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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-large-xlsr-53
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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-xlsr-53-ft-btb-cv-s99-cy
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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-xlsr-53-ft-btb-cv-s99-cy
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5434
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- Wer: 0.4161
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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: 8
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- eval_batch_size: 64
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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: 800
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- training_steps: 8000
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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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| 4.9477 | 0.0337 | 500 | 1.7842 | 0.9396 |
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| 1.035 | 0.0675 | 1000 | 1.2386 | 0.7851 |
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| 0.8162 | 0.1012 | 1500 | 1.0027 | 0.7022 |
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| 0.702 | 0.1349 | 2000 | 0.9614 | 0.6609 |
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| 0.6574 | 0.1687 | 2500 | 0.8651 | 0.6165 |
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| 0.602 | 0.2024 | 3000 | 0.7874 | 0.5728 |
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| 0.5547 | 0.2361 | 3500 | 0.7803 | 0.5767 |
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| 0.5325 | 0.2699 | 4000 | 0.7444 | 0.5494 |
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| 0.5074 | 0.3036 | 4500 | 0.6984 | 0.5280 |
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| 0.4755 | 0.3373 | 5000 | 0.6562 | 0.4964 |
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| 0.4582 | 0.3711 | 5500 | 0.6308 | 0.4779 |
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| 0.4177 | 0.4048 | 6000 | 0.6201 | 0.4672 |
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| 0.3892 | 0.4385 | 6500 | 0.5882 | 0.4502 |
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| 0.3694 | 0.4723 | 7000 | 0.5677 | 0.4295 |
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| 0.3437 | 0.5060 | 7500 | 0.5474 | 0.4185 |
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| 0.3481 | 0.5397 | 8000 | 0.5434 | 0.4161 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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