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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xls-r-300-cv17-polish-adap-cs
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: pl
split: validation
args: pl
metrics:
- name: Wer
type: wer
value: 0.3181674482322567
---
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# xls-r-300-cv17-polish-adap-cs
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4585
- Wer: 0.3182
- Cer: 0.0713
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.5986 | 1.6 | 100 | 3.9654 | 0.9986 | 0.9660 |
| 3.2886 | 3.2 | 200 | 3.4889 | 1.0 | 1.0 |
| 3.1683 | 4.8 | 300 | 3.1937 | 0.9946 | 0.9735 |
| 2.7362 | 6.4 | 400 | 2.6853 | 1.0 | 0.8424 |
| 0.6269 | 8.0 | 500 | 0.5183 | 0.5745 | 0.1381 |
| 0.2661 | 9.6 | 600 | 0.4218 | 0.4551 | 0.1048 |
| 0.1646 | 11.2 | 700 | 0.4160 | 0.4211 | 0.0985 |
| 0.1197 | 12.8 | 800 | 0.4793 | 0.4578 | 0.1072 |
| 0.1925 | 14.4 | 900 | 0.4402 | 0.4283 | 0.0969 |
| 0.1132 | 16.0 | 1000 | 0.4253 | 0.3909 | 0.0906 |
| 0.0851 | 17.6 | 1100 | 0.4609 | 0.3951 | 0.0921 |
| 0.0799 | 19.2 | 1200 | 0.4453 | 0.3944 | 0.0907 |
| 0.0657 | 20.8 | 1300 | 0.4681 | 0.3846 | 0.0887 |
| 0.1188 | 22.4 | 1400 | 0.4575 | 0.3785 | 0.0873 |
| 0.1088 | 24.0 | 1500 | 0.4649 | 0.3824 | 0.0882 |
| 0.0698 | 25.6 | 1600 | 0.4496 | 0.3611 | 0.0817 |
| 0.0575 | 27.2 | 1700 | 0.4459 | 0.3585 | 0.0822 |
| 0.0705 | 28.8 | 1800 | 0.4542 | 0.3608 | 0.0820 |
| 0.0524 | 30.4 | 1900 | 0.4785 | 0.3549 | 0.0814 |
| 0.0338 | 32.0 | 2000 | 0.4566 | 0.3521 | 0.0801 |
| 0.0357 | 33.6 | 2100 | 0.4597 | 0.3472 | 0.0783 |
| 0.0477 | 35.2 | 2200 | 0.4626 | 0.3451 | 0.0788 |
| 0.0478 | 36.8 | 2300 | 0.4730 | 0.3375 | 0.0765 |
| 0.0568 | 38.4 | 2400 | 0.4713 | 0.3333 | 0.0749 |
| 0.0217 | 40.0 | 2500 | 0.4701 | 0.3324 | 0.0755 |
| 0.0404 | 41.6 | 2600 | 0.4585 | 0.3278 | 0.0740 |
| 0.0118 | 43.2 | 2700 | 0.4656 | 0.3259 | 0.0736 |
| 0.0374 | 44.8 | 2800 | 0.4625 | 0.3249 | 0.0731 |
| 0.0417 | 46.4 | 2900 | 0.4599 | 0.3206 | 0.0721 |
| 0.0378 | 48.0 | 3000 | 0.4614 | 0.3195 | 0.0717 |
| 0.0381 | 49.6 | 3100 | 0.4585 | 0.3182 | 0.0713 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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