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--- |
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base_model: openai/whisper-medium |
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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 Medium 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 Medium Mnong |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the MnongAudio-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0471 |
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- Wer: 7.2593 |
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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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| 2.3012 | 0.1421 | 200 | 2.0190 | 142.3332 | |
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| 1.4133 | 0.2843 | 400 | 1.3463 | 99.4906 | |
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| 0.9797 | 0.4264 | 600 | 0.9503 | 80.8456 | |
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| 0.7402 | 0.5686 | 800 | 0.6821 | 62.0479 | |
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| 0.4908 | 0.7107 | 1000 | 0.4992 | 47.8349 | |
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| 0.3865 | 0.8529 | 1200 | 0.4090 | 42.6133 | |
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| 0.3031 | 0.9950 | 1400 | 0.3108 | 34.7937 | |
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| 0.203 | 1.1372 | 1600 | 0.2632 | 39.2511 | |
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| 0.1846 | 1.2793 | 1800 | 0.2209 | 28.3749 | |
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| 0.1313 | 1.4215 | 2000 | 0.1776 | 18.2119 | |
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| 0.0984 | 1.5636 | 2200 | 0.1525 | 18.8487 | |
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| 0.1009 | 1.7058 | 2400 | 0.1276 | 14.8242 | |
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| 0.0803 | 1.8479 | 2600 | 0.1034 | 12.1498 | |
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| 0.061 | 1.9900 | 2800 | 0.0910 | 11.7422 | |
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| 0.0327 | 2.1322 | 3000 | 0.0808 | 12.3535 | |
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| 0.026 | 2.2743 | 3200 | 0.0716 | 9.2970 | |
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| 0.024 | 2.4165 | 3400 | 0.0612 | 10.2649 | |
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| 0.0282 | 2.5586 | 3600 | 0.0552 | 8.0234 | |
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| 0.016 | 2.7008 | 3800 | 0.0488 | 7.8961 | |
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| 0.0237 | 2.8429 | 4000 | 0.0471 | 7.2593 | |
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### Framework versions |
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- Transformers 4.42.4 |
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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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