naharte/russian_english
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How to use Quiglee2/whisper-tiny-russian-ft with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Quiglee2/whisper-tiny-russian-ft") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Quiglee2/whisper-tiny-russian-ft")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Quiglee2/whisper-tiny-russian-ft", device_map="auto")This model is a fine-tuned version of openai/whisper-tiny on the Russian English 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 |
|---|---|---|---|---|
| 0.1726 | 1.0707 | 1000 | 0.2409 | 10.6280 |
| 0.0781 | 2.1413 | 2000 | 0.2263 | 10.1195 |
Base model
openai/whisper-tiny