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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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metrics: |
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- wer |
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base_model: openai/whisper-medium |
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model-index: |
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- name: Whisper Small 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: 8.85 |
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name: WER |
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- type: wer_without_norm |
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value: 21.75 |
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name: WER unnormalized |
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- type: cer |
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value: 2.63 |
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name: CER |
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- type: mer |
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value: 8.76 |
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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: 12.18 |
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name: WER |
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- type: wer_without_norm |
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value: 32.17 |
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name: WER unnormalized |
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- type: cer |
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value: 6.99 |
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name: CER |
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- type: mer |
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value: 11.84 |
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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: 12.77 |
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name: WER |
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- type: wer_without_norm |
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value: 32.37 |
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name: WER unnormalized |
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- type: cer |
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value: 5.87 |
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name: CER |
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- type: mer |
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value: 12.52 |
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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 Small 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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3739 |
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- Wer: 8.5898 |
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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: 32 |
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- eval_batch_size: 16 |
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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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| 0.0474 | 1.1 | 1000 | 0.2561 | 9.4612 | |
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| 0.0119 | 3.09 | 2000 | 0.2901 | 8.9726 | |
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| 0.0045 | 5.08 | 3000 | 0.3151 | 8.8870 | |
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| 0.0007 | 7.07 | 4000 | 0.4218 | 8.6032 | |
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| 0.0005 | 9.07 | 5000 | 0.3739 | 8.5898 | |
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### Evaluation results |
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When tested on diffrent polish ASR datasets (splits: test), this model achieves the following results: |
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| Dataset | WER | WER unnormalized | CER | MER | |
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|:-----------------:|:-----:|:----------------:|:-----:|:-----:| |
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|common_voice_11_0 | 8.85 | 21.75 | 2.63 | 8.76 | |
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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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