Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Instructions to use Makkoen/whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Makkoen/whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Makkoen/whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Makkoen/whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000") model = AutoModelForSpeechSeq2Seq.from_pretrained("Makkoen/whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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---
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license: apache-2.0
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base_model: openai/whisper-large-v3
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tags:
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metrics:
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- wer
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model-index:
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- name: whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.4507
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- Wer: 21.8713
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language:
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- en
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license: apache-2.0
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base_model: openai/whisper-large-v3
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tags:
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metrics:
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- wer
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model-index:
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- name: ./whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ./whisper-large-cit-synth-do0.15-wd0-lr1e-05-1000
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the SF 1000 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4507
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- Wer: 21.8713
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