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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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model-index:
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- name: wav2vec2-large-xls-r-300m-Indonesian
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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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should probably proofread and complete it, then remove this comment. -->
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# wav2vec2-large-xls-r-300m-Indonesian
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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: 0.4087
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- Wer: 0.2461
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- Cer: 0.0666
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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: 64
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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: 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: 400
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- num_epochs: 50
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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| 5.0788 | 4.26 | 200 | 2.9389 | 1.0 | 1.0 |
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| 2.8288 | 8.51 | 400 | 2.2535 | 1.0 | 0.8004 |
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| 0.907 | 12.77 | 600 | 0.4558 | 0.4243 | 0.1095 |
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| 0.4071 | 17.02 | 800 | 0.4013 | 0.3468 | 0.0913 |
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| 0.3 | 21.28 | 1000 | 0.4167 | 0.3075 | 0.0816 |
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| 0.2544 | 25.53 | 1200 | 0.4132 | 0.2835 | 0.0762 |
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| 0.2145 | 29.79 | 1400 | 0.3878 | 0.2693 | 0.0729 |
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| 0.1923 | 34.04 | 1600 | 0.4023 | 0.2623 | 0.0702 |
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| 0.1681 | 38.3 | 1800 | 0.3984 | 0.2581 | 0.0686 |
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| 0.1598 | 42.55 | 2000 | 0.3982 | 0.2493 | 0.0663 |
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| 0.1464 | 46.81 | 2200 | 0.4087 | 0.2461 | 0.0666 |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2.dev0
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- Tokenizers 0.11.0
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