--- license: apache-2.0 tags: - generated_from_trainer base_model: facebook/wav2vec2-large-xlsr-53 datasets: - common_voice_13_0 metrics: - wer model-index: - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11 results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: common_voice_13_0 type: common_voice_13_0 config: id split: test args: id metrics: - type: wer value: 0.9777378318584071 name: Wer --- # wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11 This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset. It achieves the following results on the evaluation set: - Loss: 1.3207 - Wer: 0.9777 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 464 | 2.8781 | 1.0 | | 3.005 | 2.0 | 928 | 2.5395 | 1.0 | | 2.7477 | 3.0 | 1392 | 1.6528 | 0.9993 | | 1.9398 | 4.0 | 1856 | 1.3991 | 0.9854 | | 1.4528 | 5.0 | 2320 | 1.3207 | 0.9777 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2