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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-small
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_17_0
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metrics:
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- wer
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model-index:
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- name: Whisper small vi - Ox
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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: common_voice_17_0
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type: common_voice_17_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: 31.26665341022072
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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 vi - Ox
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0138
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- Wer: 31.2667
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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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- num_epochs: 3.0
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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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| 0.2276 | 0.08 | 1000 | 0.7506 | 29.8509 |
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| 0.1768 | 0.16 | 2000 | 0.8114 | 31.2189 |
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| 0.1828 | 0.24 | 3000 | 0.8569 | 31.2985 |
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| 0.1632 | 0.32 | 4000 | 0.8523 | 31.9268 |
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| 0.1566 | 0.4 | 5000 | 0.9062 | 31.9149 |
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| 0.1532 | 0.48 | 6000 | 0.8914 | 31.4496 |
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| 0.1593 | 0.56 | 7000 | 0.9342 | 31.9825 |
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| 0.1411 | 0.64 | 8000 | 0.9412 | 32.0302 |
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| 0.1531 | 0.72 | 9000 | 0.9456 | 31.6206 |
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| 0.1246 | 0.8 | 10000 | 0.9452 | 31.7240 |
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| 0.1336 | 0.88 | 11000 | 0.9622 | 31.1195 |
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| 0.1392 | 0.96 | 12000 | 0.9638 | 31.3939 |
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| 0.0725 | 1.04 | 13000 | 1.0032 | 31.5649 |
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| 0.0838 | 1.12 | 14000 | 1.0346 | 31.7916 |
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| 0.0766 | 1.2 | 15000 | 1.0138 | 31.2667 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.4.1
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- Datasets 3.0.1
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- Tokenizers 0.15.2
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