language, license, tags, datasets, model-index

language	license	tags	datasets	model-index
fr	apache-2.0	automatic-speech-recognition mozilla-foundation/common_voice_7_0 generated_from_trainer robust-speech-event hf-asr-leaderboard	mozilla-foundation/common_voice_7_0	name results XLS-R-300M - French task dataset metrics name type Automatic Speech Recognition automatic-speech-recognition name type args Common Voice 7 mozilla-foundation/common_voice_7_0 fr name type value Test WER wer 24.56 name type value Test CER cer 7.3 task dataset metrics name type Automatic Speech Recognition automatic-speech-recognition name type args Robust Speech Event - Dev Data speech-recognition-community-v2/dev_data fr name type value Test WER wer 63.62 name type value Test CER cer 17.2 task dataset metrics name type Automatic Speech Recognition automatic-speech-recognition name type args Robust Speech Event - Test Data speech-recognition-community-v2/eval_data fr name type value Test WER wer 66.45

## Model description This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FR dataset. ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 7.5e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2000 - num_epochs: 2.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 3.495 | 0.16 | 500 | 3.3883 | 1.0 | | 2.9095 | 0.32 | 1000 | 2.9152 | 1.0000 | | 1.8434 | 0.49 | 1500 | 1.0473 | 0.7446 | | 1.4298 | 0.65 | 2000 | 0.5729 | 0.5130 | | 1.1937 | 0.81 | 2500 | 0.3795 | 0.3450 | | 1.1248 | 0.97 | 3000 | 0.3321 | 0.3052 | | 1.0835 | 1.13 | 3500 | 0.3038 | 0.2805 | | 1.0479 | 1.3 | 4000 | 0.2910 | 0.2689 | | 1.0413 | 1.46 | 4500 | 0.2798 | 0.2593 | | 1.014 | 1.62 | 5000 | 0.2727 | 0.2512 | | 1.004 | 1.78 | 5500 | 0.2646 | 0.2471 | | 0.9949 | 1.94 | 6000 | 0.2619 | 0.2457 | It achieves the best result on STEP 6000 on the validation set: - Loss: 0.2619 - Wer: 0.2457 ### Framework versions - Transformers 4.17.0.dev0 - Pytorch 1.10.2+cu102 - Datasets 1.18.2.dev0 - Tokenizers 0.11.0 ### Evaluation Commands 1. To evaluate on mozilla-foundation/common_voice_7 with split test bash python eval.py --model_id Plim/xls-r-300m-fr --dataset mozilla-foundation/common_voice_7_0 --config fr --split test 2. To evaluate on speech-recognition-community-v2/dev_data bash python eval.py --model_id Plim/xls-r-300m-fr --dataset speech-recognition-community-v2/dev_data --config fr --split validation --chunk_length_s 5.0 --stride_length_s 1.0