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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-small
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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: tr
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split: test
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args: tr
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metrics:
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- name: Wer
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type: wer
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value: 16.634639647508685
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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-small
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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: 0.2615
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- Wer: 16.6346
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- Cer: 4.2839
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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: 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: 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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
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| 0.1412 | 0.08 | 400 | 0.2656 | 19.8335 | 5.2393 |
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| 0.0851 | 1.03 | 800 | 0.2382 | 18.6300 | 4.8916 |
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| 0.0525 | 1.11 | 1200 | 0.2532 | 19.1696 | 5.2238 |
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| 0.0163 | 2.07 | 1600 | 0.2447 | 17.2014 | 4.5840 |
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| 0.0202 | 3.02 | 2000 | 0.2472 | 17.1063 | 4.4935 |
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| 0.0075 | 3.1 | 2400 | 0.2503 | 17.0151 | 4.4318 |
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| 0.0039 | 4.05 | 2800 | 0.2514 | 16.7433 | 4.3655 |
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| 0.0038 | 5.01 | 3200 | 0.2565 | 16.8870 | 4.3582 |
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| 0.0023 | 5.09 | 3600 | 0.2590 | 16.6987 | 4.3337 |
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| 0.0013 | 6.04 | 4000 | 0.2576 | 16.6327 | 4.2853 |
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| 0.0011 | 6.12 | 4400 | 0.2647 | 16.9122 | 4.3556 |
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| 0.001 | 7.07 | 4800 | 0.2615 | 16.6346 | 4.2839 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.1.dev0
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- Tokenizers 0.13.2
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