Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_8_0
robust-speech-event
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use comodoro/wav2vec2-xls-r-300m-west-slavic-cv8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use comodoro/wav2vec2-xls-r-300m-west-slavic-cv8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="comodoro/wav2vec2-xls-r-300m-west-slavic-cv8")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("comodoro/wav2vec2-xls-r-300m-west-slavic-cv8") model = AutoModelForCTC.from_pretrained("comodoro/wav2vec2-xls-r-300m-west-slavic-cv8") - Notebooks
- Google Colab
- Kaggle
wav2vec2-xls-r-300m-west-slavic-cv8
This model is a fine-tuned version of 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
- Downloads last month
- 11
Evaluation results
- Test WER on Common Voice 8self-reported53.500
- Test CER on Common Voice 8self-reported14.700
- Test WER on Common Voice 8self-reported81.700
- Test CER on Common Voice 8self-reported21.200
- Test WER on Common Voice 8self-reported60.200
- Test CER on Common Voice 8self-reported15.600
- Test WER on Common Voice 8self-reported69.600
- Test CER on Common Voice 8self-reported20.700