Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Safetensors
Czech
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use mikr/whisper-large2-czech-cv11-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikr/whisper-large2-czech-cv11-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mikr/whisper-large2-czech-cv11-v2")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mikr/whisper-large2-czech-cv11-v2") model = AutoModelForMultimodalLM.from_pretrained("mikr/whisper-large2-czech-cv11-v2") - Notebooks
- Google Colab
- Kaggle
update model card README.md
Browse files
README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_11_0
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metrics:
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- wer
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model-index:
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- name:
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_11_0
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type: common_voice_11_0
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config: cs
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split: test
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args: cs
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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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#
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2120
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- Wer: 9.0459
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---
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language:
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- cs
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper Large-v2 Czech CV11 v2
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: mozilla-foundation/common_voice_11_0 cs
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type: mozilla-foundation/common_voice_11_0
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config: cs
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split: test
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args: cs
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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-v2 Czech CV11 v2
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 cs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2120
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- Wer: 9.0459
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run.log
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eval_samples_per_second = 3.665
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eval_steps_per_second = 0.458
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eval_wer = 9.0459
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eval_samples_per_second = 3.665
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eval_steps_per_second = 0.458
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eval_wer = 9.0459
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12/17/2022 15:14:25 - WARNING - huggingface_hub.repository - remote: Scanning LFS files for validity, may be slow...
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To https://huggingface.co/mikr/whisper-large2-czech-cv11-v2
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9271259..d5ff598 main -> main
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