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---
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language:
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- tr
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- common_voice
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- generated_from_trainer
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model-index:
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- name: wav2vec2-xls-r-common_voice-tr-ft-stream
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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-xls-r-common_voice-tr-ft-stream
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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 - TR dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3519
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- Wer: 0.2927
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- Cer: 0.0694
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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: 0.0005
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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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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 64
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- total_eval_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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- training_steps: 5000
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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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| 0.6768 | 9.01 | 500 | 0.4220 | 0.5143 | 0.1235 |
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| 0.3801 | 19.01 | 1000 | 0.3303 | 0.4403 | 0.1055 |
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| 0.3616 | 29.0 | 1500 | 0.3540 | 0.3716 | 0.0878 |
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| 0.2334 | 39.0 | 2000 | 0.3666 | 0.3671 | 0.0842 |
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| 0.3141 | 49.0 | 2500 | 0.3407 | 0.3373 | 0.0819 |
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| 0.1926 | 58.01 | 3000 | 0.3886 | 0.3520 | 0.0867 |
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| 0.1372 | 68.01 | 3500 | 0.3415 | 0.3189 | 0.0743 |
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| 0.091 | 78.0 | 4000 | 0.3750 | 0.3164 | 0.0757 |
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| 0.0893 | 88.0 | 4500 | 0.3559 | 0.2968 | 0.0712 |
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| 0.095 | 98.0 | 5000 | 0.3519 | 0.2927 | 0.0694 |
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### Framework versions
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- Transformers 4.16.0.dev0
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- Pytorch 1.10.2
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- Datasets 1.18.2
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- Tokenizers 0.10.3
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