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--- |
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language: |
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- vi |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- whisper-event |
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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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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Vietnamese |
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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: mozilla-foundation/common_voice_16_0 vi |
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type: mozilla-foundation/common_voice_16_0 |
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config: vi |
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split: test |
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args: vi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 37.80239886155723 |
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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 Base Vietnamese |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 vi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7770 |
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- Wer: 37.8024 |
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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: 5e-07 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 10000 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
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| 0.6043 | 33.0 | 500 | 0.9039 | 42.6408 | |
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| 0.2836 | 66.0 | 1000 | 0.7761 | 38.3106 | |
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| 0.1593 | 99.0 | 1500 | 0.7770 | 37.8024 | |
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| 0.0835 | 133.0 | 2000 | 0.8019 | 37.8634 | |
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| 0.0395 | 166.0 | 2500 | 0.8317 | 38.1582 | |
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| 0.0217 | 199.0 | 3000 | 0.8563 | 38.2395 | |
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| 0.0146 | 233.0 | 3500 | 0.8744 | 38.2801 | |
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| 0.0107 | 266.0 | 4000 | 0.8893 | 38.4733 | |
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| 0.0082 | 299.0 | 4500 | 0.9031 | 38.3310 | |
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| 0.0065 | 333.0 | 5000 | 0.9155 | 38.4326 | |
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| 0.0053 | 366.0 | 5500 | 0.9267 | 38.6156 | |
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| 0.0044 | 399.0 | 6000 | 0.9381 | 38.7579 | |
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| 0.0037 | 433.0 | 6500 | 0.9486 | 38.7782 | |
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| 0.0032 | 466.0 | 7000 | 0.9580 | 39.0120 | |
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| 0.0028 | 499.0 | 7500 | 0.9669 | 39.1441 | |
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| 0.0025 | 533.0 | 8000 | 0.9747 | 39.1746 | |
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| 0.0022 | 566.0 | 8500 | 0.9810 | 39.2864 | |
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| 0.0021 | 599.0 | 9000 | 0.9866 | 39.2763 | |
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| 0.002 | 633.0 | 9500 | 0.9899 | 39.3271 | |
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| 0.0019 | 666.0 | 10000 | 0.9911 | 39.3271 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.0 |
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