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--- |
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library_name: transformers |
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language: |
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- hi |
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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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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Ori vi |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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args: 'config: hi, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 15.251862231728003 |
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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 Ori vi |
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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 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4021 |
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- Wer: 15.2519 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 200 |
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- training_steps: 1000 |
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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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| 0.458 | 0.2222 | 100 | 0.4649 | 16.8154 | |
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| 0.4314 | 0.4444 | 200 | 0.4266 | 16.4319 | |
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| 0.4275 | 0.6667 | 300 | 0.4166 | 15.5542 | |
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| 0.3946 | 0.8889 | 400 | 0.4107 | 15.5764 | |
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| 0.2151 | 1.1111 | 500 | 0.4051 | 15.5616 | |
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| 0.2383 | 1.3333 | 600 | 0.4014 | 15.3551 | |
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| 0.2176 | 1.5556 | 700 | 0.3979 | 15.5395 | |
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| 0.2271 | 1.7778 | 800 | 0.3996 | 15.2371 | |
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| 0.222 | 2.0 | 900 | 0.3966 | 15.4141 | |
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| 0.1469 | 2.2222 | 1000 | 0.4021 | 15.2519 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.0 |
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