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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:
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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-tiny](https://huggingface.co/openai/whisper-tiny) on the
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It achieves the following results on the evaluation set:
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- Loss: 2.
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- Wer:
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## Model description
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- seed: 42
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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:
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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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| 2.4773 | 42.86 | 300 | 2.4649 | 449.5006 |
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| 2.3142 | 57.14 | 400 | 2.3466 | 473.6002 |
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| 2.2942 | 71.43 | 500 | 2.3101 | 485.9867 |
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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-tiny
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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: 497.22306295399517
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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-tiny
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0279
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- Wer: 497.2231
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## Model description
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- seed: 42
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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: 700
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- mixed_precision_training: Native AMP
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### Training results
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| 2.4773 | 42.86 | 300 | 2.4649 | 449.5006 |
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| 2.3142 | 57.14 | 400 | 2.3466 | 473.6002 |
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| 2.2942 | 71.43 | 500 | 2.3101 | 485.9867 |
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| 2.0644 | 85.71 | 600 | 2.0926 | 491.4800 |
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| 1.9799 | 100.0 | 700 | 2.0279 | 497.2231 |
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### Framework versions
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