Whisper
Collection
Whisper model fine-tuned on different languages • 10 items • Updated
How to use ALM/whisper-it-small with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ALM/whisper-it-small") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ALM/whisper-it-small")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ALM/whisper-it-small")This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 it 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 |
|---|---|---|---|---|
| 0.2529 | 1.0 | 466 | 0.2758 | 12.4907 |
| 0.1711 | 2.0 | 932 | 0.2517 | 11.2714 |