--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - superb metrics: - accuracy model-index: - name: wav2vec2-base-finetuned-ks-balanced2 results: - task: name: Audio Classification type: audio-classification dataset: name: superb type: superb config: ks split: validation args: ks metrics: - name: Accuracy type: accuracy value: 0.48602530155928214 --- # wav2vec2-base-finetuned-ks-balanced2 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. It achieves the following results on the evaluation set: - Loss: 1.6199 - Accuracy: 0.4860 ## 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: 64 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.4624 | 0.99 | 79 | 1.8039 | 0.4685 | | 0.8255 | 1.99 | 159 | 1.6513 | 0.4843 | | 0.6409 | 3.0 | 239 | 1.6199 | 0.4860 | | 0.5099 | 4.0 | 319 | 1.6686 | 0.4790 | | 0.4903 | 4.95 | 395 | 1.7152 | 0.4682 | ### Framework versions - Transformers 4.33.2 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.13.3