Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use iqbalasrif/whisper-tiny-hyperparameter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iqbalasrif/whisper-tiny-hyperparameter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="iqbalasrif/whisper-tiny-hyperparameter")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("iqbalasrif/whisper-tiny-hyperparameter") model = AutoModelForSpeechSeq2Seq.from_pretrained("iqbalasrif/whisper-tiny-hyperparameter") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1.0204081632653061, | |
| "eval_cer": 0.20496366896291404, | |
| "eval_loss": 1.4505608081817627, | |
| "eval_runtime": 170.4457, | |
| "eval_samples": 1136, | |
| "eval_samples_per_second": 6.665, | |
| "eval_steps_per_second": 0.417, | |
| "eval_wer": 0.6883827458964245 | |
| } |