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---
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
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