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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./data-configs/btb-cv-s99.json
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-cv-s99-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-cv-s99-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: 0.5434
- Wer: 0.4161
## 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: 800
- training_steps: 8000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.9477 | 0.0337 | 500 | 1.7842 | 0.9396 |
| 1.035 | 0.0675 | 1000 | 1.2386 | 0.7851 |
| 0.8162 | 0.1012 | 1500 | 1.0027 | 0.7022 |
| 0.702 | 0.1349 | 2000 | 0.9614 | 0.6609 |
| 0.6574 | 0.1687 | 2500 | 0.8651 | 0.6165 |
| 0.602 | 0.2024 | 3000 | 0.7874 | 0.5728 |
| 0.5547 | 0.2361 | 3500 | 0.7803 | 0.5767 |
| 0.5325 | 0.2699 | 4000 | 0.7444 | 0.5494 |
| 0.5074 | 0.3036 | 4500 | 0.6984 | 0.5280 |
| 0.4755 | 0.3373 | 5000 | 0.6562 | 0.4964 |
| 0.4582 | 0.3711 | 5500 | 0.6308 | 0.4779 |
| 0.4177 | 0.4048 | 6000 | 0.6201 | 0.4672 |
| 0.3892 | 0.4385 | 6500 | 0.5882 | 0.4502 |
| 0.3694 | 0.4723 | 7000 | 0.5677 | 0.4295 |
| 0.3437 | 0.5060 | 7500 | 0.5474 | 0.4185 |
| 0.3481 | 0.5397 | 8000 | 0.5434 | 0.4161 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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