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--- |
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base_model: openai/whisper-base |
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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 Base 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 Base Mnong |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the MnongAudio-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5864 |
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- Wer: 73.4845 |
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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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| 2.7525 | 0.1421 | 200 | 2.6537 | 416.5818 | |
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| 2.2459 | 0.2843 | 400 | 2.2237 | 158.5838 | |
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| 1.8682 | 0.4264 | 600 | 1.8896 | 237.7483 | |
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| 1.7212 | 0.5686 | 800 | 1.6295 | 110.0866 | |
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| 1.4164 | 0.7107 | 1000 | 1.4443 | 108.9913 | |
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| 1.2698 | 0.8529 | 1200 | 1.3000 | 91.3653 | |
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| 1.1479 | 0.9950 | 1400 | 1.1657 | 102.3688 | |
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| 1.0034 | 1.1372 | 1600 | 1.0799 | 84.6918 | |
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| 0.945 | 1.2793 | 1800 | 0.9844 | 85.7106 | |
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| 0.8249 | 1.4215 | 2000 | 0.8974 | 87.1880 | |
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| 0.726 | 1.5636 | 2200 | 0.8412 | 92.9699 | |
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| 0.7561 | 1.7058 | 2400 | 0.7859 | 80.8202 | |
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| 0.6884 | 1.8479 | 2600 | 0.7328 | 85.3031 | |
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| 0.6329 | 1.9900 | 2800 | 0.6872 | 80.9985 | |
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| 0.5129 | 2.1322 | 3000 | 0.6672 | 76.4901 | |
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| 0.5361 | 2.2743 | 3200 | 0.6369 | 78.2985 | |
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| 0.482 | 2.4165 | 3400 | 0.6178 | 75.9042 | |
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| 0.5211 | 2.5586 | 3600 | 0.6030 | 79.3938 | |
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| 0.4749 | 2.7008 | 3800 | 0.5905 | 76.0316 | |
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| 0.4648 | 2.8429 | 4000 | 0.5864 | 73.4845 | |
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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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