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README.md
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Cer: 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: 2
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- eval_batch_size: 8
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- seed: 42
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Cer
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### Framework versions
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 14.2905
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- Cer: 1.0
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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: 4e-55
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Cer |
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| 6.6387 | 0.74 | 500 | 14.2905 | 1.0 |
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| 6.7215 | 1.48 | 1000 | 14.2905 | 1.0 |
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| 6.6215 | 2.22 | 1500 | 14.2905 | 1.0 |
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| 6.5914 | 2.96 | 2000 | 14.2905 | 1.0 |
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| 6.8135 | 3.7 | 2500 | 14.2905 | 1.0 |
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| 6.5716 | 4.44 | 3000 | 14.2905 | 1.0 |
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| 6.6272 | 5.19 | 3500 | 14.2905 | 1.0 |
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| 6.6394 | 5.93 | 4000 | 14.2905 | 1.0 |
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| 6.6572 | 6.67 | 4500 | 14.2905 | 1.0 |
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| 6.5405 | 7.41 | 5000 | 14.2905 | 1.0 |
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| 6.7215 | 8.15 | 5500 | 14.2905 | 1.0 |
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| 6.6013 | 8.89 | 6000 | 14.2905 | 1.0 |
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| 6.666 | 9.63 | 6500 | 14.2905 | 1.0 |
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| 6.5773 | 10.37 | 7000 | 14.2905 | 1.0 |
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| 6.8272 | 11.11 | 7500 | 14.2905 | 1.0 |
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| 6.6015 | 11.85 | 8000 | 14.2905 | 1.0 |
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| 6.6827 | 12.59 | 8500 | 14.2905 | 1.0 |
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| 6.5923 | 13.33 | 9000 | 14.2905 | 1.0 |
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| 6.6176 | 14.07 | 9500 | 14.2905 | 1.0 |
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| 6.6977 | 14.81 | 10000 | 14.2905 | 1.0 |
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| 6.712 | 15.56 | 10500 | 14.2905 | 1.0 |
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| 6.5061 | 16.3 | 11000 | 14.2905 | 1.0 |
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| 6.7086 | 17.04 | 11500 | 14.2905 | 1.0 |
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| 6.6407 | 17.78 | 12000 | 14.2905 | 1.0 |
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| 6.7531 | 18.52 | 12500 | 14.2905 | 1.0 |
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| 6.5844 | 19.26 | 13000 | 14.2905 | 1.0 |
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| 6.6102 | 20.0 | 13500 | 14.2905 | 1.0 |
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| 6.6593 | 20.74 | 14000 | 14.2905 | 1.0 |
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| 6.6405 | 21.48 | 14500 | 14.2905 | 1.0 |
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| 6.6198 | 22.22 | 15000 | 14.2905 | 1.0 |
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| 6.6925 | 22.96 | 15500 | 14.2905 | 1.0 |
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| 6.6277 | 23.7 | 16000 | 14.2905 | 1.0 |
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| 6.719 | 24.44 | 16500 | 14.2905 | 1.0 |
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| 6.6951 | 25.19 | 17000 | 14.2905 | 1.0 |
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| 6.6291 | 25.93 | 17500 | 14.2905 | 1.0 |
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| 6.5456 | 26.67 | 18000 | 14.2905 | 1.0 |
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| 6.655 | 27.41 | 18500 | 14.2905 | 1.0 |
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| 6.6637 | 28.15 | 19000 | 14.2905 | 1.0 |
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| 6.6484 | 28.89 | 19500 | 14.2905 | 1.0 |
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| 6.6542 | 29.63 | 20000 | 14.2905 | 1.0 |
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### Framework versions
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