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---
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library_name: transformers
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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: wav2vec2_milDB
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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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# wav2vec2_milDB
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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: 1.9031
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- Wer: 1.0
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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: 32
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 5000
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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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| 1.9166 | 10.9890 | 1000 | 1.6068 | 1.0 |
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| 1.2813 | 21.9780 | 2000 | 1.6121 | 1.0 |
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| 1.8313 | 32.9670 | 3000 | 1.8892 | 1.0 |
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| 1.8958 | 43.9560 | 4000 | 1.8899 | 1.0 |
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| 1.897 | 54.9451 | 5000 | 1.9031 | 1.0 |
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.4.1+cu124
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- Datasets 2.21.0
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- Tokenizers 0.21.0
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