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README.md
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---
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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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-
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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:
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config: cmn_hans_cn
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split: test
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args: cmn_hans_cn
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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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#
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the
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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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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.0001 |
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### Framework versions
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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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- fleurs
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metrics:
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- wer
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model-index:
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- name: openai/whisper-small
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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: fleurs
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type: fleurs
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config: cmn_hans_cn
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split: test
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args: cmn_hans_cn
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metrics:
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- name: Wer
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type: wer
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value: 17.229965685827946
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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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# openai/whisper-small
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4330
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- Wer: 17.2300
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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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| 0.0005 | 76.0 | 1000 | 0.3573 | 16.6439 |
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| 0.0002 | 153.0 | 2000 | 0.3897 | 16.9749 |
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| 0.0001 | 230.0 | 3000 | 0.4125 | 17.2330 |
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| 0.0001 | 307.0 | 4000 | 0.4256 | 17.2451 |
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| 0.0001 | 384.0 | 5000 | 0.4330 | 17.2300 |
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### Framework versions
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