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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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 Tiny Hu v2 |
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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: 15.7367 |
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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 Tiny Hu v2 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1930 |
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- Wer Ortho: 17.3040 |
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- Wer: 15.7367 |
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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: 4e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 500 |
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- training_steps: 15000 |
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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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| 0.5487 | 0.33 | 1000 | 0.5970 | 55.5492 | 52.2206 | |
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| 0.3922 | 0.67 | 2000 | 0.4419 | 43.1109 | 39.9911 | |
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| 0.3242 | 1.0 | 3000 | 0.3662 | 37.2727 | 34.2040 | |
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| 0.2517 | 1.34 | 4000 | 0.3329 | 33.7890 | 30.8746 | |
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| 0.2455 | 1.67 | 5000 | 0.2925 | 30.6185 | 28.0196 | |
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| 0.1398 | 2.01 | 6000 | 0.2600 | 27.1709 | 24.5983 | |
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| 0.1421 | 2.34 | 7000 | 0.2491 | 26.1291 | 23.6347 | |
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| 0.1578 | 2.68 | 8000 | 0.2342 | 24.4761 | 22.0783 | |
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| 0.0732 | 3.01 | 9000 | 0.2163 | 22.1245 | 19.8547 | |
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| 0.0941 | 3.35 | 10000 | 0.2143 | 22.2058 | 19.8399 | |
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| 0.0936 | 3.68 | 11000 | 0.2094 | 20.5980 | 18.7756 | |
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| 0.0489 | 4.02 | 12000 | 0.2027 | 18.9630 | 17.2665 | |
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| 0.0548 | 4.35 | 13000 | 0.1981 | 18.4933 | 16.5491 | |
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| 0.0585 | 4.69 | 14000 | 0.1953 | 17.7195 | 15.7693 | |
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| 0.0356 | 5.02 | 15000 | 0.1930 | 17.3040 | 15.7367 | |
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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 2.16.1 |
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- Tokenizers 0.15.0 |
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