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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-1b-luxembourgish-38h-11k-steps
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-xls-r-1b-luxembourgish-38h-11k-steps
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5388
- Wer: 53.3282
- Cer: 15.6751
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- training_steps: 11000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:|
| 0.627 | 1.4286 | 1000 | 0.3266 | 39.7841 | 11.5375 |
| 0.9399 | 2.8571 | 2000 | 0.5695 | 46.6975 | 13.7326 |
| 0.7264 | 4.2857 | 3000 | 0.4885 | 48.5736 | 14.8389 |
| 0.7351 | 5.7143 | 4000 | 0.5389 | 53.3539 | 15.6838 |
| 0.759 | 7.1429 | 5000 | 0.5388 | 53.4567 | 15.6620 |
| 0.7855 | 8.5714 | 6000 | 0.5388 | 53.2768 | 15.6707 |
| 0.762 | 10.0 | 7000 | 0.5388 | 53.3796 | 15.7012 |
| 0.7479 | 11.4286 | 8000 | 0.5388 | 53.3539 | 15.6751 |
| 0.8233 | 12.8571 | 9000 | 0.5388 | 53.4053 | 15.6794 |
| 0.7284 | 14.2857 | 10000 | 0.5388 | 53.3025 | 15.6925 |
| 0.7415 | 15.7143 | 11000 | 0.5388 | 53.3282 | 15.6751 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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