DynamicSuperb/AAVESpeechRecognition_CORAAL
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How to use melvinrajendran/whisper-tiny-coraal with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="melvinrajendran/whisper-tiny-coraal") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("melvinrajendran/whisper-tiny-coraal")
model = AutoModelForSpeechSeq2Seq.from_pretrained("melvinrajendran/whisper-tiny-coraal", device_map="auto")This model is a fine-tuned version of openai/whisper-tiny on the AAVE Speech Recognition CORAAL 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 |
|---|---|---|---|---|
| 1.5330 | 0.6579 | 25 | 1.2165 | 32.8886 |
| 1.0415 | 1.3158 | 50 | 0.8379 | 29.4863 |
| 0.7776 | 1.9737 | 75 | 0.7499 | 30.3536 |
| 0.6051 | 2.6316 | 100 | 0.7323 | 28.4857 |
| 0.4924 | 3.2895 | 125 | 0.7279 | 36.7578 |
| 0.4527 | 3.9474 | 150 | 0.7222 | 36.2909 |
| 0.3521 | 4.6053 | 175 | 0.7257 | 30.9540 |
| 0.3158 | 5.2632 | 200 | 0.7214 | 29.4196 |
Base model
openai/whisper-tiny