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update model card README.md

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  ---
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- language:
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- - ja
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  license: apache-2.0
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  tags:
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- - automatic-speech-recognition
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- - mozilla-foundation/common_voice_8_0
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  - generated_from_trainer
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  datasets:
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  - common_voice
@@ -18,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  #
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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 MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9564
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- - Wer: 2.4135
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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: 2000
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- - num_epochs: 10.0
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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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- | 4.2279 | 4.5 | 1000 | 4.1102 | 2.0825 |
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- | 2.4119 | 9.01 | 2000 | 1.1737 | 2.3581 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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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  #
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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: 0.5349
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+ - Wer: 2.6274
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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: 2000
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+ - num_epochs: 50.0
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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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+ | 4.221 | 4.5 | 1000 | 4.1195 | 2.4024 |
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+ | 2.3597 | 9.01 | 2000 | 1.1024 | 2.7618 |
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+ | 1.8795 | 13.51 | 3000 | 0.7498 | 2.5885 |
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+ | 1.7143 | 18.02 | 4000 | 0.6539 | 2.5976 |
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+ | 1.6025 | 22.52 | 5000 | 0.5989 | 2.6034 |
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+ | 1.5403 | 27.03 | 6000 | 0.6035 | 2.6946 |
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+ | 1.4773 | 31.53 | 7000 | 0.5647 | 2.5558 |
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+ | 1.4228 | 36.04 | 8000 | 0.5477 | 2.5676 |
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+ | 1.3801 | 40.54 | 9000 | 0.5413 | 2.6192 |
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+ | 1.3558 | 45.05 | 10000 | 0.5343 | 2.6575 |
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+ | 1.3298 | 49.55 | 11000 | 0.5349 | 2.6274 |
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  ### Framework versions