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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: fluent-noisy-wav2vec |
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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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# fluent-noisy-wav2vec |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0129 |
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- Wer: 0.2656 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 1000 |
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- num_epochs: 25 |
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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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| 4.5477 | 1.26 | 500 | 2.9258 | 1.0 | |
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| 1.6916 | 2.53 | 1000 | 0.4439 | 0.5218 | |
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| 0.4069 | 3.79 | 1500 | 0.0990 | 0.3524 | |
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| 0.2584 | 5.05 | 2000 | 0.0812 | 0.3256 | |
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| 0.1954 | 6.31 | 2500 | 0.0340 | 0.2825 | |
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| 0.1391 | 7.58 | 3000 | 0.0691 | 0.3046 | |
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| 0.1378 | 8.84 | 3500 | 0.0334 | 0.2848 | |
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| 0.1088 | 10.1 | 4000 | 0.0349 | 0.2871 | |
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| 0.0972 | 11.36 | 4500 | 0.0959 | 0.2761 | |
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| 0.0883 | 12.63 | 5000 | 0.0229 | 0.2726 | |
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| 0.0734 | 13.89 | 5500 | 0.0303 | 0.2772 | |
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| 0.0644 | 15.15 | 6000 | 0.0251 | 0.2755 | |
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| 0.0536 | 16.41 | 6500 | 0.0139 | 0.2714 | |
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| 0.0428 | 17.68 | 7000 | 0.0214 | 0.2685 | |
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| 0.0362 | 18.94 | 7500 | 0.0196 | 0.2667 | |
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| 0.0377 | 20.2 | 8000 | 0.0257 | 0.2691 | |
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| 0.0289 | 21.46 | 8500 | 0.0191 | 0.2673 | |
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| 0.0297 | 22.73 | 9000 | 0.0207 | 0.2667 | |
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| 0.029 | 23.99 | 9500 | 0.0129 | 0.2656 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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