--- language: - fr tags: - automatic-speech-recognition - generated_from_trainer - hf-asr-leaderboard - mozilla-foundation/common_voice_8_0 - robust-speech-event datasets: - mozilla-foundation/common_voice_8_0 model-index: - name: xls-r-300m-fr results: - task: name: Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 8.0 fr type: mozilla-foundation/common_voice_8_0 args: fr metrics: - name: Test WER type: wer value: 21.58 - task: name: Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: fr metrics: - name: Test WER type: wer value: 36.03 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: fr metrics: - name: Test WER type: wer value: 38.86 --- # This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset. ## 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: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2700 - num_epochs: 1.0 - mixed_precision_training: Native AMP ### Framework versions - Transformers 4.17.0.dev0 - Pytorch 1.10.2+cu102 - Datasets 1.18.2.dev0 - Tokenizers 0.11.0