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--- |
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library_name: transformers |
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language: |
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- sw |
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widget: |
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- example_title: speech sample 1 |
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src: https://cdn-media.huggingface.co/speech_samples/sample1.flac |
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- example_title: speech sample 2 |
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src: https://cdn-media.huggingface.co/speech_samples/sample2.flac |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small SW-eolang |
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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 17 |
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type: mozilla-foundation/common_voice_17_0 |
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config: sw |
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split: test |
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args: sw |
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metrics: |
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- name: Wer |
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type: wer |
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value: 27.951115548558043 |
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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 SW-eolang |
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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 17 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5136 |
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- Wer Ortho: 36.8520 |
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- Wer: 27.9511 |
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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: 16 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 4000 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
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| 0.4894 | 0.1721 | 500 | 0.7495 | 47.1590 | 39.6183 | |
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| 0.4068 | 0.3441 | 1000 | 0.6356 | 44.4535 | 36.3763 | |
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| 0.4137 | 0.5162 | 1500 | 0.5934 | 41.9094 | 33.4866 | |
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| 0.3759 | 0.6882 | 2000 | 0.5590 | 41.4031 | 33.1765 | |
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| 0.38 | 0.8603 | 2500 | 0.5293 | 37.2958 | 28.8699 | |
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| 0.2027 | 1.0323 | 3000 | 0.5235 | 37.4755 | 29.0340 | |
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| 0.2089 | 1.2044 | 3500 | 0.5149 | 35.8239 | 27.4845 | |
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| 0.2282 | 1.3765 | 4000 | 0.5136 | 36.8520 | 27.9511 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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