--- language: - gl license: apache-2.0 tags: - automatic-speech-recognition - generated_from_trainer - gl - hf-asr-leaderboard - model_for_talk - mozilla-foundation/common_voice_7_0 - robust-speech-event datasets: - mozilla-foundation/common_voice_7_0 model-index: - name: XLS-R-300M - Galician results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 7.0 type: mozilla-foundation/common_voice_7_0 args: gl metrics: - name: Test WER type: wer value: 101.54 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: gl metrics: - name: Test WER type: wer value: 105.69 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: gl metrics: - name: Test WER type: wer value: 101.95 --- # wav2vec2-large-xls-r-300m-galician 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_7_0 - GL dataset. It achieves the following results on the evaluation set: - Loss: 0.1525 - Wer: 0.1542 ## 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: 7e-05 - train_batch_size: 32 - eval_batch_size: 32 - 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: 20.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 3.0067 | 4.35 | 500 | 2.9632 | 1.0 | | 1.4939 | 8.7 | 1000 | 0.5005 | 0.4157 | | 0.9982 | 13.04 | 1500 | 0.1967 | 0.1857 | | 0.8726 | 17.39 | 2000 | 0.1587 | 0.1564 | ### Framework versions - Transformers 4.16.0.dev0 - Pytorch 1.10.1+cu102 - Datasets 1.17.1.dev0 - Tokenizers 0.11.0