ai4bharat/IndicVoices
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How to use erjoy/whisper-tiny-hi-3k-steps with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="erjoy/whisper-tiny-hi-3k-steps") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("erjoy/whisper-tiny-hi-3k-steps")
model = AutoModelForSpeechSeq2Seq.from_pretrained("erjoy/whisper-tiny-hi-3k-steps")This model is a fine-tuned version of openai/whisper-tiny on the ai4bharat/IndicVoices 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 |
|---|---|---|---|---|
| 0.6607 | 0.8104 | 500 | 0.6622 | 72.1794 |
| 0.4574 | 1.6207 | 1000 | 0.5104 | 59.5822 |
| 0.3659 | 2.4311 | 1500 | 0.4626 | 56.2291 |
| 0.3346 | 3.2415 | 2000 | 0.4417 | 53.4954 |
| 0.2912 | 4.0519 | 2500 | 0.4301 | 51.6118 |
| 0.275 | 4.8622 | 3000 | 0.4275 | 51.3495 |
Base model
openai/whisper-tiny