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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- 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: openai/whisper-large-v2
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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: common_voice_11_0
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config: es
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split: test
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args: es
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metrics:
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- name: Wer
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type: wer
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value: 5.288186684683748
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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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# openai/whisper-large-v2
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) 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: 0.1702
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- Wer: 5.2882
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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: 8
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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: 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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| 0.1738 | 0.1 | 1000 | 0.2031 | 7.0384 |
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| 0.2108 | 1.01 | 2000 | 0.1885 | 6.6668 |
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| 0.1599 | 1.11 | 3000 | 0.1814 | 6.5342 |
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| 0.0794 | 2.01 | 4000 | 0.1792 | 6.0314 |
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| 0.0477 | 2.11 | 5000 | 0.1936 | 6.1795 |
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| 0.0341 | 3.02 | 6000 | 0.2038 | 6.0113 |
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| 0.0264 | 3.12 | 7000 | 0.2111 | 5.8410 |
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| 0.0608 | 4.02 | 8000 | 0.1824 | 5.9067 |
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| 0.0523 | 4.12 | 9000 | 0.1768 | 5.3941 |
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| 0.0984 | 5.03 | 10000 | 0.1702 | 5.2882 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 2.0.0.dev20221210+cu117
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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