--- language: - nl license: apache-2.0 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_8_0 - nl - robust-speech-event datasets: - mozilla-foundation/common_voice_8_0 model-index: - name: XLS-R-1B - Dutch 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: 10.38 - name: Test CER type: cer value: 3.04 - name: Test WER (+LM) type: wer value: 6.83 - name: Test CER (+LM) type: cer value: 2.31 - 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: 31.12 - name: Test CER type: cer value: 15.92 - name: Test WER (+LM) type: wer value: 23.95 - name: Test CER (+LM) type: cer value: 14.18 --- # XLS-R-1B-DUTCH Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Dutch using the [Common Voice 8](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0). When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the [OVHcloud](https://www.ovhcloud.com/en/public-cloud/ai-training/) :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint ## Evaluation Commands 1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test` ```bash python eval.py --model_id jonatasgrosman/wav2vec2-xls-r-1b-dutch --dataset mozilla-foundation/common_voice_8_0 --config nl --split test ``` 2. To evaluate on `speech-recognition-community-v2/dev_data` ```bash python eval.py --model_id jonatasgrosman/wav2vec2-xls-r-1b-dutch --dataset speech-recognition-community-v2/dev_data --config nl --split validation --chunk_length_s 5.0 --stride_length_s 1.0 ```