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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: wav2vec2-xls-r-300m-CV8-ro
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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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# wav2vec2-xls-r-300m-CV8-ro
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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: 0.1619
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- Wer: 0.6045
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- Cer: 0.0479
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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: 0.0003
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 2000
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- num_epochs: 50.0
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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| 2.9736 | 3.62 | 500 | 2.9508 | 1.0 | 1.0 |
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| 1.3293 | 7.25 | 1000 | 0.3330 | 0.8407 | 0.0862 |
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| 0.956 | 10.87 | 1500 | 0.2042 | 0.6872 | 0.0602 |
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| 0.9509 | 14.49 | 2000 | 0.2184 | 0.7088 | 0.0652 |
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| 0.9272 | 18.12 | 2500 | 0.2312 | 0.7211 | 0.0703 |
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| 0.8561 | 21.74 | 3000 | 0.2158 | 0.6838 | 0.0631 |
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| 0.8258 | 25.36 | 3500 | 0.1970 | 0.6844 | 0.0601 |
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| 0.7993 | 28.98 | 4000 | 0.1895 | 0.6698 | 0.0577 |
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| 0.7525 | 32.61 | 4500 | 0.1845 | 0.6453 | 0.0550 |
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| 0.7211 | 36.23 | 5000 | 0.1781 | 0.6274 | 0.0531 |
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| 0.677 | 39.85 | 5500 | 0.1732 | 0.6188 | 0.0514 |
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| 0.6517 | 43.48 | 6000 | 0.1691 | 0.6177 | 0.0503 |
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| 0.6326 | 47.1 | 6500 | 0.1619 | 0.6045 | 0.0479 |
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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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