google/fleurs
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How to use emilios/whisper-md-hu with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="emilios/whisper-md-hu") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("emilios/whisper-md-hu")
model = AutoModelForSpeechSeq2Seq.from_pretrained("emilios/whisper-md-hu", device_map="auto")This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0,google/fleurs hu,hu_hu 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 |
|---|---|---|---|---|
| 0.0621 | 1.05 | 1000 | 0.2690 | 20.5099 |
| 0.0174 | 2.1 | 2000 | 0.2705 | 19.2292 |
| 0.006 | 3.15 | 3000 | 0.2954 | 18.9890 |
| 0.0028 | 4.2 | 4000 | 0.3093 | 18.8023 |
| 0.0016 | 5.25 | 5000 | 0.3240 | 18.9653 |
| 0.0018 | 6.3 | 6000 | 0.3313 | 18.6451 |
| 0.0014 | 7.35 | 7000 | 0.3330 | 18.9446 |
| 0.0016 | 8.39 | 8000 | 0.3428 | 18.6422 |
| 0.0015 | 9.44 | 9000 | 0.3508 | 18.9564 |
| 0.001 | 10.49 | 10000 | 0.3569 | 18.8556 |