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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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