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README.md
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base_model: facebook/wav2vec2-xls-r-300m
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tags:
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- generated_from_trainer
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model-index:
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- name: libri-wav2vec2-xlsr-300m-phoneme-demo
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results: []
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# libri-wav2vec2-xlsr-300m-phoneme-demo
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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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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 4
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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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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### Framework versions
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base_model: facebook/wav2vec2-xls-r-300m
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: libri-wav2vec2-xlsr-300m-phoneme-demo
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results: []
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# libri-wav2vec2-xlsr-300m-phoneme-demo
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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: 17.5394
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- Wer: 3.3218
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- Cer: 0.9677
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 20
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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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| No log | 5.0 | 5 | 17.5401 | 3.3057 | 0.9626 |
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| No log | 10.0 | 10 | 17.5399 | 3.3356 | 0.9671 |
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| No log | 15.0 | 15 | 17.5399 | 3.3126 | 0.9624 |
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| No log | 20.0 | 20 | 17.5394 | 3.3218 | 0.9677 |
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### Framework versions
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