fixie-ai/common_voice_17_0
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How to use deepdml/whisper-tiny-ta-mix-norm with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="deepdml/whisper-tiny-ta-mix-norm") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("deepdml/whisper-tiny-ta-mix-norm")
model = AutoModelForSpeechSeq2Seq.from_pretrained("deepdml/whisper-tiny-ta-mix-norm")This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.2508 | 0.125 | 1000 | 0.3392 | 62.4235 | 15.5864 |
| 0.1747 | 0.25 | 2000 | 0.3003 | 57.3701 | 13.4963 |
| 0.1586 | 0.375 | 3000 | 0.2905 | 55.5023 | 13.1754 |
| 0.1244 | 0.5 | 4000 | 0.2812 | 53.6500 | 12.6062 |
| 0.1361 | 0.625 | 5000 | 0.2687 | 52.9080 | 12.3268 |
| 0.1093 | 0.75 | 6000 | 0.2685 | 52.2523 | 12.0787 |
| 0.1141 | 0.875 | 7000 | 0.2647 | 51.9844 | 11.9065 |
| 0.1274 | 1.0 | 8000 | 0.2641 | 51.6662 | 11.8757 |
Please cite the model using the following BibTeX entry:
@misc{deepdml/whisper-tiny-ta-mix-norm,
title={Fine-tuned Whisper tiny ASR model for speech recognition in Tamil},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-ta-mix-norm}},
year={2026}
}
Base model
openai/whisper-tiny