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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-large-xlsr-53-W2V2-TR-MED
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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-large-xlsr-53-W2V2-TR-MED
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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 common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4467
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- Wer: 0.4598
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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: 2
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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: 500
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- num_epochs: 60
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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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| 5.1343 | 4.21 | 400 | 2.3674 | 1.0372 |
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| 0.8075 | 8.42 | 800 | 0.4583 | 0.6308 |
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| 0.3209 | 12.63 | 1200 | 0.4291 | 0.5531 |
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| 0.2273 | 16.84 | 1600 | 0.4348 | 0.5378 |
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| 0.1764 | 21.05 | 2000 | 0.4550 | 0.5326 |
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| 0.148 | 25.26 | 2400 | 0.4839 | 0.5319 |
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| 0.1268 | 29.47 | 2800 | 0.4515 | 0.5070 |
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| 0.1113 | 33.68 | 3200 | 0.4590 | 0.4930 |
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| 0.1025 | 37.89 | 3600 | 0.4546 | 0.4888 |
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| 0.0922 | 42.11 | 4000 | 0.4782 | 0.4852 |
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| 0.082 | 46.32 | 4400 | 0.4605 | 0.4752 |
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| 0.0751 | 50.53 | 4800 | 0.4358 | 0.4689 |
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| 0.0699 | 54.74 | 5200 | 0.4359 | 0.4629 |
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| 0.0633 | 58.95 | 5600 | 0.4467 | 0.4598 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.10.0+cu111
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- Datasets 1.14.0
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- Tokenizers 0.10.3
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