ASR/STT
Collection
8 items • Updated • 1
How to use mrmuminov/whisper-tiny-uz with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="mrmuminov/whisper-tiny-uz") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("mrmuminov/whisper-tiny-uz")
model = AutoModelForSpeechSeq2Seq.from_pretrained("mrmuminov/whisper-tiny-uz")This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6528 | 0.0352 | 2000 | 0.8591 | 62.8798 |
| 0.5201 | 0.0704 | 4000 | 0.7052 | 56.4951 |
| 0.4258 | 0.1056 | 6000 | 0.6407 | 53.7817 |
| 0.4136 | 0.1408 | 8000 | 0.6057 | 50.5588 |
| 0.4164 | 0.1760 | 10000 | 0.5943 | 50.1992 |
Base model
openai/whisper-tiny