clt013/malay-speech-3k-rows-dataset
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How to use clt013/whisper-small-ft-malay-test-3 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="clt013/whisper-small-ft-malay-test-3") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("clt013/whisper-small-ft-malay-test-3")
model = AutoModelForSpeechSeq2Seq.from_pretrained("clt013/whisper-small-ft-malay-test-3")This model is a fine-tuned version of openai/whisper-small on the Malay Speech 3k 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 |
|---|---|---|---|---|
| 0.7275 | 0.1 | 100 | 0.677592 | 38.9111 |
| 0.521 | 0.2 | 200 | 0.565486 | 36.6151 |
| 0.3128 | 0.3 | 300 | 0.525294 | 29.7965 |
| 0.2964 | 0.4 | 400 | 0.500519 | 35.2235 |
| 0.1631 | 0.5 | 500 | 0.508256 | 36.2845 |
| 0.0731 | 0.6 | 600 | 0.532225 | 38.4414 |
| 0.0548 | 0.7 | 700 | 0.519905 | 27.2743 |
| 0.0289 | 0.8 | 800 | 0.533013 | 27.6917 |
| 0.0131 | 0.9 | 900 | 0.548259 | 26.9090 |
| 0.0071 | 1.0 | 1000 | 0.545344 | 27.1699 |
Base model
openai/whisper-small