--- license: apache-2.0 base_model: facebook/wav2vec2-large-xlsr-53 tags: - generated_from_trainer datasets: - common_voice_13_0 metrics: - wer model-index: - name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod12 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_13_0 type: common_voice_13_0 config: id split: test args: id metrics: - name: Wer type: wer value: 0.48354535398230086 --- # wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod12 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: 0.4926 - Wer: 0.4835 ## 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: 3e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 9 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 2.8927 | 1.8 | 1000 | 2.8756 | 1.0 | | 1.2282 | 3.6 | 2000 | 0.8005 | 0.6955 | | 0.79 | 5.4 | 3000 | 0.5742 | 0.5471 | | 0.6958 | 7.19 | 4000 | 0.5083 | 0.4917 | | 0.7162 | 8.99 | 5000 | 0.4926 | 0.4835 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2