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: output1
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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: nl
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split: test
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args: nl
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metrics:
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- name: Wer
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type: wer
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value: 5.895082837397793
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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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# output1
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) 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: 0.1310
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- Wer: 5.8951
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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: 4
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- eval_batch_size: 4
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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: 12000
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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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| 0.138 | 0.08 | 1000 | 0.2101 | 11.5288 |
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| 0.121 | 0.17 | 2000 | 0.1987 | 10.4458 |
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| 0.1413 | 0.25 | 3000 | 0.1956 | 10.4672 |
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| 0.1158 | 0.33 | 4000 | 0.1778 | 9.3729 |
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| 0.1056 | 0.42 | 5000 | 0.1795 | 9.7792 |
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| 0.056 | 1.05 | 6000 | 0.1560 | 7.6927 |
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| 0.0323 | 1.14 | 7000 | 0.1460 | 7.1445 |
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| 0.0213 | 1.22 | 8000 | 0.1491 | 7.2844 |
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| 0.051 | 1.3 | 9000 | 0.1457 | 6.9587 |
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| 0.0196 | 1.39 | 10000 | 0.1420 | 6.6086 |
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| 0.019 | 2.02 | 11000 | 0.1303 | 6.0553 |
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| 0.0124 | 2.11 | 12000 | 0.1310 | 5.8951 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu117
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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