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kylzer
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asr_skripsi_colab_common_voice

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
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Eval Results
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update model card README.md

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@@ -16,12 +16,12 @@ model-index:
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  name: common_voice
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  type: common_voice
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  config: id
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- split: train+validation
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  args: id
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  metrics:
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  - name: Wer
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  type: wer
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- value: 0.22400210084033614
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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
@@ -31,8 +31,8 @@ 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-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: 0.3589
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- - Wer: 0.2240
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  ## Model description
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@@ -67,19 +67,19 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 2.3848 | 3.64 | 400 | 0.7048 | 0.6599 |
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- | 0.5612 | 7.27 | 800 | 0.4098 | 0.3711 |
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- | 0.3146 | 10.91 | 1200 | 0.4011 | 0.3258 |
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- | 0.225 | 14.55 | 1600 | 0.3816 | 0.2799 |
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- | 0.1787 | 18.18 | 2000 | 0.3890 | 0.2673 |
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- | 0.1473 | 21.82 | 2400 | 0.3614 | 0.2466 |
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- | 0.1214 | 25.45 | 2800 | 0.3590 | 0.2388 |
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- | 0.1057 | 29.09 | 3200 | 0.3589 | 0.2240 |
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  ### Framework versions
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- - Transformers 4.25.1
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- - Pytorch 1.13.0+cu116
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- - Datasets 2.7.1
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  - Tokenizers 0.13.2
 
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  name: common_voice
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  type: common_voice
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  config: id
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+ split: test
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  args: id
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 0.36856617647058826
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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-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: 0.3839
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+ - Wer: 0.3686
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 4.4354 | 3.64 | 400 | 1.9595 | 1.0 |
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+ | 0.7227 | 7.27 | 800 | 0.4532 | 0.5039 |
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+ | 0.3293 | 10.91 | 1200 | 0.4277 | 0.4425 |
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+ | 0.2298 | 14.55 | 1600 | 0.3947 | 0.4182 |
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+ | 0.1789 | 18.18 | 2000 | 0.3960 | 0.4009 |
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+ | 0.1496 | 21.82 | 2400 | 0.3793 | 0.3848 |
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+ | 0.122 | 25.45 | 2800 | 0.3794 | 0.3795 |
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+ | 0.1056 | 29.09 | 3200 | 0.3839 | 0.3686 |
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  ### Framework versions
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.10.0
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  - Tokenizers 0.13.2