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--- |
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tags: |
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- automatic-speech-recognition |
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- librispeech_asr |
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- generated_from_trainer |
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model-index: |
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- name: wavlm-libri-clean-100h-base |
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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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# wavlm-libri-clean-100h-base |
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This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on the LIBRISPEECH_ASR - CLEAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0955 |
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- Wer: 0.0773 |
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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: 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: 500 |
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- num_epochs: 1.0 |
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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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| 2.8664 | 0.17 | 300 | 2.8439 | 1.0 | |
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| 0.5009 | 0.34 | 600 | 0.2709 | 0.2162 | |
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| 0.2056 | 0.5 | 900 | 0.1934 | 0.1602 | |
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| 0.1648 | 0.67 | 1200 | 0.1576 | 0.1306 | |
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| 0.1922 | 0.84 | 1500 | 0.1358 | 0.1114 | |
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| 0.093 | 1.01 | 1800 | 0.1277 | 0.1035 | |
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| 0.0652 | 1.18 | 2100 | 0.1251 | 0.1005 | |
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| 0.0848 | 1.35 | 2400 | 0.1188 | 0.0964 | |
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| 0.0706 | 1.51 | 2700 | 0.1091 | 0.0905 | |
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| 0.0846 | 1.68 | 3000 | 0.1018 | 0.0840 | |
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| 0.0684 | 1.85 | 3300 | 0.0978 | 0.0809 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.9.1 |
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- Datasets 1.18.0 |
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- Tokenizers 0.10.3 |
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