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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 11000: |
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- Wer: 8.4969 |
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Unfortunatly the colab disconected, this is the end... :( maybe later continue |
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My own hungarian language specific compare test result (on CV11): |
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| Modell | WER | CER | NORMALISED WER | NORMALISED CER | |
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|:----------------------------------:|:-------------:|:---------------:|:--------------:|:--------------:| |
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| openai/whisper-tiny | 112.1 | 51.33 | 108.79 | 49.64 | |
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| openai/whisper-base | 95.87 | 42.84 | 95.68 | 41.38 | |
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| openai/whisper-small | 53.65 | 15.89 | 49.8 | 14.63 | |
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| Hungarians/whisper-tiny-cv16-hu | 30.57 | 8.52 | 27.71 | 7.86 | |
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| Hungarians/whisper-tiny-cv16-hu-v2 | 16.99 | 4.98 | 15.27 | 4.49 | |
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| Hungarians/whisper-base-cv16-hu | 15.55 | 4.07 | 13.68 | 3.67 | |
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| Hungarians/whisper-base-cv16-hu-v2 | 12.63 | 3.55 | 11.39 | 3.26 | |
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| Hungarians/whisper-small-cv16-hu | 17.86 | 4.1 | 15.27 | 3.58 | |
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| sarpba/whisper-small-cv16-v1.5-hu| 9.94 | 2.41 | 8.50 | 2.14 | |
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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: 15000 |
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- executed steps: 11000 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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### 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 |
