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---
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language:
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- ro
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license: mit
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base_model: openai/whisper-large-v3-turbo
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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_17_0
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metrics:
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- wer
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model-index:
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- name: Whisper Large_v2 RO CV17
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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: mozilla-foundation/common_voice_17_0
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args: 'config: ro, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 47.51015670342426
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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 Large_v2 RO CV17
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) 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: 1.6152
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- Wer: 47.5102
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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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| 0.5004 | 5.4945 | 1000 | 1.1554 | 106.2565 |
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| 0.0896 | 10.9890 | 2000 | 1.3810 | 51.0737 |
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| 0.0121 | 16.4835 | 3000 | 1.5371 | 49.9013 |
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| 0.0027 | 21.9780 | 4000 | 1.5901 | 49.1468 |
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| 0.0008 | 27.4725 | 5000 | 1.6152 | 47.5102 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.5.1+cu118
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- Datasets 3.1.0
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- Tokenizers 0.19.1
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