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---
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library_name: transformers
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language:
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- ro
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license: apache-2.0
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base_model: openai/whisper-tiny
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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 Tiny Ro (local) - Augustin Jianu
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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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config: ro
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split: test
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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: 37.48352861569144
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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 Tiny Ro (local) - Augustin Jianu
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) 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: 0.5978
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- Wer: 37.4835
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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 OptimizerNames.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: 500
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- training_steps: 10000
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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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| 0.4417 | 1.7730 | 1000 | 0.5327 | 43.8513 |
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| 0.1813 | 3.5461 | 2000 | 0.4666 | 38.8689 |
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| 0.0751 | 5.3191 | 3000 | 0.4645 | 36.5006 |
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| 0.0326 | 7.0922 | 4000 | 0.4803 | 36.4614 |
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| 0.0234 | 8.8652 | 5000 | 0.5087 | 36.5148 |
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| 0.0082 | 10.6383 | 6000 | 0.5424 | 36.6252 |
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| 0.0042 | 12.4113 | 7000 | 0.5650 | 37.6509 |
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| 0.0029 | 14.1844 | 8000 | 0.5809 | 36.8710 |
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| 0.0025 | 15.9574 | 9000 | 0.5922 | 38.1495 |
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| 0.0021 | 17.7305 | 10000 | 0.5978 | 37.4835 |
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### Framework versions
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- Transformers 4.48.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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