--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: wav2vec2-large-xls-r-300m-dementianet results: [] --- # wav2vec2-large-xls-r-300m-dementianet This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3430 - Accuracy: 0.4062 ## 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: 0.0001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 22 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.3845 | 3.33 | 40 | 1.3556 | 0.3125 | | 1.3659 | 6.67 | 80 | 1.3602 | 0.3125 | | 1.3619 | 10.0 | 120 | 1.3569 | 0.3125 | | 1.3575 | 13.33 | 160 | 1.3509 | 0.3125 | | 1.3356 | 16.67 | 200 | 1.3599 | 0.3125 | | 1.3166 | 20.0 | 240 | 1.3430 | 0.4062 | ### Framework versions - Transformers 4.14.1 - Pytorch 1.10.0+cu111 - Datasets 1.16.1 - Tokenizers 0.10.3