johnatanebonilla/coser
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How to use johnatanebonilla/whisper-small-coser with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="johnatanebonilla/whisper-small-coser") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("johnatanebonilla/whisper-small-coser")
model = AutoModelForSpeechSeq2Seq.from_pretrained("johnatanebonilla/whisper-small-coser", device_map="auto")This model is a fine-tuned version of openai/whisper-small on coser-asr 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 |
|---|---|---|---|---|
| 0.8783 | 0.3 | 1000 | 0.9044 | 96.7315 |
| 0.7787 | 0.59 | 2000 | 0.8388 | 102.7047 |
| 0.7897 | 0.89 | 3000 | 0.8049 | 107.5558 |
| 0.6478 | 1.19 | 4000 | 0.7951 | 108.2685 |
Base model
openai/whisper-small