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--- |
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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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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_0 |
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language: |
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- hu |
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widget: |
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- example_title: Sample 1 |
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src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac |
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- example_title: Sample 2 |
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src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac |
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metrics: |
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- wer |
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pipeline_tag: automatic-speech-recognition |
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model-index: |
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- name: Whisper Small Hungarian |
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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 16.0 - Hungarian |
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type: mozilla-foundation/common_voice_16_0 |
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config: hu |
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split: test |
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args: hu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 18.8314 |
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verified: true |
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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 Hungarian (training in progress) |
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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 16 dataset of Mozilla Foundation. |
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It achieves the following results on the evaluation set: |
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Tempolary at step 3500: |
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- Wer: 18.8314 |
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Unfortunatly the colab disconected, this is the end... :( maybe later continue |
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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: 1.25e-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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- 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: 400 |
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- planed training_steps: 6000 |
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- executed steps: 3500 only (colab dc) |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Steps | Training Loss | Validation Loss | Wer Ortho | Wer | |
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|:-----:|:-------------:|:---------------:|:---------:|:---------:| |
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| 500 | 0.354600 | 0.349688 | 34.385555 | 31.246555 | |
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| 1000 | 0.283800 | 0.290485 | 29.696507 | 26.625776 | |
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| 1500 | 0.248800 | 0.255122 | 26.360826 | 23.300925 | |
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| 2000 | 0.198300 | 0.234539 | 24.557530 | 21.714145 | |
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| 2500 | 0.196300 | 0.224310 | 23.557423 | 20.698512 | |
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| 3000 | 0.153000 | 0.210894 | 22.088291 | 19.231356 | |
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| 3500 | 0.109100 | 0.210817 | 21.465313 | 18.831435 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
