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- library_name: transformers
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- # Model Card for Model ID
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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-clean-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-clean-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: 0.0100
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+ - Wer: 0.2638
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+
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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: 30
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+ - mixed_precision_training: Native AMP
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+
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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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+ | 4.7739 | 1.26 | 500 | 2.7988 | 1.0 |
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+ | 1.4369 | 2.53 | 1000 | 0.2079 | 0.5323 |
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+ | 0.2838 | 3.79 | 1500 | 0.0565 | 0.3471 |
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+ | 0.1845 | 5.05 | 2000 | 0.0435 | 0.3209 |
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+ | 0.1383 | 6.31 | 2500 | 0.0284 | 0.3011 |
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+ | 0.1131 | 7.58 | 3000 | 0.4893 | 0.2964 |
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+ | 0.1127 | 8.84 | 3500 | 0.0340 | 0.2702 |
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+ | 0.0942 | 10.1 | 4000 | 0.0155 | 0.2732 |
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+ | 0.0779 | 11.36 | 4500 | 0.0134 | 0.2667 |
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+ | 0.0665 | 12.63 | 5000 | 0.0130 | 0.2732 |
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+ | 0.0619 | 13.89 | 5500 | 0.0163 | 0.2667 |
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+ | 0.0539 | 15.15 | 6000 | 0.0514 | 0.2650 |
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+ | 0.0456 | 16.41 | 6500 | 0.0110 | 0.2662 |
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+ | 0.0405 | 17.68 | 7000 | 0.0105 | 0.2667 |
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+ | 0.0343 | 18.94 | 7500 | 0.0297 | 0.2667 |
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+ | 0.0325 | 20.2 | 8000 | 0.0109 | 0.2656 |
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+ | 0.0241 | 21.46 | 8500 | 0.0109 | 0.2662 |
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+ | 0.0214 | 22.73 | 9000 | 0.0136 | 0.2644 |
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+ | 0.0215 | 23.99 | 9500 | 0.0101 | 0.2638 |
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+ | 0.0215 | 25.25 | 10000 | 0.0101 | 0.2667 |
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+ | 0.0226 | 26.52 | 10500 | 0.0096 | 0.2638 |
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+ | 0.012 | 27.78 | 11000 | 0.0091 | 0.2644 |
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+ | 0.0111 | 29.04 | 11500 | 0.0100 | 0.2638 |
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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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