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---
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language:
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- english
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license: apache-2.0
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base_model: openai/whisper-small
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tags:
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- hf-asr-leaderboard
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper Small en
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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 11.0
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type: mozilla-foundation/common_voice_11_0
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config: null
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split: None
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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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value: 0.0
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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 en
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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 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2396
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- Wer: 0.0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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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: 5
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- training_steps: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| No log | 10.0 | 10 | 2.7433 | 92.3077 |
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| No log | 20.0 | 20 | 1.2396 | 0.0 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.2
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- Tokenizers 0.13.3
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