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README.md
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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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- speech-recognition
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- common_voice
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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-common_voice-tr-demo
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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-common_voice-tr-demo
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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 - TR dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3856
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- Wer: 0.3556
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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: 15.0
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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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| 3.7391 | 0.92 | 100 | 3.5760 | 1.0 |
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| 2.927 | 1.83 | 200 | 3.0796 | 0.9999 |
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| 0.9009 | 2.75 | 300 | 0.9278 | 0.8226 |
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| 0.6529 | 3.67 | 400 | 0.5926 | 0.6367 |
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| 0.3623 | 4.59 | 500 | 0.5372 | 0.5692 |
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| 0.2888 | 5.5 | 600 | 0.4407 | 0.4838 |
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| 0.285 | 6.42 | 700 | 0.4341 | 0.4694 |
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| 0.0842 | 7.34 | 800 | 0.4153 | 0.4302 |
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| 0.1415 | 8.26 | 900 | 0.4317 | 0.4136 |
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| 0.1552 | 9.17 | 1000 | 0.4145 | 0.4013 |
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| 0.1184 | 10.09 | 1100 | 0.4115 | 0.3844 |
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| 0.0556 | 11.01 | 1200 | 0.4182 | 0.3862 |
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| 0.0851 | 11.93 | 1300 | 0.3985 | 0.3688 |
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| 0.0961 | 12.84 | 1400 | 0.4030 | 0.3665 |
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| 0.0596 | 13.76 | 1500 | 0.3880 | 0.3631 |
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| 0.0917 | 14.68 | 1600 | 0.3878 | 0.3582 |
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### Framework versions
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- Transformers 4.11.0.dev0
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- Pytorch 1.9.0+cu111
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- Datasets 1.12.1
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- Tokenizers 0.10.3
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