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--- |
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language: |
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- pl |
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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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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium PL |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: 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: pl |
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split: test |
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args: pl |
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metrics: |
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- type: wer |
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value: 8.71 |
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name: WER |
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- type: wer_without_norm |
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value: 22.0 |
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name: WER unnormalized |
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- type: cer |
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value: 2.41 |
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name: CER |
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- type: mer |
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value: 8.65 |
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name: MER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: facebook/voxpopuli |
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type: facebook/voxpopuli |
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config: pl |
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split: test |
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metrics: |
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- type: wer |
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value: 11.99 |
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name: WER |
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- type: wer_without_norm |
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value: 30.9 |
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name: WER unnormalized |
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- type: cer |
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value: 6.54 |
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name: CER |
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- type: mer |
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value: 11.68 |
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name: MER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: google/fleurs |
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type: google/fleurs |
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config: pl_pl |
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split: test |
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metrics: |
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- type: wer |
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value: 10.89 |
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name: WER |
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- type: wer_without_norm |
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value: 30.7 |
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name: WER unnormalized |
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- type: cer |
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value: 4.04 |
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name: CER |
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- type: mer |
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value: 10.8 |
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name: MER |
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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 Medium PL |
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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 and the FLEURS datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3947 |
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- Wer: 8.6872 |
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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: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 8000 |
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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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| 0.0805 | 0.48 | 500 | 0.2556 | 10.4888 | |
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| 0.0685 | 0.96 | 1000 | 0.2462 | 10.7608 | |
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| 0.0356 | 1.45 | 1500 | 0.2561 | 9.6728 | |
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| 0.0337 | 1.93 | 2000 | 0.2327 | 9.6459 | |
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| 0.017 | 2.41 | 2500 | 0.2444 | 9.9464 | |
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| 0.0179 | 2.9 | 3000 | 0.2554 | 9.6476 | |
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| 0.0056 | 3.38 | 3500 | 0.3001 | 9.3638 | |
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| 0.007 | 3.86 | 4000 | 0.2809 | 9.2245 | |
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| 0.0033 | 4.34 | 4500 | 0.3235 | 9.3437 | |
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| 0.0024 | 4.83 | 5000 | 0.3148 | 9.0633 | |
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| 0.0008 | 5.31 | 5500 | 0.3416 | 9.0112 | |
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| 0.0011 | 5.79 | 6000 | 0.3876 | 9.1858 | |
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| 0.0004 | 6.27 | 6500 | 0.3745 | 8.7292 | |
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| 0.0003 | 6.76 | 7000 | 0.3704 | 9.0314 | |
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| 0.0003 | 7.24 | 7500 | 0.3929 | 8.6553 | |
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| 0.0002 | 7.72 | 8000 | 0.3947 | 8.6872 | |
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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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