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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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base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_13_0
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metrics:
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- wer
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model-index:
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- name: whisper-small-dv
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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_13_0
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type: common_voice_13_0
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config: dv
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split: test
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args: dv
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metrics:
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- name: Wer
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type: wer
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value: 11.072086796258302
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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-dv
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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_13_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2738
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- Wer Ortho: 56.8842
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- Wer: 11.0721
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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: 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: constant_with_warmup
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- lr_scheduler_warmup_steps: 50
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- training_steps: 3000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
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| 0.1237 | 1.63 | 500 | 0.1702 | 63.0963 | 13.1429 |
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| 0.0494 | 3.26 | 1000 | 0.1662 | 57.8592 | 11.6285 |
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| 0.0315 | 4.89 | 1500 | 0.1894 | 58.3397 | 11.3937 |
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| 0.0121 | 6.51 | 2000 | 0.2257 | 57.7756 | 11.5502 |
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| 0.005 | 8.14 | 2500 | 0.2643 | 56.9747 | 11.1573 |
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| 0.0056 | 9.77 | 3000 | 0.2738 | 56.8842 | 11.0721 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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