google/fleurs
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How to use sgangireddy/whisper-small-ta with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="sgangireddy/whisper-small-ta") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("sgangireddy/whisper-small-ta")
model = AutoModelForSpeechSeq2Seq.from_pretrained("sgangireddy/whisper-small-ta")This model is a fine-tuned version of openai/whisper-small on the google/fleurs ta_in dataset. It achieves the following results on the evaluation set:
This model is fine-tuned for 1000 steps on Tamil Fluers data.
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0004 | 83.33 | 1000 | 0.5390 | 20.9327 |