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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: 0.3726 |
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- Wer: 37.8757 |
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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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| 3.2302 | 0.2915 | 200 | 3.1116 | 239.5568 | |
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| 1.7352 | 0.5831 | 400 | 1.7781 | 96.5359 | |
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| 1.2762 | 0.8746 | 600 | 1.3745 | 100.9170 | |
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| 0.9605 | 1.1662 | 800 | 1.1114 | 89.1747 | |
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| 0.8392 | 1.4577 | 1000 | 0.9010 | 81.3551 | |
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| 0.6779 | 1.7493 | 1200 | 0.7770 | 64.3912 | |
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| 0.3956 | 2.0408 | 1400 | 0.6635 | 63.0922 | |
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| 0.35 | 2.3324 | 1600 | 0.6001 | 55.6037 | |
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| 0.3225 | 2.6239 | 1800 | 0.5402 | 59.2970 | |
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| 0.326 | 2.9155 | 2000 | 0.4830 | 48.0387 | |
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| 0.143 | 3.2070 | 2200 | 0.4697 | 41.7983 | |
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| 0.119 | 3.4985 | 2400 | 0.4404 | 41.5181 | |
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| 0.1123 | 3.7901 | 2600 | 0.4205 | 44.4727 | |
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| 0.0709 | 4.0816 | 2800 | 0.4009 | 38.9710 | |
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| 0.0764 | 4.3732 | 3000 | 0.3959 | 39.8370 | |
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| 0.0587 | 4.6647 | 3200 | 0.3800 | 35.8889 | |
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| 0.0627 | 4.9563 | 3400 | 0.3771 | 37.6465 | |
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| 0.0326 | 5.2478 | 3600 | 0.3754 | 35.3795 | |
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| 0.0355 | 5.5394 | 3800 | 0.3751 | 39.4549 | |
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| 0.0331 | 5.8309 | 4000 | 0.3726 | 37.8757 | |
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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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