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--- |
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base_model: openai/whisper-small |
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language: |
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- vi |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Small Mnong |
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results: [] |
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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 Mnong |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the MnongAudio-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1380 |
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- Wer: 29.9287 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 4000 |
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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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| 3.2102 | 0.1421 | 200 | 3.0988 | 153.0565 | |
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| 1.7796 | 0.2843 | 400 | 1.7393 | 146.0774 | |
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| 1.3216 | 0.4264 | 600 | 1.3372 | 109.1187 | |
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| 1.0883 | 0.5686 | 800 | 1.0383 | 101.5028 | |
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| 0.8187 | 0.7107 | 1000 | 0.8161 | 63.4997 | |
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| 0.652 | 0.8529 | 1200 | 0.6821 | 66.2252 | |
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| 0.5411 | 0.9950 | 1400 | 0.5551 | 58.2272 | |
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| 0.4082 | 1.1372 | 1600 | 0.4738 | 58.5074 | |
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| 0.359 | 1.2793 | 1800 | 0.4075 | 45.1859 | |
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| 0.2761 | 1.4215 | 2000 | 0.3466 | 43.9379 | |
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| 0.212 | 1.5636 | 2200 | 0.3002 | 42.0785 | |
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| 0.2192 | 1.7058 | 2400 | 0.2642 | 36.0927 | |
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| 0.1932 | 1.8479 | 2600 | 0.2269 | 39.3785 | |
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| 0.1541 | 1.9900 | 2800 | 0.2013 | 30.5400 | |
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| 0.0944 | 2.1322 | 3000 | 0.1894 | 36.6021 | |
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| 0.0848 | 2.2743 | 3200 | 0.1682 | 29.4447 | |
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| 0.0811 | 2.4165 | 3400 | 0.1565 | 28.0183 | |
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| 0.0899 | 2.5586 | 3600 | 0.1481 | 31.0749 | |
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| 0.0749 | 2.7008 | 3800 | 0.1409 | 25.6240 | |
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| 0.0737 | 2.8429 | 4000 | 0.1380 | 29.9287 | |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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