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README.md
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---
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language:
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- hi
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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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- 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 Small te
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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: null
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split: None
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args: 'config: hi, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 105.71808510638299
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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 te
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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: 0.4158
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- Wer: 105.7181
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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-06
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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: 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: 100
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- training_steps: 500
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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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| 1.5803 | 1.75 | 100 | 1.4660 | 135.6383 |
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| 0.7665 | 3.51 | 200 | 0.6849 | 114.4947 |
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| 0.5158 | 5.26 | 300 | 0.4969 | 125.3989 |
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| 0.4441 | 7.02 | 400 | 0.4337 | 109.5745 |
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| 0.4234 | 8.77 | 500 | 0.4158 | 105.7181 |
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### Framework versions
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- Transformers 4.29.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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