--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - minds14 metrics: - accuracy model-index: - name: my_awesome_mind_model 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: 0.061946902654867256 --- # my_awesome_mind_model 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: 2.6953 - Accuracy: 0.0619 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - 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 | 2.6477 | 0.0708 | | No log | 1.9333 | 7 | 2.6612 | 0.0619 | | 2.6309 | 2.8 | 10 | 2.6706 | 0.0708 | | 2.6309 | 3.9333 | 14 | 2.6782 | 0.0796 | | 2.6309 | 4.8 | 17 | 2.6847 | 0.0619 | | 2.6133 | 5.9333 | 21 | 2.6933 | 0.0619 | | 2.6133 | 6.8 | 24 | 2.6951 | 0.0619 | | 2.6133 | 7.9333 | 28 | 2.6950 | 0.0619 | | 2.603 | 8.5333 | 30 | 2.6953 | 0.0619 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3