End of training
Browse files- README.md +11 -8
- preprocessor_config.json +14 -0
README.md
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---
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library_name: transformers
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-
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_17_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:
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type: common_voice_17_0
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config: nan-tw
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split: test
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args:
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metrics:
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- name: Wer
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type: wer
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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 [
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It achieves the following results on the evaluation set:
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- Loss: 0.4709
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- Wer: 84.1740
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---
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library_name: transformers
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language:
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- nan
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license: apache-2.0
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base_model: openai/whisper-medium
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tags:
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_17_0
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metrics:
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- wer
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model-index:
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- name: Hokkien-to-Tai Lo Whisper ver 4
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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 16.0
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type: mozilla-foundation/common_voice_17_0
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config: nan-tw
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split: test
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args: 'config: hi, split: test'
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metrics:
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- name: Wer
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type: wer
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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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# Hokkien-to-Tai Lo Whisper ver 4
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4709
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- Wer: 84.1740
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preprocessor_config.json
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{
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"chunk_length": 30,
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"feature_extractor_type": "WhisperFeatureExtractor",
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"feature_size": 80,
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"hop_length": 160,
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"n_fft": 400,
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"n_samples": 480000,
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"nb_max_frames": 3000,
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"padding_side": "right",
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"padding_value": 0.0,
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"processor_class": "WhisperProcessor",
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"return_attention_mask": false,
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"sampling_rate": 16000
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}
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