Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Chinese
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use thomas0104/whisper_medium_nan_tw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thomas0104/whisper_medium_nan_tw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thomas0104/whisper_medium_nan_tw")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("thomas0104/whisper_medium_nan_tw") model = AutoModelForSpeechSeq2Seq.from_pretrained("thomas0104/whisper_medium_nan_tw") - Notebooks
- Google Colab
- Kaggle
File size: 382 Bytes
d0d02c2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"epoch": 25.01,
"eval_cer": 22.368140081144567,
"eval_loss": 0.9100435376167297,
"eval_runtime": 285.8867,
"eval_samples_per_second": 3.449,
"eval_steps_per_second": 0.434,
"eval_wer": 42.07091581466174,
"train_loss": 0.12630675020669588,
"train_runtime": 10982.7988,
"train_samples_per_second": 3.642,
"train_steps_per_second": 0.455
} |