End of training
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README.md
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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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: 16
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- eval_batch_size: 8
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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: 100
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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
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### Framework versions
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: -1.7265
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- Cer: 2.8268
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- Wer: 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: 5e-05
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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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- 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: 100
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- num_epochs: 300
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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 | Cer | Wer |
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| -2.2058 | 16.6667 | 100 | -1.7563 | 2.7979 | 1.0 |
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| -2.2553 | 33.3333 | 200 | -1.7904 | 2.8052 | 1.0 |
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| -2.3332 | 50.0 | 300 | -1.8135 | 2.8289 | 1.0 |
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| -2.3625 | 66.6667 | 400 | -1.7726 | 2.7791 | 1.0 |
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| -2.3912 | 83.3333 | 500 | -1.7941 | 2.7467 | 1.0 |
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| -2.4162 | 100.0 | 600 | -1.7979 | 2.7745 | 1.0 |
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| -2.4141 | 116.6667 | 700 | -1.7517 | 2.7428 | 1.0 |
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| -2.4383 | 133.3333 | 800 | -1.8364 | 2.9398 | 1.0 |
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| -2.4441 | 150.0 | 900 | -1.7691 | 2.8856 | 1.0 |
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| -2.4518 | 166.6667 | 1000 | -1.7509 | 2.7699 | 1.0 |
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| -2.4653 | 183.3333 | 1100 | -1.7286 | 2.8175 | 1.0 |
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| -2.4651 | 200.0 | 1200 | -1.7521 | 2.7321 | 1.0 |
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| -2.4619 | 216.6667 | 1300 | -1.6761 | 2.7655 | 1.0 |
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| -2.4649 | 233.3333 | 1400 | -1.6887 | 2.7880 | 1.0 |
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| -2.4863 | 250.0 | 1500 | -1.7591 | 2.7745 | 1.0 |
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| -2.472 | 266.6667 | 1600 | -1.7198 | 2.7464 | 1.0 |
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| -2.477 | 283.3333 | 1700 | -1.7385 | 2.8616 | 1.0 |
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| -2.4708 | 300.0 | 1800 | -1.7265 | 2.8268 | 1.0 |
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### Framework versions
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