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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: 0.7612841022711041
---
<!-- 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: 1.1618
- Wer: 0.7613
## 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
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.7106 | 6.25 | 50 | 4.0034 | 1.0 |
| 3.4036 | 12.5 | 100 | 3.1030 | 1.0 |
| 3.7265 | 18.75 | 150 | 3.0466 | 1.0 |
| 3.2292 | 25.0 | 200 | 3.0166 | 1.0 |
| 3.1305 | 31.25 | 250 | 2.9699 | 1.0 |
| 3.0447 | 37.5 | 300 | 2.9144 | 1.0 |
| 2.9037 | 43.75 | 350 | 2.2919 | 0.9998 |
| 2.1115 | 50.0 | 400 | 1.3995 | 0.9429 |
| 1.3456 | 56.25 | 450 | 1.1093 | 0.8435 |
| 1.3206 | 62.5 | 500 | 1.1573 | 0.8112 |
| 1.0078 | 68.75 | 550 | 1.1746 | 0.7757 |
| 1.0674 | 75.0 | 600 | 1.1618 | 0.7613 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
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