--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - audiofolder metrics: - accuracy model-index: - name: wav2vec2-base-finetuned-ks-open-close results: - task: name: Audio Classification type: audio-classification dataset: name: audiofolder type: audiofolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.998286586955712 --- # wav2vec2-base-finetuned-ks-open-close This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0100 - Accuracy: 0.9983 ## 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: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0866 | 1.0 | 209 | 0.0388 | 0.9956 | | 0.021 | 2.0 | 419 | 0.0162 | 0.9978 | | 0.0172 | 3.0 | 629 | 0.0102 | 0.9985 | | 0.0195 | 4.0 | 839 | 0.0083 | 0.9991 | | 0.0188 | 4.98 | 1045 | 0.0100 | 0.9983 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1