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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-ccv-cy
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-xlsr-53-ft-btb-ccv-cy
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.
It achieves the following results on the evaluation set:
- Loss: 0.6832
- Wer: 0.4641
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 4.8422 | 0.0854 | 500 | 2.2692 | 0.9886 |
| 1.2704 | 0.1709 | 1000 | 1.1623 | 0.7745 |
| 1.0177 | 0.2563 | 1500 | 0.9608 | 0.6586 |
| 0.9289 | 0.3417 | 2000 | 0.8117 | 0.6027 |
| 0.855 | 0.4271 | 2500 | 0.7981 | 0.5627 |
| 0.804 | 0.5126 | 3000 | 0.7293 | 0.5387 |
| 0.7384 | 0.5980 | 3500 | 0.6784 | 0.5150 |
| 0.7277 | 0.6834 | 4000 | 0.6553 | 0.4961 |
| 0.7009 | 0.7688 | 4500 | 0.6262 | 0.4684 |
| 0.6774 | 0.8543 | 5000 | 0.5955 | 0.4525 |
| 0.6427 | 0.9397 | 5500 | 0.5997 | 0.4741 |
| 0.6224 | 1.0251 | 6000 | 0.5653 | 0.4310 |
| 0.5507 | 1.1105 | 6500 | 0.5521 | 0.4173 |
| 0.6425 | 1.1960 | 7000 | 0.9010 | 0.5927 |
| 0.7218 | 1.2814 | 7500 | 0.7136 | 0.5011 |
| 0.8592 | 1.3668 | 8000 | 0.8863 | 0.6393 |
| 0.8668 | 1.4522 | 8500 | 0.7689 | 0.5330 |
| 0.7688 | 1.5377 | 9000 | 0.7101 | 0.4776 |
| 0.688 | 1.6231 | 9500 | 0.6742 | 0.4661 |
| 0.7079 | 1.7085 | 10000 | 0.6832 | 0.4641 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|