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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: ps_af
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split: test
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args: ps_af
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metrics:
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- name: Wer
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type: wer
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value: 57.
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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: 1.
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- Wer: 57.
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps:
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- mixed_precision_training: Native AMP
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### Training results
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| 0.8565 | 7.41 | 200 | 0.9367 | 61.9930 |
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| 0.2246 | 11.11 | 300 | 0.9642 | 58.8302 |
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| 0.054 | 14.81 | 400 | 1.0876 | 57.9903 |
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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: ps_af
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split: test
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args: ps_af
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metrics:
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- name: Wer
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type: wer
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value: 57.87681598062954
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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: 1.1798
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- Wer: 57.8768
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 500
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- mixed_precision_training: Native AMP
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### Training results
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| 0.8565 | 7.41 | 200 | 0.9367 | 61.9930 |
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| 0.2246 | 11.11 | 300 | 0.9642 | 58.8302 |
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| 0.054 | 14.81 | 400 | 1.0876 | 57.9903 |
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| 0.0159 | 18.52 | 500 | 1.1798 | 57.8768 |
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### Framework versions
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