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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-500sh
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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-500sh
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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: 0.5794
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- Wer: 0.4009
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- Cer: 0.1032
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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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| 0.5288 | 17.0 | 500 | 0.5099 | 0.5426 | 0.1432 |
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| 0.2967 | 34.0 | 1000 | 0.5421 | 0.4746 | 0.1256 |
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| 0.2447 | 51.0 | 1500 | 0.5347 | 0.4831 | 0.1267 |
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| 0.122 | 68.01 | 2000 | 0.5854 | 0.4479 | 0.1161 |
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| 0.1035 | 86.0 | 2500 | 0.5597 | 0.4457 | 0.1166 |
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| 0.081 | 103.0 | 3000 | 0.5748 | 0.4250 | 0.1144 |
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| 0.0849 | 120.0 | 3500 | 0.5598 | 0.4337 | 0.1145 |
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| 0.0542 | 137.01 | 4000 | 0.5687 | 0.4223 | 0.1097 |
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| 0.0318 | 155.0 | 4500 | 0.5904 | 0.4057 | 0.1052 |
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| 0.0106 | 172.0 | 5000 | 0.5794 | 0.4009 | 0.1032 |
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### Framework versions
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- Transformers 4.17.0.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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