Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
German
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use HanCreation/whisper-tiny-french-HanNeurAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HanCreation/whisper-tiny-french-HanNeurAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="HanCreation/whisper-tiny-french-HanNeurAI")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("HanCreation/whisper-tiny-french-HanNeurAI") model = AutoModelForSpeechSeq2Seq.from_pretrained("HanCreation/whisper-tiny-french-HanNeurAI") - Notebooks
- Google Colab
- Kaggle
Dean Hans Felandio Setiadi Saputra commited on
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It achieves the following results on the evaluation set:
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- Loss: 0.6998
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- Wer: 38.8453
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## Model description
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It achieves the following results on the evaluation set:
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- Loss: 0.6998
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- Wer: 38.8453
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This fine-tuning model is part of my school project. With limitation of my compute, I scaled down the dataset
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Additional information and demo code can be found in this github: [HanCreation/Whisper-Tiny-German](https://github.com/HanCreation/Whisper-Tiny-German)
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## Model description
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