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---
language:
- cs
- hsb
- pl
- sk
- sl
- multilingual
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- xlsr-fine-tuning-week
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-xls-r-300m-west-slavic-cv8
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: cs
metrics:
- type: wer
value: 53.5
name: Test WER
- type: cer
value: 14.7
name: Test CER
- type: wer
value: 81.7
name: Test WER
- type: cer
value: 21.2
name: Test CER
- type: wer
value: 60.2
name: Test WER
- type: cer
value: 15.6
name: Test CER
- type: wer
value: 69.6
name: Test WER
- type: cer
value: 20.7
name: Test CER
- type: wer
value: 73.2
name: Test WER
- type: cer
value: 23.2
name: Test CER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: cs
metrics:
- type: wer
value: 84.11
name: Test WER
- type: wer
value: 65.3
name: Test WER
- type: wer
value: 88.37
name: Test WER
- type: wer
value: 87.69
name: Test WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: cs
metrics:
- type: wer
value: 75.99
name: Test WER
- type: wer
value: 72.0
name: Test WER
- type: wer
value: 89.08
name: Test WER
- type: wer
value: 87.89
name: Test WER
---
# wav2vec2-xls-r-300m-west-slavic-cv8
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 8 dataset of five similar languages with similar scripts: Czech, Slovak, Polish, Slovenian and Upper Sorbian. Training and validation sets were concatenated and shuffled.
Evaluation set used for training was concatenated from the respective test sets and shuffled while limiting each language to at most 2000 samples. During training, cca WER 70 was achieved on this set.
### Evaluation script
```
python eval.py --model_id comodoro/wav2vec2-xls-r-300m-west-slavic-cv8 --dataset mozilla-foundation/common_voice_8_0 --split test --config {lang}
```
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- 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
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
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