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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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metrics:
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- wer
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model-index:
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- name: asr_skripsi_colab_common_voice
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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: 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
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should probably proofread and complete it, then remove this comment. -->
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# asr_skripsi_colab_common_voice
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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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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: 16
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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: 32
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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: 30
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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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| 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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