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--- |
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language: |
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- hi |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: openai/whisper-medium |
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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 medium Hi - Aa |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: 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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config: hi |
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split: test |
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args: 'config: hi, split: test' |
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metrics: |
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- type: wer |
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value: 24.227545923982053 |
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name: Wer |
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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 Hi - Aa |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) 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: 0.3556 |
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- Wer: 24.2275 |
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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: 5000 |
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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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| 0.0564 | 2.4450 | 1000 | 0.2346 | 26.9153 | |
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| 0.0159 | 4.8900 | 2000 | 0.2877 | 26.1619 | |
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| 0.0026 | 7.3350 | 3000 | 0.3198 | 24.9471 | |
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| 0.0002 | 9.7800 | 4000 | 0.3457 | 24.8074 | |
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| 0.0001 | 12.2249 | 5000 | 0.3556 | 24.2275 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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