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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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  model-index:
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  - name: wav2vec2-large-xls-r-1b-Swedish
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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
@@ -16,10 +61,16 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
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  It achieves the following results on the evaluation set:
 
 
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  - Loss: 0.3370
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  - Wer: 0.1803
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  - Cer: 0.0569
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  ## Model description
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  More information needed
 
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  ---
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+ language:
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+ - sv-SE
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+
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  license: apache-2.0
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  tags:
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+ - automatic-speech-recognition
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+ - robust-speech-event
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  datasets:
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+ - mozilla-foundation/common_voice_8_0
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+ metrics:
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+ - wer
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+ - cer
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  model-index:
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  - name: wav2vec2-large-xls-r-1b-Swedish
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+ results:
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+ - task:
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+ type: automatic-speech-recognition # Required. Example: automatic-speech-recognition
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+ name: Speech Recognition # Optional. Example: Speech Recognition
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+ dataset:
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+ type: mozilla-foundation/common_voice_8_0 # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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+ name: Common Voice sv-SE # Required. Example: Common Voice zh-CN
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+ args: sv-SE # Optional. Example: zh-CN
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+ metrics:
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+ - type: wer # Required. Example: wer
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+ value: 18.03 # Required. Example: 20.90
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+ name: Test WER Without LM # Optional. Example: Test WER
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+ args:
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+ - learning_rate: 7.5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 1000
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+ - num_epochs: 50
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+ - mixed_precision_training: Native AMP # Optional. Example for BLEU: max_order
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+ - type: cer # Required. Example: wer
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+ value: 5.69 # Required. Example: 20.90
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+ name: Test CER Without LM # Optional. Example: Test WER
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+ args:
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+ - learning_rate: 7.5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 1000
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+ - num_epochs: 50
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+ - mixed_precision_training: Native AMP
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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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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
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  It achieves the following results on the evaluation set:
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+
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+ **Without LM**
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  - Loss: 0.3370
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  - Wer: 0.1803
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  - Cer: 0.0569
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+ **With LM**
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+
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+
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+
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  ## Model description
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  More information needed