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--- |
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language: |
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- pl |
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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 Large v2 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: 7.280175959972464 |
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name: WER |
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- type: wer |
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value: 7.31 |
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name: WER |
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- type: wer_without_norm |
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value: 20.18 |
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name: WER unnormalized |
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- type: cer |
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value: 2.08 |
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name: CER |
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- type: mer |
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value: 7.27 |
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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: 9.61 |
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name: WER |
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- type: wer_without_norm |
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value: 30.33 |
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name: WER unnormalized |
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- type: cer |
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value: 5.5 |
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name: CER |
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- type: mer |
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value: 9.45 |
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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: 8.68 |
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name: WER |
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- type: wer_without_norm |
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value: 29.33 |
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name: WER unnormalized |
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- type: cer |
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value: 3.63 |
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name: CER |
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- type: mer |
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value: 8.62 |
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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 Large v2 PL |
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This model is a fine-tuned version of [bardsai/whisper-large-v2-pl](https://huggingface.co/bardsai/whisper-large-v2-pl) 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: 0.3684 |
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- Wer: 7.2802 |
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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: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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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: 2100 |
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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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| 0.0047 | 1.35 | 700 | 0.3428 | 8.5562 | |
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| 0.0011 | 2.7 | 1400 | 0.3605 | 7.5505 | |
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| 0.0003 | 4.05 | 2100 | 0.3684 | 7.2802 | |
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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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