Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use razhan/whisper-base-hawrami-transcription with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razhan/whisper-base-hawrami-transcription with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="razhan/whisper-base-hawrami-transcription")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("razhan/whisper-base-hawrami-transcription") model = AutoModelForSpeechSeq2Seq.from_pretrained("razhan/whisper-base-hawrami-transcription", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 4.0, | |
| "eval_cer": 0.08564332792052727, | |
| "eval_loss": 0.2611912190914154, | |
| "eval_runtime": 165.3715, | |
| "eval_samples": 1263, | |
| "eval_samples_per_second": 7.637, | |
| "eval_steps_per_second": 0.06, | |
| "eval_wer": 0.40128824476650565 | |
| } |