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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: '' |
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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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# |
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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: 0.7060 |
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- Wer: 0.5559 |
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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: 7e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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: 1200 |
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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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| 3.9554 | 2.61 | 300 | 3.8166 | 1.0 | |
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| 2.9853 | 5.22 | 600 | 2.9793 | 1.0 | |
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| 0.6939 | 7.83 | 900 | 0.9723 | 0.9149 | |
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| 0.352 | 10.43 | 1200 | 0.6556 | 0.7296 | |
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| 0.2369 | 13.04 | 1500 | 0.6315 | 0.6928 | |
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| 0.1757 | 15.65 | 1800 | 0.6387 | 0.6724 | |
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| 0.1517 | 18.26 | 2100 | 0.6607 | 0.6265 | |
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| 0.1229 | 20.87 | 2400 | 0.6520 | 0.6183 | |
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| 0.1201 | 23.48 | 2700 | 0.6750 | 0.6116 | |
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| 0.1076 | 26.09 | 3000 | 0.6698 | 0.6006 | |
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| 0.1006 | 28.7 | 3300 | 0.6804 | 0.5872 | |
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| 0.0952 | 31.3 | 3600 | 0.7010 | 0.6003 | |
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| 0.0894 | 33.91 | 3900 | 0.7069 | 0.5840 | |
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| 0.0873 | 36.52 | 4200 | 0.6765 | 0.5781 | |
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| 0.0798 | 39.13 | 4500 | 0.6822 | 0.5617 | |
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| 0.0767 | 41.74 | 4800 | 0.7003 | 0.5638 | |
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| 0.0717 | 44.35 | 5100 | 0.6970 | 0.5591 | |
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| 0.0687 | 46.96 | 5400 | 0.7073 | 0.5603 | |
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| 0.0669 | 49.57 | 5700 | 0.7060 | 0.5559 | |
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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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