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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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metrics:
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- wer
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model-index:
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- name: wav2vec2-common_voice-tr-output
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice
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type: common_voice
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config: tr
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split: test
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args: tr
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metrics:
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- name: Wer
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type: wer
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value: 0.3403125319170667
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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-output
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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: 0.3795
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- Wer: 0.3403
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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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| No log | 0.92 | 100 | 3.6032 | 1.0 |
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| No log | 1.83 | 200 | 3.0158 | 0.9999 |
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| No log | 2.75 | 300 | 0.9692 | 0.8029 |
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| No log | 3.67 | 400 | 0.5820 | 0.6161 |
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| 3.1812 | 4.59 | 500 | 0.4891 | 0.5095 |
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| 3.1812 | 5.5 | 600 | 0.4719 | 0.4853 |
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| 3.1812 | 6.42 | 700 | 0.4360 | 0.4539 |
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| 3.1812 | 7.34 | 800 | 0.4098 | 0.4283 |
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| 3.1812 | 8.26 | 900 | 0.4020 | 0.3993 |
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| 0.2212 | 9.17 | 1000 | 0.4001 | 0.3806 |
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| 0.2212 | 10.09 | 1100 | 0.4000 | 0.3873 |
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| 0.2212 | 11.01 | 1200 | 0.4070 | 0.3751 |
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| 0.2212 | 11.93 | 1300 | 0.3874 | 0.3551 |
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| 0.2212 | 12.84 | 1400 | 0.3913 | 0.3561 |
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| 0.0998 | 13.76 | 1500 | 0.3882 | 0.3492 |
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| 0.0998 | 14.68 | 1600 | 0.3795 | 0.3403 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 1.12.1+cu102
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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