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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
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: 0.14290815597771747
- 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: 0.1413499060557884
---
<!-- 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
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: 0.2131
- Wer: 0.1429
And on the test set:
- Wer: 0.1413
## 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: 5e-05
- train_batch_size: 32
- 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: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.0565 | 1.72 | 200 | 3.1053 | 1.0 |
| 2.7675 | 3.45 | 400 | 1.1551 | 0.8611 |
| 1.3474 | 5.17 | 600 | 0.4770 | 0.4397 |
| 0.9617 | 6.9 | 800 | 0.3218 | 0.3343 |
| 0.9058 | 8.62 | 1000 | 0.2741 | 0.2768 |
| 0.9712 | 10.34 | 1200 | 0.2619 | 0.2505 |
| 0.6908 | 12.07 | 1400 | 0.2288 | 0.2243 |
| 0.745 | 13.79 | 1600 | 0.2288 | 0.2095 |
| 0.7742 | 15.52 | 1800 | 0.2289 | 0.1979 |
| 0.7231 | 17.24 | 2000 | 0.2198 | 0.1940 |
| 0.6475 | 18.97 | 2200 | 0.2180 | 0.1992 |
| 0.6421 | 20.69 | 2400 | 0.2133 | 0.1741 |
| 0.5925 | 22.41 | 2600 | 0.1998 | 0.1747 |
| 0.5608 | 24.14 | 2800 | 0.2212 | 0.1950 |
| 0.5315 | 25.86 | 3000 | 0.2187 | 0.1624 |
| 0.5362 | 27.59 | 3200 | 0.2057 | 0.1718 |
| 0.563 | 29.31 | 3400 | 0.2090 | 0.1613 |
| 0.4218 | 31.03 | 3600 | 0.2126 | 0.1531 |
| 0.3826 | 32.76 | 3800 | 0.2084 | 0.1538 |
| 0.356 | 34.48 | 4000 | 0.2115 | 0.1612 |
| 0.2966 | 36.21 | 4200 | 0.2093 | 0.1536 |
| 0.3377 | 37.93 | 4400 | 0.2061 | 0.1527 |
| 0.321 | 39.66 | 4600 | 0.2121 | 0.1463 |
| 0.2942 | 41.38 | 4800 | 0.2158 | 0.1441 |
| 0.2931 | 43.1 | 5000 | 0.2173 | 0.1446 |
| 0.2346 | 44.83 | 5200 | 0.2152 | 0.1436 |
| 0.2543 | 46.55 | 5400 | 0.2066 | 0.1445 |
| 0.2385 | 48.28 | 5600 | 0.2108 | 0.1432 |
| 0.2726 | 50.0 | 5800 | 0.2131 | 0.1429 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
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