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
File size: 473 Bytes
b375e8b 39c8550 b375e8b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"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,
"total_flos": 2.6372074438656e+18,
"train_loss": 0.7337436556816102,
"train_runtime": 5396.4455,
"train_samples": 10165,
"train_samples_per_second": 7.535,
"train_steps_per_second": 0.059
} |