--- language: - nl license: apache-2.0 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_8_0 - generated_from_trainer - nl - robust-speech-event - model_for_talk - hf-asr-leaderboard datasets: - mozilla-foundation/common_voice_8_0 model-index: - name: wav2vec2-large-xls-r-1b-nl-lm results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 8 type: mozilla-foundation/common_voice_8_0 args: nl metrics: - name: Test WER type: wer value: 9.73 - name: Test CER type: cer value: 2.89 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: nl metrics: - name: Test WER type: wer value: 27.27 - name: Test CER type: cer value: 13.23 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: nl metrics: - name: Test WER type: wer value: 27.67 --- # wav2vec2-large-xls-r-1b-nl-lm This model is a fine-tuned version of [wav2vec2-large-xls-r-1b-nl-lm](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice 8 dataset. It achieves the following results on the test set: - Loss: 0.1479 - Wer: 0.1156 Note that the above test results come from the original model without LM (language model) which can be found at https://huggingface.co/RuudVelo/wav2vec2-large-xls-r-1b-nl. The results with the LM model can be found on the right side of this model card. ## Model description Model RuudVelo/wav2vec2-large-xls-r-1b-nl which has been improved with a KenLM 5-gram. ## Intended uses & limitations More information needed ## Training and evaluation data Common Voice 8 nl dataset has been used for the model ## Training procedure ### Training hyperparameters Parameters can be found in the run.sh file at https://huggingface.co/RuudVelo/wav2vec2-large-xls-r-1b-nl ### Framework versions - Transformers 4.16.0.dev0 - Pytorch 1.10.1+cu102 - Datasets 1.18.3 - Tokenizers 0.11.0