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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
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model-index:
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- name: ''
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results: []
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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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#
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2852
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- Wer: 0.2396
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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: 7e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: 1000
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- num_epochs: 100.0
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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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| 6.9294 | 6.1 | 500 | 2.9712 | 1.0 |
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| 2.8305 | 12.2 | 1000 | 1.7073 | 0.9479 |
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| 1.4795 | 18.29 | 1500 | 0.5756 | 0.6397 |
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| 1.3433 | 24.39 | 2000 | 0.4968 | 0.5424 |
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| 1.1766 | 30.49 | 2500 | 0.4185 | 0.4743 |
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| 1.0017 | 36.59 | 3000 | 0.3303 | 0.3578 |
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| 0.9358 | 42.68 | 3500 | 0.3003 | 0.3051 |
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| 0.8358 | 48.78 | 4000 | 0.3045 | 0.2884 |
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| 0.7647 | 54.88 | 4500 | 0.2866 | 0.2677 |
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| 0.7482 | 60.98 | 5000 | 0.2829 | 0.2585 |
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| 0.6943 | 67.07 | 5500 | 0.2782 | 0.2478 |
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| 0.6586 | 73.17 | 6000 | 0.2911 | 0.2537 |
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| 0.6425 | 79.27 | 6500 | 0.2817 | 0.2462 |
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| 0.6067 | 85.37 | 7000 | 0.2910 | 0.2436 |
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| 0.5974 | 91.46 | 7500 | 0.2875 | 0.2430 |
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| 0.5812 | 97.56 | 8000 | 0.2852 | 0.2396 |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2.dev0
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- Tokenizers 0.11.0
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