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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: 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: en
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split: test
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args: en
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metrics:
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- name: Wer
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type: wer
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value: 12.141503068470264
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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: 0.3104
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- Wer: 12.1415
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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: 40000
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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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| 0.1577 | 0.06 | 2500 | 0.4077 | 16.2349 |
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| 0.2244 | 0.12 | 5000 | 0.3698 | 14.7325 |
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| 0.3231 | 0.19 | 7500 | 0.3434 | 13.7448 |
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| 0.2536 | 0.25 | 10000 | 0.3406 | 13.4981 |
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| 0.2234 | 0.31 | 12500 | 0.3510 | 14.1304 |
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| 0.1989 | 0.38 | 15000 | 0.3388 | 13.6394 |
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| 0.2449 | 0.44 | 17500 | 0.3394 | 13.4293 |
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| 0.2302 | 0.5 | 20000 | 0.3198 | 12.5020 |
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| 0.213 | 0.56 | 22500 | 0.3167 | 12.4904 |
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| 0.2395 | 0.62 | 25000 | 0.3145 | 12.7533 |
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| 0.1152 | 0.69 | 27500 | 0.3181 | 12.6087 |
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| 0.0901 | 1.01 | 30000 | 0.3134 | 12.3240 |
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| 0.1595 | 1.07 | 32500 | 0.3107 | 12.0213 |
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| 0.1249 | 1.13 | 35000 | 0.3131 | 12.0869 |
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| 0.1404 | 1.2 | 37500 | 0.3117 | 12.4635 |
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| 0.1812 | 1.26 | 40000 | 0.3104 | 12.1415 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu117
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- Datasets 2.11.1.dev0
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- Tokenizers 0.13.2
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