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--- |
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language: |
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- et |
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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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- 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 et - Common Voice+FLEURS |
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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, FLEURS |
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type: mozilla-foundation/common_voice_11_0 |
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config: et |
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split: train |
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metrics: |
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- name: Wer |
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type: wer |
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value: 42.48444526581655 |
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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 et - Common Voice+FLEURS |
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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, FLEURS dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8754 |
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- Wer: 42.4844 |
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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: 64 |
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- eval_batch_size: 32 |
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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: 5000 |
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- mixed_precision_training: Native AMP |
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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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| 0.0094 | 10.0 | 1000 | 0.7125 | 43.4085 | |
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| 0.0024 | 20.01 | 2000 | 0.7960 | 42.1795 | |
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| 0.0012 | 30.01 | 3000 | 0.8237 | 41.8961 | |
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| 0.0006 | 40.02 | 4000 | 0.8627 | 41.7853 | |
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| 0.0004 | 51.0 | 5000 | 0.8754 | 42.4844 | |
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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 |
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