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update model card README.md
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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: whisper-small-pt-cv11-v5
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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: pt
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split: test
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args: pt
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metrics:
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- name: Wer
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type: wer
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value: 15.22342064714946
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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-small-pt-cv11-v5
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 0.3799
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- Wer: 15.2234
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- Cer: 6.1647
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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: 5e-06
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- train_batch_size: 32
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- eval_batch_size: 16
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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: 1000
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
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| 0.2817 | 0.92 | 500 | 0.3352 | 15.9476 | 6.3609 |
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| 0.2245 | 1.84 | 1000 | 0.3047 | 15.0231 | 5.9326 |
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| 0.1587 | 2.76 | 1500 | 0.2985 | 15.0847 | 5.9326 |
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| 0.1181 | 3.68 | 2000 | 0.3056 | 14.6841 | 5.8856 |
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| 0.0741 | 4.6 | 2500 | 0.3162 | 14.9923 | 5.9906 |
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| 0.0438 | 5.52 | 3000 | 0.3466 | 15.4700 | 6.2255 |
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| 0.0294 | 6.45 | 3500 | 0.3799 | 15.2234 | 6.1647 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.12.1+cu116
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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