---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-1b-danish-12h-6k-steps
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: da
      split: test
      args: da
    metrics:
    - name: Wer
      type: wer
      value: 29.80512727765972
---

<!-- 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-danish-12h-6k-steps

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4179
- Wer: 29.8051
- Cer: 9.5826

## 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     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:|
| 0.9182        | 5.3333  | 1000  | 0.5134          | 53.0768 | 16.3044 |
| 0.2894        | 10.6667 | 2000  | 0.3309          | 35.3529 | 10.9777 |
| 0.2917        | 16.0    | 3000  | 0.3877          | 38.0657 | 12.0348 |
| 0.1964        | 21.3333 | 4000  | 0.4244          | 36.1713 | 11.4545 |
| 0.1227        | 26.6667 | 5000  | 0.4213          | 36.4335 | 11.6030 |
| 0.1455        | 32.0    | 6000  | 0.4112          | 34.1412 | 10.9986 |
| 0.1005        | 37.3333 | 7000  | 0.4383          | 33.8563 | 10.8228 |
| 0.0604        | 42.6667 | 8000  | 0.4381          | 33.0379 | 10.5787 |
| 0.0616        | 48.0    | 9000  | 0.4445          | 31.4826 | 10.0955 |
| 0.0425        | 53.3333 | 10000 | 0.4412          | 30.7637 | 9.8170  |
| 0.0326        | 58.6667 | 11000 | 0.4179          | 29.8051 | 9.5826  |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3