--- license: apache-2.0 base_model: facebook/wav2vec2-large-xlsr-53 tags: - generated_from_trainer datasets: - xtreme_s metrics: - wer model-index: - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod6 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: xtreme_s type: xtreme_s config: fleurs.id_id split: test args: fleurs.id_id metrics: - name: Wer type: wer value: 0.50321808112558 --- # wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod6 This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the xtreme_s dataset. It achieves the following results on the evaluation set: - Loss: 0.8186 - Wer: 0.5032 ## 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: 0.001 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 600 - num_epochs: 60 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 4.9714 | 18.18 | 300 | 2.8507 | 1.0 | | 1.2966 | 36.36 | 600 | 0.8132 | 0.6056 | | 0.1563 | 54.55 | 900 | 0.8186 | 0.5032 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1