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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-1b-frisian-cv-8-10m
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_8_0
type: common_voice_8_0
config: fy-NL
split: validation
args: fy-NL
metrics:
- name: Wer
type: wer
value: 0.5262462505356378
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_8_0
type: common_voice_8_0
config: fy-NL
split: test
args: fy-NL
metrics:
- name: Wer
type: wer
value: 0.6225249313484608
---
<!-- 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-large-xls-r-1b-frisian-cv-8-10m
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_8_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9269
- Wer: 0.5262
And on the test set:
- Wer: 0.6225
## 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: 7e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 80
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.2929 | 6.25 | 50 | 3.0514 | 1.0 |
| 3.315 | 12.5 | 100 | 3.2255 | 1.0 |
| 3.1506 | 18.75 | 150 | 2.9924 | 1.0 |
| 2.9773 | 25.0 | 200 | 2.2199 | 1.0 |
| 2.1616 | 31.25 | 250 | 1.1423 | 0.8603 |
| 1.6887 | 37.5 | 300 | 0.9730 | 0.7020 |
| 1.1178 | 43.75 | 350 | 0.8971 | 0.6323 |
| 0.9512 | 50.0 | 400 | 0.9040 | 0.5960 |
| 0.7696 | 56.25 | 450 | 0.9232 | 0.5713 |
| 0.7348 | 62.5 | 500 | 0.9203 | 0.5412 |
| 0.9312 | 68.75 | 550 | 0.9673 | 0.5376 |
| 0.6519 | 75.0 | 600 | 0.9269 | 0.5262 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
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