 checkpoint with the Whisper encoder frozen.

It is a real training run, not a smoke-test checkpoint, but it is still a review candidate until the held-out evaluation and failure taxonomy are complete.

License is set conservatively because this pass includes Waxal-derived data.

  • Training rows: 9138
  • Dev rows: 1024
  • Max steps: 600
  • Method: full fine-tuning from teckedd/whisper-small-waxal-round2-specaug-v1
  • Dataset mix: Waxal only from the v0.1 sanitized manifest
  • Frozen encoder: True
  • Stop on first regression: True

Baseline metrics:

{
  "baseline_loss": 3.306061029434204,
  "baseline_model_preparation_time": 0.0044,
  "baseline_wer": 0.31875728802265535,
  "baseline_runtime": 651.5194,
  "baseline_samples_per_second": 1.572,
  "baseline_steps_per_second": 0.393
}

Baseline by corpus:

{
  "waxal": {
    "baseline_waxal_loss": 3.306061029434204,
    "baseline_waxal_model_preparation_time": 0.0044,
    "baseline_waxal_wer": 0.31875728802265535,
    "baseline_waxal_runtime": 656.1573,
    "baseline_waxal_samples_per_second": 1.561,
    "baseline_waxal_steps_per_second": 0.39
  }
}

Final metrics:

{
  "final_loss": 0.4626207947731018,
  "final_model_preparation_time": 0.0044,
  "final_wer": 0.3408573491032262,
  "final_runtime": 636.7901,
  "final_samples_per_second": 1.608,
  "final_steps_per_second": 0.402,
  "epoch": 0.34995625546806647
}

Final by corpus:

{
  "waxal": {
    "final_waxal_loss": 0.4626207947731018,
    "final_waxal_model_preparation_time": 0.0044,
    "final_waxal_wer": 0.3408573491032262,
    "final_waxal_runtime": 645.7581,
    "final_waxal_samples_per_second": 1.586,
    "final_waxal_steps_per_second": 0.396,
    "epoch": 0.34995625546806647
  }
}
Downloads last month
21
Safetensors
Model size
0.2B params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for teckedd/serendepify-gsl-asr-ak-waxal-whisper-small-only-lowlr-freezeenc-fullft-v0.4

Finetuned
(7)
this model