PenguinbladeZ
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End of training
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README.md
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@@ -7,36 +7,36 @@ base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- mozilla-foundation/
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metrics:
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- wer
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model-index:
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- name: Whisper Small Canontese X
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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
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type: mozilla-foundation/
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config:
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split: None
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args: 'config: zh-HK, split: test'
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metrics:
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- name: Wer
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type: wer
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value:
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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 Small Canontese X
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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## Model description
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@@ -69,9 +69,9 @@ The following hyperparameters were used during training:
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:-------:|
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| 0.
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| 0.
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| 0.
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### Framework versions
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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: Whisper Small Canontese X 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: Common Voice 16.1 and 17.0
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type: mozilla-foundation/common_voice_17_0
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config: yue
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split: None
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args: 'config: zh-HK, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 54.825384904243336
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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 Small Canontese X v2
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 and 17.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2264
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- Wer: 54.8254
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:-------:|
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| 0.2578 | 0.6954 | 1000 | 0.2680 | 61.4345 |
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| 0.0892 | 1.3908 | 2000 | 0.2376 | 57.3789 |
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| 0.0295 | 2.0862 | 3000 | 0.2264 | 54.8254 |
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### Framework versions
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