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
| { | |
| "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 | |
| } |