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README.md
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---
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language:
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- ha
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- mozilla-foundation/common_voice_8_0
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- generated_from_trainer
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datasets:
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- common_voice
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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
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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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:
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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:
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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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| 1.
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| 0.
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### Framework versions
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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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#
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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: 0.4939
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- Wer: 0.5737
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 7.5e-05
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- train_batch_size: 8
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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: 32
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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: 80.0
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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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| 3.1674 | 8.33 | 500 | 3.0295 | 1.0 |
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| 2.6987 | 16.66 | 1000 | 2.6878 | 1.0 |
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| 1.3454 | 24.99 | 1500 | 0.6814 | 0.6981 |
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| 1.1227 | 33.33 | 2000 | 0.5791 | 0.6513 |
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| 0.9972 | 41.66 | 2500 | 0.5235 | 0.5718 |
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| 0.9123 | 49.99 | 3000 | 0.5104 | 0.5633 |
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| 0.836 | 58.33 | 3500 | 0.4927 | 0.5580 |
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| 0.7725 | 66.66 | 4000 | 0.5078 | 0.5779 |
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| 0.7297 | 74.99 | 4500 | 0.4939 | 0.5737 |
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### Framework versions
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