--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - minds14 metrics: - accuracy model-index: - name: audio_classification results: - task: name: Audio Classification type: audio-classification dataset: name: minds14 type: minds14 config: en-US split: train args: en-US metrics: - name: Accuracy type: accuracy value: 0.02654867256637168 --- # audio_classification (default from Skill Academy, I just learn and run the program provided) This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset. It achieves the following results on the evaluation set: - Loss: 2.6736 - Accuracy: 0.0265 ## 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | No log | 0.8 | 3 | 2.6313 | 0.1062 | | No log | 1.8667 | 7 | 2.6508 | 0.0708 | | 2.6379 | 2.9333 | 11 | 2.6587 | 0.0531 | | 2.6379 | 4.0 | 15 | 2.6631 | 0.0442 | | 2.6379 | 4.8 | 18 | 2.6712 | 0.0354 | | 2.6277 | 5.8667 | 22 | 2.6724 | 0.0354 | | 2.6277 | 6.9333 | 26 | 2.6745 | 0.0177 | | 2.6257 | 8.0 | 30 | 2.6736 | 0.0265 | ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1