openslr/librispeech_asr
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How to use Pageee/FT-English-10ma with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Pageee/FT-English-10ma") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Pageee/FT-English-10ma")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Pageee/FT-English-10ma")This model is a fine-tuned version of openai/whisper-small on the librispeech 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 |
|---|---|---|---|---|
| 0.4076 | 16.6667 | 100 | 0.6901 | 3.4530 |
| 0.0849 | 33.3333 | 200 | 0.4441 | 3.4673 |
| 0.0295 | 50.0 | 300 | 0.4029 | 3.5427 |
Base model
openai/whisper-small