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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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- whisper-event |
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- hf-asr-leaderboard |
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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: openai/whisper-medium |
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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: common_voice_11_0 |
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config: ba |
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split: test |
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args: ba |
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metrics: |
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- name: Wer |
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type: wer |
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value: 19.56338265908963 |
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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-medium](https://huggingface.co/openai/whisper-medium) 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: 0.2195 |
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- Wer: 19.56 |
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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: 2 |
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- eval_batch_size: 1 |
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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: 10000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Epoch | Step | Wer | |
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|:-------------:|:-----:|:----:| |
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| 0.1 | 1000 | 43.61 | |
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| 0.2 | 2000 | 36.79 | |
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| 0.3 | 3000 | 33.05 | |
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| 0.4 | 4000 | 29.53 | |
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| 0.5 | 5000 | 26.01 | |
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| 0.6 | 6000 | 23.44 | |
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| 0.7 | 7000 | 22.22 | |
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| 0.8 | 8000 | 21.88 | |
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| 0.9 | 9000 | 20.53 | |
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| 1.0 | 10000 | 19.56 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
