Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
PolyAI/minds14
Instructions to use eeizenman/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eeizenman/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eeizenman/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("eeizenman/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("eeizenman/whisper-tiny-en") - Notebooks
- Google Colab
- Kaggle
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# whisper-tiny-en
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.6636
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- Wer Ortho: 32.9426
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# whisper-tiny-en
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the [PolyAI/minds14](https://huggingface.co/datasets/PolyAI/minds14) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6636
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- Wer Ortho: 32.9426
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