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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 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: 32.2247 |
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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 Hungarian |
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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 dataset of Mozilla Foundation. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3628 |
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- Wer Ortho: 34.7985 |
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- Wer: 32.2247 |
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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: 3.75e-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: 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 Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| |
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| 0.7288 | 0.17 | 500 | 0.7093 | 59.8298 | 57.4443 | |
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| 0.5483 | 0.33 | 1000 | 0.5648 | 52.3541 | 49.3122 | |
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| 0.4647 | 0.5 | 1500 | 0.4912 | 46.1159 | 42.9533 | |
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| 0.3925 | 0.67 | 2000 | 0.4463 | 42.8674 | 39.9838 | |
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| 0.3682 | 0.84 | 2500 | 0.4258 | 41.1739 | 38.0487 | |
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| 0.3219 | 1.0 | 3000 | 0.3932 | 37.5828 | 34.7286 | |
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| 0.2638 | 1.17 | 3500 | 0.3909 | 37.8060 | 35.0311 | |
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| 0.2507 | 1.34 | 4000 | 0.3881 | 36.7856 | 34.1199 | |
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| 0.2483 | 1.51 | 4500 | 0.3737 | 35.5778 | 32.9881 | |
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| 0.2444 | 1.67 | 5000 | 0.3628 | 34.7985 | 32.2247 | |
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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 |
