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---
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library_name: transformers
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language:
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- de
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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_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper Large De - Krish Kalra
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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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config: de
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split: test
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args: 'config: de, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 9.29112181693049
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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 De - Krish Kalra
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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 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2176
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- Wer: 9.2911
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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: 5
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- num_epochs: 5
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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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| 0.1148 | 1.0 | 300 | 0.1876 | 10.6676 |
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| 0.1281 | 2.0 | 600 | 0.2023 | 11.0805 |
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| 0.032 | 3.0 | 900 | 0.2043 | 10.1170 |
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| 0.0015 | 4.0 | 1200 | 0.2194 | 9.7729 |
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| 0.0005 | 5.0 | 1500 | 0.2176 | 9.2911 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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