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README.md
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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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datasets:
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- vivos
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metrics:
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- wer
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model-index:
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- name: wav2vec2-augmented-vivos
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: vivos
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type: vivos
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config: default
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split: None
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 0.2447200155008719
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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-augmented-vivos
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the vivos dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4403
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- Wer: 0.2447
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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: 0.0002
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.3
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- num_epochs: 20
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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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| 6.6691 | 2.0 | 146 | 4.0324 | 1.0 |
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| 3.4795 | 4.0 | 292 | 3.6294 | 1.0 |
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| 3.4178 | 6.0 | 438 | 3.4910 | 1.0 |
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| 1.8415 | 8.0 | 584 | 0.7926 | 0.5287 |
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| 0.5336 | 10.0 | 730 | 0.5809 | 0.3677 |
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| 0.3349 | 12.0 | 876 | 0.4679 | 0.2853 |
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| 0.2424 | 14.0 | 1022 | 0.4440 | 0.2680 |
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| 0.2193 | 16.0 | 1168 | 0.4420 | 0.2536 |
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| 0.1627 | 18.0 | 1314 | 0.4373 | 0.2455 |
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| 0.1532 | 20.0 | 1460 | 0.4403 | 0.2447 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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