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update model card README.md

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@@ -4,24 +4,9 @@ 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-large-xls-r-300m-turkish-colab
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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: 0.5164947400674088
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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
@@ -30,9 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
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  # wav2vec2-large-xls-r-300m-turkish-colab
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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 dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.4866
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- - Wer: 0.5165
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  ## Model description
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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: 10
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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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- | 4.0176 | 3.33 | 400 | 1.0080 | 0.8303 |
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- | 0.5978 | 6.67 | 800 | 0.5870 | 0.6240 |
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- | 0.2233 | 10.0 | 1200 | 0.4866 | 0.5165 |
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  ### Framework versions
 
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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-xls-r-300m-turkish-colab
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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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  # wav2vec2-large-xls-r-300m-turkish-colab
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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 dataset.
 
 
 
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  ## Model description
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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: 3
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  ### Training results
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  ### Framework versions